Quantitative Pupillometry/Pupillography

Number: 0879

Table Of Contents

Applicable CPT / HCPCS / ICD-10 Codes


Scope of Policy

This Clinical Policy Bulletin addresses quantitative pupillometry and chromatic pupillography.

Experimental and Investigational

  1. Aetna considers the use of quantitative pupillometry/pupillography experimental and investigational for all indications including the following (not an all-inclusive list) because its effectiveness has not been established:

    1. Acute mountain sickness
    2. Age-related macular degeneration (monitoring the progression of disease and assessing changes in retinal function that result from treatments)
    3. Alzheimer’s disease
    4. As an indicator of mid-brain compression due to supratentorial ischemic stroke or primary intra-parenchymal hemorrhage
    5. As a marker for depression
    6. Brain death determination
    7. Brain injury
    8. Congenital central hypoventilation syndrome
    9. Detection of autonomic dysfunction in individuals with multiple sclerosis
    10. Detection of impaired cerebral autoregulation in critically ill persons
    11. Determination of autonomic nerve activity during anti-psychotic treatment
    12. Diagnosis and evaluation of treatment success in non-convulsive status epilepticus
    13. Discriminating compressive lesions from microvascular ischemic third nerve palsy
    14. Evaluation of hypersomnolence
    15. Excessive sleepiness/narcolepsy
    16. Glaucoma
    17. Impaired or loss of consciousness
    18. Management of individuals undergoing surgical resection of pituitary tumors
    19. Monitoring the severity of diabetic retinopathy
    20. Neuromonitoring of delirium in sedated mechanically ventilated critically ill persons
    21. Pain assessment
    22. Parkinson disease
    23. Prediction of anisocoria in individuals with acute neurologic injuries
    24. Prediction of clinical improvement during lumbar drain trials in individuals with normal pressure hydrocephalus undergoing temporary cerebrospinal fluid diversion
    25. Prediction of outcome after cardiac arrest
    26. Prediction of post-operative opioid-induced respiratory depression
    27. Pre-transplant screening and post-transplant monitoring in persons undergoing liver transplantation
    28. Rheumatic diseases (e.g., rheumatoid arthritis, Sjogren's syndrome, systemic lupus erythematosus, and systemic sclerosis)
    29. Screening for elevated intra-cranial pressure.
  2. Aetna considers the use of chromatic pupillography experimental and investigational for the following (not an all-inclusive list) because its effectiveness has not been established:

    1. For detection of glaucoma
    2. For detection of Leber congenital amaurosis
    3. For detection of optic nerve diseases (e.g., optic neuritis and non-arteritic anterior ischemic optic neuropathy)
    4. For detection of retinitis pigmentosa
    5. For evaluation of Gaucher disease
    6. For evaluation of hemianopia
    7. For monitoring of progression of retinal and optic nerve diseases or recovery after treatment.


CPT Codes / HCPCS Codes / ICD-10 Codes

Code Code Description

CPT codes not covered for indications listed in the CPB:

Quantitative pupillography – no specific code:

95919 Quantitative pupillometry with physician or other qualified health care professional interpretation and report, unilateral or bilateral

Other CPT codes related to the CPB:

62272 Spinal puncture, therapeutic, for drainage of cerebrospinal fluid (by needle or catheter)

ICD-10 codes not covered for indications listed in the CPB (not all inclusive):

A18.59 Other tuberculosis of eye
A50.44 Late congenital syphilitic optic nerve atrophy
A52.15 Late syphilitic neuropathy
C72.30 - C72.32 Malignant neoplasm of optic nerve
C75.1 Malignant neoplasm of pituitary gland
D35.2 Benign neoplasm of pituitary gland
D44.3 Neoplasm of uncertain behavior of pituitary gland
D75.1 Secondary polycythemia [acute mountain sickness]
E11.311 – E11.3599 Type 2 diabetes mellitus with unspecified, mild nonproliferative, moderate nonproliferative, severe nonproliferative, proliferative diabetic retinopathy
F05 Delirium due to known physiological condition [neuromonitoring in sedated mechanically ventilated critically ill persons]
F06.0, F06.2, F23, F24, F28, F29 Psychosis
F32.0 - F32.A Depressive episode
F33.0 - F33.9 Major depressive disorder, recurrent
G20 - G21.9 Parkinson's disease
G30.0 - G30.9 Alzheimer's disease
G35 Multiple sclerosis
G36.0 Neuromyelitis optica [Devic]
G40.901 Epilepsy, unspecified, not intractable, with status epilepticus
G40.911 Epilepsy, unspecified, intractable, with status epilepticus
G47.00 - G47.9 Sleep disorders
G91.2 (Idiopathic) normal pressure hydrocephalus
G93.2 Benign intracranial hypertension
G93.5 Compression of brain
H33.001 - H35.23 Retinal detachments, occlusions and retinopathy
H35.30 - H35.329 Age-related macular degeneration
H35.40 - H35.469 Peripheral retinal degeneration
H35.50 Unspecified hereditary retinal dystrophy [Leber congenital amaurosis]
H35.52 Retinitis pigmentosa
H35.60 - H35.63 Retinal hemorrhage
H35.70 - H35.739 Separation of retinal layers
H35.81 - H35.89 Other specified retinal disorders
H40.001 - H42 Glaucoma
H44.2C1 - H44.2C9 Degenerative myopia with retinal detachment
H46.00 - H46.9 Optic neuritis
H47.011 - H47.019 Ischemic optic neuropathy
H47.021 - H47.029 Hemorrhage in optic nerve sheath
H47.031 - H47.039 Optic nerve hypoplasia
H47.091 - H47.099 Other disorders of optic nerve, not elsewhere classified
H47.20 Unspecified optic atrophy
H47.211 - H47.219 Optic nerve atrophy
H47.22 Hereditary optic atrophy
H47.231 - H47.239 Glaucomatous optic atrophy
H47.291 - H47.299 Other optic atrophy
H49.00 - H49.03 Third [oculomotor] nerve palsy
H53.461 - H53.469 Homonymous bilateral field defects
H57.02 Anisocoria [Anisocoria and acute neurologic injuries]
I46.2 - I46.9 Cardiac arrest
I61.0 - I61.9 Nontraumatic intracerebral hemorrhage
I63.00 - I63.9 Cerebral infarction
M05.00 - M14.89 Rheumatoid arthritis and other inflammatory polyarthropathies
M32.0 - M32.9 Systemic lupus erythematosus
M34.0 - M34.9 Systemic sclerosis [scleroderma]
M35.00 - M35.09 Sicca syndrome [Sjögrens]
Q14.1 Congenital malformation of retina
R06.03 Acute respiratory distress [respiratory depression]
R40.0 Somnolence [impaired]
R55 Syncope and collapse
S06.0x0A – S06.9x9S Intracranial injury
T40.2X5A - T40.2X5S Adverse effect of other opioids [morphine]
T70.29XA – T70.29XS Other effects of high altitude [acute mountain sickness]
Z48.21 - Z48.298 Aftercare following organ transplant [liver transplantation]
Z76.82 Awaiting organ transplant status [liver transplantation]


Pupillary examination has been used as a basic measure in critically ill patients and is important for the prognosis and management of disease.  Traditionally, pupillary measurements have been carried out in a subjective manner – by means of a pen flash-light to evaluate for reactivity and a pupil gauge for pupil size.  Pupillometry refers to an objective way of measuring the diameter of the pupil.   The NeurOptics NPi-100 Pupillometer is a hand-held infrared device that allows for objective measurement of pupillary light reflex and pupil size.  Moreover, the numeric scale of the Neurological Pupil index (NPi), allows for a more rigorous interpretation and classification of the pupillary response.  The Pupillometer and its NPi scale reduce subjectivity from the measurement by comparing the pupillary light reflex against normative data in the NPi model and automatically deriving whether the pupillary reflex falls within the normal range or outside of the normal range and provide a reliable way to quantitatively classify the pupillary light response. 

While pupillometry has been used in many clinical applications, its clinical value has yet to be established through well-designed studies.

Bertinotti and colleagues (2002) stated that the central and peripheral nervous systems are variably affected in the rheumatic diseases.  Automated standardized infrared pupillometry allows for safe, non-invasive assessment of the pupillary innervation.  Pupillometry has already been used in studying the autonomic nervous system (ANS) in various rheumatic diseases.  In systemic lupus erythematosus, the irideal parasympathetic branch of ANS was more affected than the sympathetic branch.  In Sjogren's syndrome, signs of pupillary parasympathetic denervation have been reported.  In rheumatoid arthritis, pupil parasympathetic dysfunction has been shown to correlate with ocular dryness.  In systemic sclerosis (SSc), both sympathetic as well as parasympathetic irideal impairment have been demonstrated.  Besides providing autonomic innervation, sensory nerves fibers are able to control iris diameter.  Exogenous ocular instillation of substance P (SP) can determine an omathropine-resistant, non-cholinergic myosis, acting on specific receptors present on the iris sphincter muscle.  These investigators first studied pupillary SPergic responsiveness in SSc, evaluating SP-stimulated pupillary diameters by pupillometry.  A higher basal and SP-stimulated myosis was found in limited cutaneous SSC (lSSc) versus both diffuse cutaneous SSc (dSSc) and controls, whereas no differences existed between dSSc and controls.  From the literature, the pupillary parasympathetic nervous system seems to be more affected than the sympathetic branch of ANS in the rheumatic diseases characterized by an inflammatory status.  However, the authors found in SSc both sympathetic and parasympathetic pupil control to be equally impaired.  From their experience, the authors concluded that pupillary nervous control is differently affected in the 2 subsets of SSc, and that the SPergic system seems to be impaired only in lSSc.  The role of pupillometry in the management of patients with rheumatic diseases has not been established; its clinical value has to be ascertained via well-designed studies.

Taylor et al (2003) prospectively used a new hand-held pupillometer to assess pupillary function quantitatively.  Repetitive measurements were initially made in more than 300 healthy volunteers aged from 1 to 87 years, providing a total of 2,432 paired (alternative right eye, left eye) measurements under varying light conditions.  The authors studied 17 patients undergoing a variety of non-intracranial, non-ophthalmological, endoscopic, or surgical procedures and 20 seniors in a cardiology clinic to learn more about the effects of a variety of drugs.  Additionally, the authors carried out detailed studies in 26 adults with acute severe head injury in whom intra-cranial pressure (ICP) was continuously monitored.  Finally, 5 patients suffering from sub-arachnoid hemorrhage were also studied.  Quantitative pupillary measurements could be reliably replicated in the study participants.  In healthy volunteers the resting pupillary aperture averaged 4.1 mm and the minimal aperture after stimulation was 2.7 mm, resulting in a 34 % change in pupil size.  Constriction velocity averaged 1.48 +/- 0.33 mm/second.  Pupillary symmetry was striking in both healthy volunteers and patients without intra-cranial or uncorrected visual acuity disorders.  In the 2,432 paired measurements in healthy volunteers, constriction velocity was noted to fall below 0.85 mm/second on only 33 occasions and below 0.6 mm/second on 8 occasions (less than 1 in 310 observations).  In out-patients, the reduction in constriction velocity was observed when either oral or intravenous narcotic agents and diazepam analogs were administered.  These effects were transient and always symmetrical.  Among the 26 patients with head injuries, 8 were found to have elevations ICP above 20 mm Hg and pupillary dynamics in each of these patients remained normal.  In 13 patients with a midline shift greater than 3 mm, elevations of ICP above 20 mm Hg, when present for 15 mins, were frequently associated with a reduction in constriction velocity on the side of the mass effect to below 0.6 mm/second (51 % of 156 paired observations).  In 5 patients with diffuse brain swelling but no midline shift, a reduction in constriction velocities did not generally occur until the ICP exceeded 30 mm Hg.  Changes in the percentage of reduction from the resting state following stimulation were always greater than 10 %, even in patients receiving large doses of morphine and propofol in whom the ICP was lower than 20 mm Hg.  Asymmetry of pupillary size greater than 0.5 mm was observed infrequently (less than 1 %) in healthy volunteers and was rarely seen in head-injured patients unless the ICP exceeded 20 mm Hg.  The authors concluded that pupillometry is a reliable technology capable of providing repetitive data on quantitative pupillary function in states of health and disease.

Chen and colleagues (2005) noted that glaucomatous damage to upper and lower retina is often unequal.  These researchers have developed a rapid, objective, quantitative measure of asymmetry of retinal sensitivity, using infrared pupillometry and pairs of large stimuli that were symmetric about the horizontal meridian.  Results for a group of 11 young subjects free of eye disease indicated that the distribution of asymmetry is close to a normal distribution centered near upper/lower symmetry.  Some subjects showed modest amounts of asymmetry, which was relatively uniform within each eye, and between the 2 eyes, of the subject.  The authors concluded that this approach to determination of asymmetry within an eye is potentially applicable to testing patients with glaucoma.   The narrowness of the distribution should make it possible to detect asymmetries caused by disease.

In a prospective case-control study, Chang et al (2013) developed and validated an associative model using pupillography that best discriminated those with and without glaucoma.  A total of 148 patients with glaucoma (mean age of 67 ± 11 years) and 71 controls (mean age of 60 ± 10 years) were enrolled in this study.  This prototype pupillometer was designed to record and analyze pupillary responses at multiple, controlled stimulus intensities while using varied stimulus patterns and colors.  These investigators evaluated 3 approaches:
  1. comparing the responses between the 2 eyes;
  2. comparing responses to stimuli between the supero-nasal and infero-nasal fields within each eye; and
  3. calculating the absolute pupil response of each individual eye.
Associative models were developed using step-wise regression or forward selection with Akaike information criterion and validated by 5-fold cross-validation.  These researchers assessed the associative model using sensitivity, specificity and the area-under-the-receiver operating characteristic curve (AUC).  Persons with glaucoma had more asymmetric pupil responses in the 2 eyes (p < 0.001); between supero-nasal and infero-nasal visual field within the same eye (p = 0.014); and smaller amplitudes, slower velocities and longer latencies of pupil responses compared to controls (all p < 0.001).  A model including age and these 3 components resulted in an AUC of 0.87 (95 % confidence interval [CI]: 0.83 to 0.92) with 80 % sensitivity and specificity in detecting glaucoma.  This result remained robust after cross-validation.  The authors concluded that using pupillography, they were able to discriminate among persons with glaucoma and those with normal eye examinations.  Moreover, they stated that with refinement, pupil testing may provide a simple approach for glaucoma screening.

Kjesbu et al (2005) noted that the iris is a dynamic organ in which the ANS regulates the activity.  Iris activity reflects physiological reactions to different sensory stimuli, resulting in a variation in pupil size.  There are many different diagnostic tools that assess iris activity.  These investigators reviewed the methods of pupillary assessment as a research tool and in clinical use.  The basis for this study was obtained by searches on Medline and ISI Web of Knowledge.  Reference lists were further checked for other relevant studies.  The authors stated that pupillometry is a research tool that is adopted in an increasing number of medical fields.  In the past, this method was used mostly within ophthalmology and neurology; today it has spread to a wide range of medical fields (e.g., pharmacology and physiology).  There are continuous improvements in the flexibility and recording capacity of pupillometers and they are used in an increasing number of medical fields, though they are still most useful within research.

Fountas et al (2006) stated that pupillometry has been widely employed in the evaluation of a large number of pathological conditions, including intra-cranial pathology.  The recent introduction of a portable, user-friendly, infrared pupillometer (ForSite, NeurOptics Inc., Irvine, CA) has enabled the accurate and reproducible measurement of several pupillary parameters, such as maximum and minimum apertures, constriction and dilation velocities, and latency period.  It should be noted that various clinical conditions, especially neurological and ocular diseases, as well as numerous medications, may interfere with the measurements.  Furthermore, a number of physiological parameters (e.g., the intensity of retinal illumination, the level of patient's alertness, the intensity of ambient light, and the time of day that the examination is performed) may alter the obtained values.  The potential implications of pupillometry in the clinical assessment of neurosurgical patients, including its complex relationship to ICP changes, mandate the undertaking of prospective clinical studies validating the clinical significance of this non-invasive, diagnostic modality.

Wilson et al (2008) noted that gross pupil dynamics were used as an indirect measure of brain function.  Changes in hypoxia and ICP are thought to alter pupil responses to light.  These investigators assessed a portable hand-held pupillometer in the field investigating the changes in pupil size, speed of reaction, and rate of constriction/dilatation with hypoxia induced by changes in altitude.  A correlation between pupil dynamics and acute mountain sickness (AMS) was sought.  A total of 17 volunteers were studied following acute exposure to 3,450 m and then during a trek to 4,770 m in Ladakh, India.  The pupillometer was used to record maximum and minimum pupil diameter in response to a standard light source with calculation of latency, constriction and dilatation velocities.  Acute mountain sickness was recorded using Lake Louise self-completed questionnaires both in the morning and afternoon on each day.  Acute altitude exposure resulted in a significant reduction of percentage change in pupil size (36.5 % to 24.1 % p = 0.001), significant delay in pupillary contraction (latency; 0.208 to 0.223 seconds p = 0.015) and a significant slowing of the rate of contraction (constriction velocity; -2.77 mm/s to -1.75 mm/s p = 0.012).  These changes reverted to normal during a period of acclimatization.  A significant diurnal variation in pupil size was also observed.  There was no significant difference between subjects with and without AMS.  The authors concluded that the hand-held pupillometer is a suitable tool for monitoring changes in pupil dynamics in the field.  With acute exposure to hypobaric hypoxia associated with an ascent to a moderate altitude, there is a general slowing of pupil function that reverted to normal within a few days of acclimatization.  There appears to be a marked diurnal variation in pupil size.  While the measurements demonstrated an effect of hypoxia on cerebral function, but these changes did not relate to moderate AMS.

Yan et al (2009) performed an observational study of pupil assessment with automated pupillometry in clinical liver transplantation (LT) settings, including pre-transplant evaluations and post-transplant surveillance.  The results showed that unconscious patients (grade 4 hepatic encephalopathy) had a prolonged latency phase (left side: 283 +/- 80 milliseconds; right side: 295 +/- 96 milliseconds) and a reduced pupillary constrictive ratio (left direct response: 0.23 +/- 0.10; left indirect response: 0.21 +/- 0.07; right direct response: 0.20 +/- 0.08; right indirect response: 0.21 +/- 0.08) in comparison with normal and conscious patients.  After liver transplantation, the recovery of pupillography in these patients was slower than that in conscious patients.  However, the surviving recipients without major complications all had a gradual recovery of pupillary responses, which occurred on the first or second post-transplant day.  These researchers also reported 4 cases of futile LT in the absence of pre-transplant pupillary responses and other pupillary abnormalities revealed by automated pupillometry in this study.  The authors concluded that patients with grade 4 hepatic encephalopathy had a sluggish pupil response and a delayed recovery pattern after LT.  They stated that an automated pupillometer is potentially a supplementary device for pre-transplant screening and post-transplant monitoring in patients undergoing LT, but further prospective studies are needed.

Payen et al (2012) noted that pupillary size reflects the balance between sympathetic and parasympathetic systems.  Due to technological advances, accurate and repeated measurements of pupillary size are possible using infrared, video-recorded pupillometers.  Two pupil size reflexes were assessed:
  1. the pupillary reflex dilation during noxious stimulation; and
  2. the pupil light reflex when the pupil was exposed to the light.
The pupillary reflex dilation estimated the level of analgesia in response to a painful procedure or to a calibrated noxious stimulus, i.e., tetanic stimulus, in non-verbal patients.  This might be of particular interest in optimizing the management of opioids in anaesthetized patients and in assessing pain levels in the intensive care unit.  The pupil light reflex measurement was part of the routine monitoring for severely head-injured patients.  The authors stated that the impact of pupillometry in this condition remains to be determined.

Patwari et al (2012) noted that congenital central hypoventilation syndrome (CCHS) is characterized by alveolar hypoventilation, ANS dysregulation (ANSD), and mutations in the paired-like homeobox 2B (PHOX2B) gene.  Autonomic nervous system dysregulation in CCHS affects multiple systems and includes ophthalmologic abnormalities.  These researchers hypothesized that quantitative pupil measures, obtained using pupillometry, would vary between cases with CCHS and controls and within those with CCHS by PHOX2B genotype.  A total of 316 monocular measurements were taken under dark-adapted conditions with a fixed light stimulus from 22 PHOX2B mutation-confirmed cases with CCHS and 68 healthy controls.  Measures known to be illustrative of sympathetic and parasympathetic response (pre-stimulus, maximum pupil diameter, percentage of pupil constriction after light stimulus, and average constriction and dilation velocities) were significantly reduced in those with CCHS as compared with controls (all p < 0.05).  The authors concluded that these reductions were indicative of both sympathetic and parasympathetic deficits in CCHS, which is in keeping with the role of PHOX2B in ANS development.  An inverse linear relationship was apparent in pupil diameter and velocity measurements among the cases with CCHS with the most common heterozygous PHOX2B polyalanine expansion repeat mutations, suggesting a graded phenotype/genotype dose response based on polyalanine repeat length.  They stated that these results confirmed their central hypotheses while offering the first objective measures of pupillary dysfunction and ophthalmologic-specific ANSD in CCHS.

An UpToDate review on "Disorders of ventilatory control" (Johnson, 2013) states that "Congenital central hypoventilation syndrome (CCHS) is associated with a nearly absent respiratory response to hypoxia and hypercapnia, no respiratory discomfort during CO2 inhalation, mildly elevated arterial carbon dioxide tension (PaCO2) during wakefulness, and markedly elevated PaCO2 during non-REM sleep.  Patients with CCHS increase their ventilation and maintain relatively normal PaCO2 levels during exercise, and lower their PaCO2 during passive leg cycling due to nonchemoreceptive inputs.  CCHS can occur in association with Hirschsprung's disease, a condition characterized by abnormalities of the cholinergic innervation of the gastrointestinal tract.  The estimated incidence of Hirschsprung's disease among patients with CCHS (also called Ondine-Hirschsprung syndrome or Haddad syndrome) ranges from 10 to 50 percent.  Patients with CCHS are also at increased risk of neuroblastoma and ganglioneuroma.  These associations, and the demonstration of subtle autonomic abnormalities in relatives of patients with CCHS, suggest that autonomic neuropathy, particularly of the parasympathetic system, is pathophysiologically important in CCHS.  Abnormalities of the gene encoding the transcription factor PHOX2b, which is active during neuronal development, have been implicated in the pathogenesis of CCHS".  This review does not mention the use of pupillometry as a management tool.  Thus the role of pupillometry in the management of CCHS has yet to be established.

Martinez-Ricarte et al (2013) stated that pupil assessment is a fundamental part of the neurological examination.  Size and reactivity to light of each pupil should be recorded periodically since changes in these parameters may represent the only detectable sign of neurological deterioration in some patients.  However, there is great intra-observer and inter-observer variability in pupil examination due to the influence of many factors, such as the difference in ambient lighting, the visual acuity and experience of the examiner, the intensity of the luminous stimulus, and the method used to direct this stimulus.  In recent years, digital cameras have incorporated infrared devices allowing the development of user-friendly portable devices that permit repeated, non-invasive examinations of pupil size and its reactivity to light with an objective, accessible and inexpensive method.  These researchers described the fundamentals of infrared pupillometry and discussed potential applications in the monitoring of neuro-critical patients.  They also presented some recommendations in the routine assessment of pupils in neuro-critical patients.  The authors concluded that the possibility of evaluating the changes in pupil reactivity in an early, objective and almost continuous way provides a new non-invasive monitoring method.  This method could improve the predictive factor of neurological deterioration and the bedside monitoring of the neurological state of the patient, avoiding unnecessary examinations and enabling early therapeutic intervention.

An UpToDate review on "Quantifying sleepiness" (Freedman, 2013) states that "Pupillometry is not widely used because the equipment is not readily available.  Further research is necessary to determine its role in the assessment of excessive sleepiness".

In a single-blinded, observational study, Olson et al (2016) examined inter-rater reliability of pupil exam findings between 2 practitioners and between practitioners and a pupillometer. From 2,329 paired assessments, the inter-rater reliability between practitioners was only moderate for pupil size (k = 0.54), shape (k = 0.62), and reactivity (k = 0.40). Only 33.3 % of pupils scored as non-reactive by practitioners were scored as non-reactive by pupillometry. The authors concluded that despite the strong emphasis placed on the traditional pupil examination, especially for patients with a neurological illness, there is limited inter-rater reliability for subjective scoring of pupillary assessments. Thus, the use of automated pupillometers should be examined as a potential method to increase the reliability of measuring of pupil reactivity.

Brain Death

Olgun et al (2015) noted that the determination of brain death in neonates, infants, children and adults relies on a clinical diagnosis based on the absence of neurological function with a known irreversible cause of brain injury. Evaluation of pupil size and non-reactivity is a requisite for determination of brain death. There are no studies in the literature that quantitatively assess pupil size in brain dead children and adults. Infants, children and adults diagnosed with brain death were included in the study. Pupils were measured with a quantitative pupillometer (Forsite; Neuroptics, Irvine, CA). Median, minimum and maximum pupil sizes were documented and the results were adjudicated for age, vasopressor use and temperature. Median right and left pupil sizes were 5.01 ± 0.85 mm and 5.12 ± 0.87 mm, respectively, with a range between 3.69 and 7.34 mm. Pediatric pupils were larger than adult pupils (right pupil 5.53 versus 4.73 mm p: 0.018; left pupil 5.87 versus 4.77 mm p: 0.03), and there was no correlation of pupil size with temperature or increasing number of vasopressors. The authors concluded that this was the first study in the literature objectively evaluating pupil sizes in infants, children and adults diagnosed with brain death. They observed variation between observed pupil size and that expected based on brain death determination guidelines.

Gaucher Disease

Narita et al (2014) stated that the hallmark of neuronopathic Gaucher disease (GD) is oculomotor abnormalities, but ophthalmological assessment is difficult in uncooperative patients. Chromatic pupillometry is a quantitative method to assess the pupillary light reflex (PLR) with minimal patient cooperation. These researchers examined if chromatic pupillometry could be useful for neurological evaluations in GD. In these neuronopathic GD patients, red light-induced PLR was markedly impaired, whereas blue light-induced PLR was relatively spared. In addition, patients with non-neuronopathic GD showed no abnormalities. The authors concluded that these novel findings showed that chromatic pupillometry is a convenient method to detect neurological signs and monitor the course of disease in neuronopathic GD.

Furthermore, UpToDate reviews on "Gaucher disease: Pathogenesis, clinical manifestations, and diagnosis" (Hughes, 2015a) and "Gaucher disease: Initial assessment, monitoring, and clinical course" (Hughes, 2015b) do not mention pupillometry as a diagnostic tool.

Pain Assessment

In a single-center, prospective, observational study, Connelly et al (2014) explored proof of concept for the use of pupillometry in pediatric patients. Changes in pupil parameters before and after opioid exposure also were evaluated. Children 9 to 17 years of age undergoing elective surgical correction of pectus excavatum were enrolled into a protocol approved by the human ethical committee (institutional review board). Pupil size and reactivity were measured using a hand-held pupillometer. Pain was assessed using age-appropriate, validated pain self-report scales. A total of 30 patients were enrolled. Each point change on a 10-cm visual analog pain intensity scale was associated with a statistically significant mean change of 0.11 mm/s in maximum pupil constriction velocity, and of approximately 0.4 % in pupil diameter. As expected, there was an association between total opioid dose (expressed as morphine equivalents) and pupil diameter. Age, sex and baseline anxiety scores did not correlate significantly with pupillary response. The authors concluded that the association of maximum pupillary constriction velocity and diameter with pain scores illustrated the potential for using pupillometry as a non-invasive method to objectively quantitate pain response/intensity in children. They stated that the technique holds promise as a pharmacodynamic "tool" to assess opioid response in pediatric patients.

Brain Injury / Impaired/Loss of Consciousness

Truong and Ciuffreda (2016) examined if mild traumatic brain injury (mTBI) adversely affects the PLR. The PLR was evaluated in mTBI and compared to normal individuals under a range of test conditions.  A total of 9 pupil parameters (maximum, minimum and final pupil diameter, latency, amplitude and peak and average constriction and dilation velocities) and 6 stimulus conditions (dim pulse, dim step, bright pulse, bright step, bright red step and bright blue step) were assessed in 32 adults with mTBI (21 to 60 years of age) and compared to 40 normal (22 to 56 years of age).  The Neuroptics, infrared, DP-2000 binocular pupillometer was used (30-Hz sampling rate; 0.05 mm resolution) with binocular stimulation and recording.  Different test conditions allowed for discrimination of different parameters.  For any of the given 6 test conditions, 5-to-8 of the 9 pupillary parameters were statistically different (p < 0.05) between the 2 diagnostic groups.  The most promising parameters for diagnostic differentiation were constriction latency, all pupillary diameters, average constriction velocity and peak dilation velocity.  The authors concluded that mTBI adversely affects the PLR suggesting an impairment of the ANS.  They stated that these findings suggested the potential for quantitative pupillary dynamics to serve as an objective mTBI biomarker.

Narayan and colleagues (2018) noted that TBI is a leading cause of pediatric morbidity and mortality worldwide and ICP monitoring plays a crucial role in its management.  Based on existing literature, these investigators reviewed the current practicing non-invasive ICP monitoring devices and their accuracy in predicting increased ICP in pediatric TBI.  They carried out a thorough literature search on PubMed, Medline, and the Cochrane database, articles were selected systematically and reviewed completely, and relevant data were summarized and discussed.  A total of 27 articles pertaining to pediatric TBI were included and reviewed.  These researchers found various modalities of non-invasive ICP monitoring devices used over the last few years.  The non-invasive modalities so far attempted in pediatric TBI and so reviewed were transcranial Doppler, optic nerve sheath diameter, oto-acoustic emission, near-infrared spectroscopy, contrast-enhanced ultrasonography, and quantitative pupillometry.  The authors conclude that invasive monitoring methods are the current gold standard for monitoring ICP; however, complications caused by their invasive nature are of concern.  Of all the no-ninvasive methods based on the literature, these investigators found transcranial Doppler and optic nerve sheath diameter assessment to be the best tools to monitor ICP in pediatric TBI.  They stated that the promising results and developments of non-invasive ICP monitoring modalities with its ideal features of high sensitivity, diagnostic accuracy, and simple acquisition technique may make it the future of neuro-intensive monitoring in pediatric TBI.

Jahns and colleagues (2019) noted that elevated ICP is frequent after TBI and may cause abnormal pupillary reactivity, which in turn is associated with a worse prognosis.  Using automated IR pupillometry, these researchers examined the relationship between (NPi and invasive ICP in patients with severe TBI.  This was an observational cohort of consecutive subjects with severe TBI (Glasgow Coma Scale [GCS] of less than 9 with abnormal lesions on head CT) who underwent parenchymal ICP monitoring and repeated NPi assessment with the NPi-200® pupillometer.  These investigators examined NPi trends over time (4 consecutive measurements over intervals of 6 hours) prior to sustained elevated ICP of greater than 20 mmHg.  They further analyzed the relationship of cumulative abnormal NPi burden (%NPi values of less than 3 during total ICP monitoring time) with intra-cranial hypertension (ICHT)-categorized as refractory (ICHT-r; requiring surgical decompression) versus non-refractory (ICHT-nr; responsive to medical therapy)-and with the 6-month Glasgow Outcome Score (GOS).  A total of 54 patients were studied (mean age of 54 ± 21 years, 74 % with focal injuries on CT), of whom 32 (59 %) had ICHT.  Among subjects with ICHT, episodes of sustained elevated ICP (n = 43, 172 matched ICP-NPi samples; baseline ICP [T- 6 hours] 14 ± 5 mmHg versus ICPmax [T0 hour] 30 ± 9 mmHg) were associated with a concomitant decrease of the NPi (baseline 4.2 ± 0.5 versus 2.8 ± 1.6, p < 0.0001 ANOVA for repeated measures).  Abnormal NPi values were more frequent in patients with ICHT-r (n = 17; 38 [3 to 96] % of monitored time versus 1 [0 to 9] % in patients with ICHT-nr [n = 15] and 0.5 [0 to 10] % in those without ICHT [n = 22]; p = 0.007) and were associated with an unfavorable 6-month outcome (15 [1 to 80] % in GOS 1 to 3 versus 0 [0 to 7] % in GOS 4 to 5 patients; p = 0.002).  The authors concluded that in patients with severe TBI and abnormal intra-cranial CT lesions at risk for secondary intra-cranial hypertension, sustained elevated ICP was associated with impaired NPi, which in turn may recover to normal values upon ICP treatment with osmotherapy.  Sustained abnormalities of the NPi were more frequently observed in patients with refractory ICP requiring decompressive hemi-craniectomy and were associated with a worse 6-month outcome.  These researchers stated that these findings suggested that adding non-invasive NPi to invasive ICP monitoring provided important supplementary diagnostic, therapeutic, and prognostic information to guide the management of severe TBI patients.

The authors stated that this study had several drawbacks.  It was a single-centered trial, and included a relatively limited sample size of patients (n = 54) with severe TBI monitored with ICP who were at high risk for ICHT.  TBI injury subtype was also predominantly focal and included a cohort with a relatively advanced age, thus limiting the generalizability of these findings.  However, the inclusion of a selected and homogeneous TBI cohort also had advantages, as it identified a potential group of severely head-injured patients, in whom the addition of the NPi monitoring could be of particular value and may be helpful for individualized ICP care; and future larger, multi-centered confirmatory studies using combined ICP and NPi monitoring may be warranted.  Additional studies also may help to better refine the role of the NPi as a monitoring tool, its place in ICP management algorithms, and potential role in future guidelines for TBI care.  Episodes of sustained elevated ICP were retained for the analysis based on 3 main criteria: ICP max greater than 20 mmHg for at least 10 mins; at least 3 repeated consecutive NPi measurements during the 6 hours preceding ICP max (and respectively following ICP osmotherapy); and a maximum of 3 episodes per patient.  While this increased data quality (particularly, by avoiding skewing of data) and thus the robustness of the statistical analysis, it may have introduced selection biases.  The NPi data reported during episodes of elevated ICP may not necessarily be representative of average patient NPi during the entire intensive care unit (ICU) stay.  Although all patients had NPi readings taken at least every 2 hours, NPi measurements were more frequent during elevated ICP episodes (at least every hour), and in this case, the lower values were considered for the matching analysis of NPi with ICP.  Finally, there was no important change in the infusion rates of sedatives during analyzed ICP episodes, however, additional sedative boluses were given, and thus (albeit unlikely), these investigators could not completely rule out that this may have at least partly affected the NPi.

Traylor and colleagues (2021) noted that loss of consciousness (LOC) is a hallmark feature in TBI, and a strong predictor of outcomes after TBI.  In a pilot study, these researchers described associations between quantitative IR pupillometry values and LOC, ICHT, and functional outcomes in patients with TBI.  They carried out a prospective study of patients evaluated at a Level 1 trauma center between November 2019 and February 2020.  Pupillometry values including the NPi, constriction velocity (CV), and DV were obtained.  A total of 36 consecutive TBI patients were enrolled.  The median age was 48 years (range of 21 to 86 years).  The mean GCS score on arrival was 11.8 (SD = 4.0).  DV trichotomized as low (less than 0.5 mm/s), moderate (0.5 to 1.0 mm/s), or high (greater than 1.0 mm/s) was significantly associated with LOC (p = 0.02), and the need for emergent intervention (p < 0.01).  No significant association was observed between LOC and NPi (p = 0.16); nor between LOC and CV (p = 0.07).  The authors concluded that the findings of this pilot study suggested that DV, as a discrete variable, was associated with LOC in TBI.  Moreover, these researchers stated that further investigation of the relationship between discrete pupillometric variables and NPi may be valuable to understand the clinical significance of the pupillary light reflex findings in acute TBI.

Trent et al (2023) noted that triage and neurological assessment of the 1.7 million traumatic brain injuries (TBIs) occurring annually is often carried out by nurse practitioners and physician assistants in the emergency department (ED).  Subjective assessments, such as the neurological examination that includes evaluation of the PLR, can contain bias.  Quantitative pupillometry (QP) standardizes and objectifies the PLR examination.  Additional data are needed to determine whether QP can predict neurological changes in patient with TBIs.  In a prospective, observational, clinical trial, these researchers examined the effectiveness of QP in predicting neurological decline within 24 hours of admission following acute TBI.  This study employed pragmatic sampling to evaluate PLR in TBI patients using QP within 24 hours of ED admission.  Chi-square analysis was used to determine change in patient status, via Glasgow Coma Scale (GCS), at baseline and within 24 hours of admission, to the QP.  A total of 95 subjects were included in the analysis; of whom 35 experienced neuro-worsening, defined by change in GCS of greater than 2 within the first 24 hours of admission.  There was a significant association between an abnormal NPi, defined as NPi of less than 3, and neuro-worsening (p < 0.0001).  The sensitivity (51.43 %) and specificity (91.67 %) of abnormal NPi in predicting neuro-worsening varied.  The authors concluded that there was a strong association between abnormal NPi and neuro-worsening in the sample of TBI patients with high specificity and moderate sensitivity.  Moreover, these researchers stated that NPi may be an early indicator of neurological changes within 24 hours of ED admission in patients with TBI.  These findings need to be validated by well-designed studies.

Prediction of Outcome of After Cardiac Arrest

Heimburger and colleagues (2016) noted that predicting outcome after cardiac arrest (CA) is particularly difficult when therapeutic hypothermia (TH) is used. In a prospective observational study, these researchers investigated the performance of quantitative pupillometry and trans-cranial Doppler (TCD) in this context.  This study included 82 post-CA patients.  Quantitative assessment of PLR and TCD measurements of the 2 middle cerebral arteries were performed at admission (day 1) and after 24 hours (day 2) during TH (33 to 35°C) and sedation.  Neurological outcome was assessed at 3 months using cerebral performance category (CPC) scores; patients were classified as having good (CPC 1 to 2) or poor (CPC 3 to 5) outcome.  Prognostic performance was analyzed using area under the receiver operating characteristic curve (AUC-ROC).  Patients with good outcome (n = 27) had higher PLR amplitude than patients with poor outcome (n = 55) both at day 1, 13 % (10 to 18) (median of 25th to 75th percentile) versus 8 % (2 to 11) (p < 0.001), and at day 2, 17 % (13 to 20) versus 8 % (5 to 13) (p < 0.001), respectively.  The AUC-ROC curves at days 1 and 2 were 0.76 (95 % CI: 0.65 to 0.86) and 0.82 (95 % CI: 0.73 to 0.92), respectively.  The best cut-off values of PLR amplitude to predict a 3-month poor outcome were less than 9 % and less than 11 %, respectively.  A PLR amplitude of less than 7 % at day 2 predicted a 3-month poor outcome with a specificity of 100 % (95 % CI: 86 to 100) and a sensitivity of 42 % (95 % CI: 28 to 58).  No differences in TCD measurements were found between the 2 patient groups.  The authors concluded that PLR measurements might be informative in the prediction of outcome of post-CA patients even under sedation and hypothermia.

Oddo and Friberg (2017) stated that delayed awakening after targeted temperature management (TTM) and sedation is frequent among cardiac arrest patients.  Differentiating between prolonged coma and irreversible cerebral damage can be challenging, thus, the utilization of a multi-modal approach is recommended by international guidelines.  These investigators discussed indications and advantages/disadvantages of available modalities for coma prognostication and described new tools to improve the accuracy for outcome prediction.  Studies from the TTM era confirmed that combining neurological examination with electrophysiological assessment [electroencephalography (EEG) and somato-sensory evoked potentials (SSEP) greatly improved coma prognostication.  This combination is recognized as the most useful by many clinicians and appeared widely applicable as part of initial patient assessment.  Additional tests (serum neuron specific enolase and neuroimaging) may be most useful to orient clinical decisions in patients with prolonged coma.  Advanced analysis of EEG and SSEP recordings and the emergence of quantitative pupillometry hold great promise.

In a systematic review and meta-analysis, Kim et al (2022) examined the usefulness of the quantitative pupillary light reflex as a prognostic tool for neurological outcomes in post-cardiac arrest patients treated with targeted temperature management (TTM).  These investigators searched Medline, Embase, and the Cochrane Library (search date: July 9, 2021) for studies on post-cardiac arrest patients treated with TTM that had measured the percent constriction of pupillary light reflex (%PLR) with quantitative pupillometry as well as evaluated the neurological outcome.  For an assessment of the methodological quality of the included studies, 2 authors employed the prognosis study tool independently.  A total of 618 patients from 4 studies were included in this systematic review.   Standardized mean differences (SMDs) were calculated to compare patients with good or poor neurological outcomes.  A higher %PLR measured at 0 to 24 hours following hospital admission was related to good neurological outcomes at 3 months in post-cardiac arrest patients treated with TTM (SMD 0.87; 95 % CI: 0.70 to 1.05; I2 = 0 %).  A higher %PLR amplitude measured at 24 to 48 hours following hospital admission was also associated with a good neurological outcome at 3 months in post-cardiac arrest patients treated with TTM, but with high heterogeneity (SMD of 0.86; 95 % CI: 0.40 to 1.32; I2 = 70 %).  The evidence supporting these findings was of poor quality.  For poor neurological outcome, the prognosis accuracy of %PLR was 9.19 (pooled diagnostic odds ratio [DOR], I2 = 0 %) and 0.75 (AUC).  The authors concluded that this meta-analysis could not reveal that change of %PLR was an effective tool in predicting neurological outcomes for post-cardiac arrest patients treated with TTM owing to a paucity of included studies and the poor quality of the evidence.

In a post-hoc analysis of the TTH48 Trial, Paramanathan et al (2022) examined the long-term prognostic value of NPi in comatose out-of-hospital cardiac arrest patients undergoing TTM.  NPi was assessed from admission and throughout day 3 and linked to the Cerebral Performance Categories score at 6 months.  These researchers compared the prognostic performance of NPi in 65 patients randomized to a target temperature of 33 ± 1°C for 24 or 48 hours.  The NPi values were not different between TTM groups (p > 0.05).  When data were pooled, NPi was strongly associated with neurological outcome at day 1 with a mean NPi of 3.6 (95 % CI: 3.4 to 3.8) versus NPi 3.9 (3.6 to 4.1) in the poor versus good outcome group, respectively (p < 0.01).  At day 2, NPi values were 3.6 (3.1 to 4.0) and 4.1 (3.9 to 4.2) (p = .01) and at day 3, the values were 3.3 (2.6 to 4.0) and 4.3 (4.1 to 4.6), respectively (p < 0.01).  The prognostic ability of NPi, defined by AUC-ROC was best at day 3.  The authors concluded that quantitative pupillometry measured by NPi was not different in the 2 TTM groups, but overall, significantly associated with good and poor neurological outcomes at 6 months.  These researchers stated that NPI has a promising diagnostic accuracy; however, larger studies are needed to clarify the optimal cut-off value and time-points .  These investigators stated that a main drawback of this trial was the relatively small sample size (n = 65) and that NPi was not available for all patient at all time-points.  Patients with good outcome may be discharged from the ICU before day 3 and may explain the increased proportion of poor outcome patients on day 3.

Nyholm et al (2023) stated that quantitative pupillometry is the guideline-recommended method for assessing pupillary light reflex for multi-modal prognostication in comatose patients resuscitated from out-of-hospital cardiac arrest (OHCA); however, threshold values predicting an unfavorable outcome have been inconsistent across studies.  These researchers identified specific thresholds for all quantitative pupillometry parameters.  Comatose post-OHCA patients were consecutively admitted to the cardiac arrest center at Copenhagen University Hospital Rigshospitalet from April 2015 to June 2017.  The parameters of quantitatively assessed pupillary light reflex (qPLR), Neurological Pupil index (NPi), average/max constriction velocity (CV/MCV), dilation velocity (DV), and latency of constriction (Lat) were recorded on the first 3 days after admission.  These investigators evaluated the prognostic performance and identified thresholds achieving zero percent false positive rate (0 % PFR) for an unfavorable outcome of 90-day Cerebral Performance Category (CPC) 3-5.  Treating physicians were blinded for pupillometry results.  Of the 135 post-OHCA patients, the primary outcome occurred for 53 (39 %) patients.  On any day during hospitalization, a qPLR of less than 4 %, NPi of less than 2.45, CV of less than 0.1 mm/s, and an MCV of less than 0.335 mm/s predicted 90-day unfavorable neurological outcome with 0 % false positive rate (FPR; 95 % CI: 0 % to 0 %), with sensitivities of 28 % (17 % to 40 %), 9 % (2 % to 19 %), 13 % (6 % to 23 %), and 17 % (8 % to 26 %), respectively on day 1.  The authors found that specific thresholds of all quantitative pupillometry parameters, measured at any time following hospital admission until day 3, predicted a 90-day unfavorable outcome with 0 % FPR in comatose patients resuscitated from OHCA; however, at 0 % FPR, thresholds resulted in low sensitivity.  Moreover, these researchers stated that these findings should be further validated in larger multi-center clinical trials.

The authors noted that since this was a retrospective study, no control of exposure or outcome assessment could be made.  In addition, specific levels and timing of the withdrawal of sedation for the individual patients were unavailable in this registry.  Anesthesia and opioids could potentially confound measurements of pupillary reflexes.  However, previous studies have found similar results with or without sedation, with the NPi algorithm unaffected by the sedatives/analgesics.  Intra- and inter-observer reproducibility and repeatability were previously validated with low variability in measurements of quantitative pupillometry under the same clinical settings as this study.  Prognostic parameters are generally subjects of self-fulfilling prophecy bias in outcome prediction.  However, as quantitative pupillometry was not included in the clinical neuro-prognostication, treating physicians and outcome assessors were blinded to the results.  The staff conducting the manual assessment of the pupillary light reflex (PLR) for the clinical prognostication was the same that obtained the quantitative pupillometry measurements.  Therefore, before the manual evaluation of the PLR, the assessor could potentially have known the quantitative pupillometry result.  However, the assessors did not take part in the outcome assessment, and the final prognostication also included evaluations of EEG, neuroimaging, and SSEP.

Due to limited data and differences in the timing of measurements (day 1 to 3 versus after day 3) and sample (all patients versus only patients with low expectations for survival), this study did not offer data on the additional prognostic value of quantitative pupillometry, or validate it with independent prognostic value, compared to the other predictors (e.g., SSEP, EEG, and neuron-specific enolase [NSE]).  Even though quantitative pupillometry have previously been reported to increase the sensitivity of SSEP in predicting poor outcome in OHCA patients, it could be argued that it has qualities that differentiate it from other predictors (easy-to-use bedside prognostication tool with high early prognostic value); these researchers strongly recommended that future studies validate the significant contribution of quantitative pupillometry to other predictors.

Pupillography for Age-Related Macular Degeneration

Takayama and colleagues (2016)
  1. evaluated, using pupillography, the difference between eyes affected by age-related macular degeneration (ARMD) and their contralateral normal eyes with regard to the mean relative afferent pupillary defect (RAPD) score, and
  2. determined any correlations between this difference in RAPD score and differences in visual acuity (VA) or ARMD dimensions.
Measurements were made using the RAPDx pupillographer (Konan Medical, Nishinomiya, Japan), which analyzed pupil response to light stimulation.  Both best corrected VA (BCVA; converted to logMAR) and greatest linear dimension (GLD; calculated on the basis of fluorescence angiography [FA] images) were measured.  The correlations between RAPD difference and logMAR difference, and GLD difference were then analyzed.  The study included 32 patients (18 men, 14 women; mean age of 74.8 ± 9.7 years) who had ARMD in 1 eye and a normal fundus in the contralateral eye.  Mean resting pupil diameter, mean latency onset of constriction, mean constriction velocity (VC), and recovery were not significantly different in ARMD eyes compared with normal eyes.  The mean amplitude of constriction was smaller (p = 0.028), and the mean latency of maximum constriction was shorter (p = 0.0013) in ARMD eyes than in normal eyes.  Regarding RAPD scores, there was a significant correlation between VA difference and RAPD score differences of both amplitude (p < 0.001, r = 0.53) and latency (p = 0.034, r = 0.33); GLD difference was also significantly correlated with differences in both amplitude (p = 0.021, r = 0.36) and latency (p = 0.033, r = 0.33) scores; RAPD outcomes were correlated with VA and ARMD dimension.  The authors concluded that automated pupillography may be a useful tool in monitoring the progression of ARMD and assessing changes in retinal function that result from novel interventions.  Moreover, they stated that longitudinal studies are needed to identify more correlations between retinal function and RAPD.

The drawbacks of this study included its small sample size (n = 32), the use of only 30° light stimulation, and the lack of corroborating focal macular electroretinogram (ERG) measurement or scotoma caused by ARMD.  The RAPDx can be freely modified in terms of range and patterns of stimulation.  Conversely, the focal macular ERG can only be modified in terms of an area of 5°, 10°, 15°, and 30° within the measured area of focal retinal function.  Thus, future studies can be expected to detect focal retinal function and photoreceptor function in asymmetry with a greater degree of accuracy.

Pupillography for Alzheimer’s Disease / Parkinson Disease

Chang and colleagues (2017) noted that clinical assessment of pupil appearance and PLR may inform us the integrity of the ANS.  Current clinical pupil assessment is limited to qualitative examination, and relies on clinical judgment.  Infra-red (IR) video pupillography combined with image processing software offer the possibility of recording quantitative parameters.  In this study these researchers described an IR video pupillography set-up intended for human and animal testing.  As part of the validation, resting pupil diameter was measured in human subjects using the NeurOptics (Irvine, CA) pupillometer, to compare against that measured by IR video pupillography set-up, and PLR was assessed in guinea pigs.  The set-up consisted of a smart phone with a light-emitting diode (LED) strobe light (0.2 s light-ON, 5 s light-OFF cycles) as the stimulus and an IR camera to record pupil kinetics.  The consensual response was recorded, and the video-recording was processed using a custom MATLAB program.  The parameters assessed were resting pupil diameter (D1), CV, percentage constriction ratio, re-dilation velocity (DV) and percentage re-dilation ratio. We report that the IR video pupillography set-up provided comparable results as the NeurOptics pupillometer in human subjects, and was able to detect larger resting pupil size in juvenile male guinea pigs compared to juvenile female guinea pigs.  At juvenile age, male guinea pigs also had stronger pupil kinetics for both pupil constriction and dilation.  The authors concluded that their IR video pupillography set-up can be applied to clinical research in human, as well as in animal models of Alzheimer’s disease and Parkinson disease that are known to have cholinergic deficits.  They noted that PLR is becoming an increasingly popular tool in neurological and eye research, contributing to the examination of the ANS, and the retina and optic nerve of the eye.  They stated that the experimental set-up described in this study may provide a foundation for further development of a more integrated system, which can be used in research as well as in ophthalmological assessments in the clinical setting.

Quantitative Pupillometry in Isolated Third Nerve Palsy

In a retrospective, observational, case-series study, Kim and colleagues (2018) evaluated pupillary involvement according to various etiologies of acquired isolated third nerve palsy using automated pupillometry, and examined the efficacy of digital pupillometry in discriminating compressive lesions from microvascular ischemic 2rd nerve palsy.  A total of 171 subjects were included in this study, consisting of 60 subjects with presumed microvascular ischemic third nerve palsy, 51 with non-ischemic third nerve palsy, and 60 controls whose pupillary light responses were measured using a dynamic automated pupillometer.  Subjects with non-ischemic third nerve palsy were divided into subgroups according to their etiology; inflammatory and compressive groups including tumor and aneurysm.  Pupillometry parameters including minimum and maximum pupil diameters, constriction latency and ratio, maximum and average constriction velocities and dilation velocity were noted.  The diagnostic ability of pupillometry parameters for discriminating compressive versus microvascular ischemic third nerve palsy was evaluated.  The inter-eye difference of the involved eye and the uninvolved fellow eye was calculated to adjust for individual variability.  Among all parameters, reduced pupillary constriction ratio was the most specific parameter for detecting non-ischemic third nerve palsy, as a large inter-eye difference beyond the normative range of controls was found in 0 % of ischemic, 20 % of inflammatory and 60 % of compressive third nerve palsy.  With the diagnostic criteria using inter-eye differences of minimum pupil diameter of greater than 0.45 mm, or pupillary constriction ratio of less than -7.5 % compared to the fellow eye, the sensitivity and specificity for diagnosing compressive third nerve palsy were 95 % and 88 %, respectively.  In the compressive group, positive correlations were found between the degree of external ophthalmoplegia and constriction ratio (r = 0.615, p < 0.001), average constriction velocity (r = 0.591, p = 0.001) and maximum constriction velocity (r = 0.582, p = 0.001).  The authors concluded that abnormal pupillary constriction ratio was highly specific for detecting compressive third nerve palsy, although the sensitivity was not high.  These researchers stated that digital pupillometry demonstrated relatively good performance for discriminating compressive lesions from microvascular ischemic third nerve palsy.

The authors stated that this study had several drawbacks.  This trial was  retrospective and there was not enough number of patients within the compressive group for a meaningful comparison between different etiologies. These researchers excluded 6 patients with mid-brain stroke, to exclude central lesions that might interrupt pupillary light responses in both eyes.  They stated that further studies with a larger number of subjects are needed to better analyze the pupillometry data among different etiologies of acquired third nerve palsies.  Furthermore, all subjects were Korean, and thus, these findings may not be generalizable to other populations.  Lastly, as a major proportion of compressive and inflammatory cases did not show pupil involvement, the sensitivity of dynamic pupillometry was low for predicting non-microvascular etiologies of third nerve palsy.

Detection of Impaired Cerebral Autoregulation in Critically Ill Persons

Cornejo and colleagues (2020) noted that critically ill patients are at high risk of developing neurological complications.  Among all the potential etiologies, brain hypoperfusion has been advocated as one of the potential mechanisms.  Impairment of cerebral autoregulation (CAR) can result in brain hypoperfusion.  However, assessment of CAR is difficult at bedside.  In a retrospective, observational study, these researchers examined if the automated pupillometer might be able to detect impaired CAR in critically ill patients.  This trial included 92 patients; 52 were septic.  CAR was assessed using the Mxa index, which is the correlation index between continuous recording of cerebral blood flow (CBF) velocities using the transcranial Doppler and invasive arterial blood pressure (BP) over 8 ± 2 mins.  Impaired CAR was defined as an Mxa of greater than 0.3.  Automated pupillometer (Neuroptics, Irvine, CA) was used to evaluate the pupillary light reflex concomitantly to the CAR assessment.  The median Mxa was 0.33 in the whole cohort (0.33 in septic patients and 0.31 in the non-septic patients; p = 0.77).  A total of 51 (55 %) patients showed impaired CAR, 28 (54 %) in the septic group and 23 (58 %) in the non-septic group.  These investigators found a statistically significant although weak correlation between Mxa and the Neurologic Pupil Index (r2 = 0.04; p = 0.048) in the whole cohort as in septic patients (r2 = 0.11; p = 0.026); no correlation was observed in non-septic patients and for other pupillometry-derived variables.  The authors concluded that automated pupillometry could not predict CAR indices such as Mxa in a heterogeneous population of critically ill patients.

Neuromonitoring of Delirium in Sedated Mechanically Ventilated Critically Ill Persons

Farve and colleagues (2020) noted that ICU delirium is a frequent secondary neurological complication in critically ill patients undergoing prolonged mechanical ventilation.  Quantitative pupillometry is an emerging modality for the neuromonitoring of primary acute brain injury, but its potential utility in patients at risk of ICU delirium is unknown.  This was an observational cohort study of medical-surgical ICU patients, without acute or known primary brain injury, who underwent sedation and mechanical ventilation for at least 48 hours.  Starting at day 3, automated IR pupillometry-blinded to ICU caregivers-was used for repeated measurement of the pupillary function, including quantitative pupillary light reflex (q-PLR, expressed as % pupil constriction to a standardized light stimulus) and constriction velocity (CV, mm/s).  The relationship between delirium, using the CAM-ICU score, and quantitative pupillary variables was examined.  A total of 59/100 patients had ICU delirium, diagnosed at a median 8 (5 to 13) days from admission.  Compared to non-delirious patients, subjects with ICU delirium had lower values of q-PLR (25 [19 to 31] versus 20 [15 to 28] %) and CV (2.5 [1.7 to 2.8] versus 1.7 [1.4 to 2.4] mm/s) at day 3, and at all additional time-points tested (p < 0.05).  After adjusting for the Sequential Organ Failure Assessment (SOFA) score and the cumulative dose of analgesia and sedation, lower q-PLR was associated with an increased risk of ICU delirium (odds ratio [OR] 1.057 [1.007 to 1.113] at day 3; p = 0.03).  The authors concluded that sustained abnormalities of quantitative pupillary variables at the early ICU phase correlated with delirium and preceded clinical diagnosis by a median 5 days.  These researchers stated that these findings suggested a potential utility of quantitative pupillometry in sedated mechanically ventilated ICU patients at high risk of delirium.  They stated that these findings are hypotheses-generating; thus, additional larger, ideally multi-center studies are needed to confirm these findings and more precisely examine the value of low q-PLR in predicting ICU delirium, and identify precise prognostic cut-offs in this setting.

The authors stated that this study had several drawbacks.  The study was single-center and employed a convenience sample size, without formal sample size calculation, thereby implying a potential risk of biases.  The cohort was selected to be representative of a high-risk ICU delirium population, undergoing mechanically ventilation for at least 48 hours or more, i.e., a setting where neuromonitoring may be of greatest potential utility.  However, pupillometry was not started early on ICU admission in all patients expected to be on mechanical ventilation for at least 48 hours, but rather was restricted to patients who were actually still mechanically ventilated after 48 hours.  Thus, It remained to be examined if very early pupillometry assessment may provide even earlier evidence for risk of delirium.  The duration of the delirium was not available in all patients, which was an additional drawback.  While neuroimaging was not systematically carried out, these investigators excluded all patients admitted for a primary acute brain injury or with a previous known neurological disease thereby limiting as much as possible intrinsic brain factors that may potentially alter pupillometry assessment.  In addition, pupillometry measurements were carried out by an experienced research ICU physician or nurse, thus guaranteeing data reliability and quality, and the pupillometry data were blinded to clinicians involved in patient care.  These researchers did not adjust for ambient light conditions, which may at least in part affect q-PLR.  However, the pupillometer used in this study (AlgiScan device) has a black rubber that completely covers the eye, thereby ensuring homogeneous dark conditions during pupillary constriction measurements.  The average absolute difference in pupil constriction between delirious and non-delirious patients was relatively low – ranging from 0.2 to 0.3 m – which approached the limits of inter-rater variability for the device.  Furthermore, additional computed variables such as the Neurological Pupil index (NPi) were not available in this study, but warrants further investigation.

Critically Ill Patients

Opic and colleagues (2021) carried out a systematic literature search to identify potential confounders for outcome prediction using pupillary light reflex in adult critically ill patients, as measured by hand-held automated pupillometry devices.  Three digital databases (PubMed, Embase, Cochrane) were systematically searched.  Articles published between 1990 and 2019 in adult patients using monocular automated hand-held devices were considered.  Studies were classified according to the Oxford Centre for Evidence-Based Medicine classification (level 1 represents the highest and level 5 the lowest level of evidence).  Case reports, original research, and systematic reviews were included and cross-referenced.  With the use of 202 search terms, 58 eligible articles reporting the use of hand-held pupillometry in the critically ill could be identified, considering 3,246 patients.  The highest level of evidence came from 10 randomized trials and 19 prospective observational studies.  The level of evidence was mostly II to III and highest with studies regarding the potential confounding effects of pain, the use of opioids, and increased ICP.  Additional potential confounders found were selective serotonin reuptake inhibitors (SSRIs), α2-adregenic receptor agonists, and N-methyl-D-aspartate (NMDA) antagonists.  The authors concluded that the pupillary light reflex was susceptible to factors resulting from underlying co-morbid conditions and effects of treatment regimens.  Scenarios frequently encountered in critical care such as pain, use of opioids, and proof of increased ICP have potential confounding effects on outcome and pupillary reflexes.  When treatment is guided by pupillary metrics, such confounders put patients at risk of over-treatment or under-treatment.  These investigators stated that future research should validate and identify additional confounders, because the findings of this review suggested that even more unexplored confounders may exist.

Detection of Autonomic Dysfunction in Individuals with Multiple Sclerosis

In a cross-sectional study, Bitirgen and colleagues (2021) examined alterations in quantitative dynamic pupil responses to light in relation to neurologic disability and retinal axonal loss in patients with multiple sclerosis (MS).  A total of 25 patients with relapsing-remitting MS (RRMS) and 25 healthy subjects were included in this trial.  Pupillary responses were measured with an IR dynamic pupillometry unit, and peri-papillary RNFL thickness was measured with spectral-domain optical coherence tomography (SD-OCT).  Neurologic disability was evaluated by the Expanded Disability Status Scale (EDSS).  Patients with a history of optic neuritis (ON) within 6 months were excluded.  Only the right eyes were assessed, except in 11 patients with a history of unilateral ON in whom both eyes were further analyzed to examine the effect of previous ON.  The initial pupil diameter (p = 0.003) and pupil contraction amplitude (p = 0.027) were lower in patients with MS compared with healthy controls.  Initial pupil diameter correlated with EDSS score (ρ = -0.458; p = 0.021), and RNFL correlated with contraction latency (ρ = -0.524; p = 0.007).  There were no significant differences in any of the pupil parameters between eyes with and without a history of ON, and between the ON and fellow eyes of the 11 patients with previous unilateral ON.  The authors concluded that dynamic pupillometry revealed significant alterations in pupillary light reflex responses associated with neurologic disability and retinal axonal loss, independent of previous ON.  Moreover, these researchers stated that further studies with a larger sample size are needed to determine the use of quantifying dynamic pupillary responses in patients with MS and to evaluate the potential role of axonal degeneration in the pathophysiology of pupillary abnormalities.  They stated that the main drawbacks of this study were the small sample size (n = 25 for patients with MS) and the cross-sectional study design, which precluded them drawing any conclusions regarding the natural history of alterations in pupillary light responses in MS.

Determination of Autonomic Nerve Activity During Anti-Psychotic Treatment

Koller and colleagues (2020) noted that genetic variants in cytochrome P450 (CYP), dopamine receptor (DRD2, DRD3), serotonin receptor (HTR2A, HTR2C) and ATP-binding cassette subfamily B (ABCB1) genes, among others, were previously associated with the pharmacokinetics and pharmacodynamics of anti-psychotic drugs.  These researchers examined the effects of aripiprazole and olanzapine on pupillary light reflex related to pharmacogenetics.  A total of 24 healthy volunteers receiving 5 oral doses of 10-mg aripiprazole and 5-mg olanzapine tablets were genotyped for 46 polymorphisms by quantitative polymerase chain reaction (qPCR).  Pupil examination was carried out by automated pupillometry.  Aripiprazole, dehydro-aripiprazole and olanzapine plasma concentrations were measured by high-performance liquid chromatography-tandem mass spectrometry.  Aripiprazole affected pupil contraction: it caused dilatation after the administration of the 1st dose, then caused constriction after each dosing.  It induced changes in all pupillometric parameters (p < 0.05).  Olanzapine only altered minimum pupil size (p = 0.046).  Polymorphisms in CYP3A, HTR2A, UGT1A1, DRD2 and ABCB1 affected pupil size, the time of onset of constriction, pupil recovery and constriction velocity.  Aripiprazole, dehydro-aripiprazole and olanzapine pharmacokinetics were significantly affected by polymorphisms in CYP2D6, CYP3A, CYP1A2, ABCB1 and UGT1A1 genes.  The authors concluded that aripiprazole and its main metabolite, dehydro-aripiprazole altered pupil contraction, but olanzapine did not have such an effect.  Many polymorphisms may influence pupillometric parameters and several polymorphisms had an effect on aripiprazole, dehydro-aripiprazole and olanzapine pharmacokinetics.  These researchers stated that pupillography could be a useful tool for the determination of autonomic nerve activity during anti-psychotic treatment.

The authors stated that this study had several drawbacks.  Only 24 subjects were included in the study, which they considered its main drawback; thus, it is important to interpret these findings with caution: studies including more subjects are needed to increase the statistical reliability of the results.  Moreover, this study should be repeated in schizophrenic patients, whose brain structure and genetics may differ from healthy volunteers.  Moreover, neither aripiprazole nor olanzapine reached steady state during 5 days of treatment.  Both could have had a greater effect on autonomic nerve activity if they had reached steady state.  However, the Ethics Committee did not authorize a treatment longer than 5 days with anti-psychotics in healthy volunteers.  Accordingly, these investigators could not use pupillometry to evaluate autonomic disfunction in the clinical practice yet.  Furthermore, the total apparent clearance adjusted for bioavailability (Cl/F) and volume of distribution adjusted for bioavailability (Vd/F) values were calculated without knowing the bioavailability, which could yield questionable results, especially for dehydro‐aripiprazole.

Diagnosis and Evaluation of Treatment Success in Non-Convulsive Status Epilepticus

Godau and colleagues (2021) stated that non-convulsive status epilepticus (NCSE) is a frequent disorder in neurocritical care and its diagnosis can be challenging.  Patients with NCSE often show altered pupil function, but nature and extent may vary; IR pupillometry allows detection of subtle changes of pupil function.  The NPi is considered a surrogate marker of global pupil function that is supposed to be independent of absolute parameters such as the pupil diameter.  In a cross-sectional, observational study, these researchers examined if NPi is altered in NCSE.  A total of 128 consecutive adult emergency patients who had experienced a suspected seizure, have not reached their prior functional level regarding LOC, mental status or focal deficits, had no obvious clinical signs of status epilepticus and had an electroencephalography (EEG) indication as determined by the treating clinician for exclusion of NCSE were examined by routine EEG and pupillometry.  Exclusion criteria were ocular co-morbidity (n = 21) and poor EEG quality (n = 4).  Pupillometry was carried out once directly before the beginning of EEG recording.  NCSE diagnosis (no NCSE, possible NCSE and confirmed NCSE) was established according to Salzburg consensus criteria blinded to pupillometry results.  Group comparison was carried out for right NPi, left NPi, lowest NPi of both sides (minNPi) and the absolute difference of both sides (diffNPi) applying non-parametric testing . In post-hoc analysis, receiver operating characteristics (ROC) of NCSE diagnosis (combined confirmed NCSE and possible NCSE) were carried out for minNPi and diffNPi.  From 103 patients included in the final analysis, 5 (4.9 %) had confirmed NCSE, 7 (6.8 %) had possible NCSE.  Right NPi (p = 0.002), left NPi (p < 0.001) and minNPi (p < 0.001) were significantly lower in "confirmed NCSE" and "possible NCSE" compared to "no NCSE"; diffNPi was significantly higher in "confirmed NCSE" and "possible NCSE" compared to "no NCSE" (p < 0.001).  There was no significant difference of minNPi and diffNPi between "confirmed NCSE" and "possible NCSE".  ROC analysis showed an optimal cut-off of minNPi for NCSE diagnosis of 4.0 (AUC = 0.93, 95 % CI: 0.86 to 0.99).  Optimal ROC analysis cut-off of diffNPi for NCSE diagnosis was 0.2 (AUC = 0.89, 95 % CI: 0.80 to 0.99).  The authors concluded that NPi was significantly reduced and the difference between left and right NPi was significantly higher in confirmed NCSE.  An NPi of less than 4.0 on either side as well as an NPi difference of both sides of greater than 0.2 may be potential indicators of NCSE.  These researchers stated that IR pupillometry may be a helpful diagnostic tool in the evaluation of NCSE and should be further examined in larger populations.

In a prospective, observational study, Godau and associates (2022) examined NPi changes in relation to treatment success. In patents with NCSE.  Serial automated pupillometry was carried out in 68 NCSE episodes.  In accordance with local standards, patients were treated with clonazepam (1 to 2 mg), levetiracetam (40 mg/kg), and lacosamide (5 mg/kg) in a stepwise approach under continuous EEG monitoring until NCSE was terminated.  Patients with refractory NCSE received individualized regimens; NPi was examined bilaterally before and after each treatment step.  For statistical analysis, the minNPi was used.  Non-parametric testing for matched samples and Cohen's d to estimate effect size were performed.  Principal component analysis was used to evaluate the contribution of baseline minNPi, age, sex, and NCSE duration to therapeutic outcome.  In 97.1 % of 68 episodes, NCSE could be terminated; in 16.2 %, NCSE was refractory.  In 85.3 % of episodes, an abnormal baseline minNPi of less than or equal to 4.0 was obtained.  After NCSE termination, minNPi increased significantly (p < 0.001).  Cohen's d showed a strong effect size of 1.24 (95 % CI: 0.88 to 1.61).  Baseline minNPi was higher in clonazepam non-responders versus responders (p = 0.008), minNPi increased in responders (p < 0.001) but not in non-responders.  NCSE refractivity was associated with normal baseline minNPi (principal component analysis, component 1, 32.6 % of variance, r = 0.78), male sex, and longer NCSE duration (component 2, 27.1 % of variance, r = 0.62 and r = 0.78, respectively).  The authors concluded that automated pupillometry may be a helpful non-invasive neuromonitoring tool for the evaluation of patients with NCSE and response to treatment.

Monitoring the Severity of Diabetic Retinopathy

Cankurtaran and colleagues (2021) examined the use of automated quantitative static and dynamic pupillometry in screening patients with type 2 diabetes mellitus (T2DM) and different stages of diabetic retinopathy.  A total of 155 patients with T2DM (DM group) were included in this study and another 145 age- and sex-matched healthy individuals to serve as the control group.  The DM group was divided into 3 subgroups: DM without diabetic retinopathy (no-diabetic retinopathy), non-proliferative diabetic retinopathy, and proliferative diabetic retinopathy.  Static and dynamic pupillometry were carried out by means of a rotating Scheimpflug camera with a topography-based system.  In terms of pupil diameter in both static and dynamic pupillometry (p < 0.05), statistically significant differences were observed between the DM and control groups and also between the subgroups no-diabetic retinopathy, non-proliferative diabetic retinopathy, and proliferative diabetic retinopathy subgroups.  However, it was noted that no-diabetic retinopathy and non-proliferative diabetic retinopathy groups have showed similarities in the findings derived from static pupillometry under mesopic and photopic conditions.  The 2 groups also appeared similar at all time-points during the dynamic pupillometry (p > 0.05).  However, it could be concluded that the proliferative diabetic retinopathy group was significantly different from the rest of the subgroups, no-diabetic retinopathy and non-proliferative diabetic retinopathy groups, in terms of all the static pupillometry measurements (p < 0.05).  The average speed of dilation was also significantly different between the DM and control groups and among the DM subgroups (p < 0.001).  While weak-to-moderate significant correlations were found between all pupil diameters in static and dynamic pupillometry with the duration of DM (p < 0.05 for all), the HbA1c values showed no statistically significant correlations with any of the investigated static and dynamic pupil diameters (p > 0.05 for all).  The authors concluded that the findings of this study revealed that the measurements derived from automated pupillometry were altered in patients with T2DM.  The presence of non-proliferative diabetic retinopathy did not have a negative effect on pupillometry findings, but with proliferative diabetic retinopathy, significant alterations were observed.  These researchers stated that these findings suggested that using automated quantitative pupillometry may be useful in verifying the severity of diabetic retinopathy.

The authors stated that this study had several drawbacks.  Systemic diseases, use of insulin or oral anti-diabetics, and previous ocular treatments may affect pupillary measurements in DM patients, and it was utopian to think completely excluding these factors.  Furthermore, ultrastructure abnormalities in iris specimens, including sphincter and dilatator pupil muscle nerve endings, were observed in DM patients, but these investigators did not study how these might affect pupillometry measurements.  These are topics that should be examined in future research.

Prediction of Post-Operative Opioid-Induced Respiratory Depression

Packiasabapathy and colleagues (2021) noted that safe post-operative pain relief with opioids is an unmet critical medical need in children.  There is a lack of objective, non-invasive bedside tool to evaluate central nervous system (CNS) effects of intra-operative opioids.  Proactive identification of children at risk for post-operative respiratory depression (RD) will aid in tailoring analgesic therapy and significantly improve the safety of opioids in children.  Quantitative pupillometry (QP) is a non-invasive, objective, and real-time tool for monitoring CNS effect-time relationship of opioids.  In a prospective, observational study, these researchers determined the association of QP measures with post-operative RD; and identified the best intra-operative QP measures predictive of post-operative RD in children.  After approval from the institutional review board (IRB) and informed parental consent, in this exploratory study of 220 children undergoing tonsillectomy, QP measures were collected at 5 time-points: awake pre-operative baseline before anesthesia induction (at the time of enrollment [T1]), immediately after anesthesia induction before morphine administration (T2), 3 mins after intra-operative morphine administration (T3), at the end of surgery (T4), and post-operatively when awake in post-anesthesia recovery unit (PACU) (T5).  Intra-operative use of opioid and incidence of post-operative RD were collected.  Analyses were aimed at examining correlations of QP measures with the incidence of RD and, if found significant, to develop a predictive model for post-operative RD.  Peri-operative QP measures of percentage pupil constriction (CONQ, p = 0.027), minimum pupillary diameter (MIN, p = 0.027), and maximum pupillary diameter (MAX, p = 0.034) differed significantly among children with and without post-operative RD.  A predictive model including the minimum pupillary diameter 3 mins after morphine administration (MIN3), minimum pupillary diameter normalized to baseline (MIN31), and percentage pupillary constriction after surgery (T4) standardized to baseline (T1) (CONQ41), along with the weight-based morphine dose performed the best to predict post-operative RD in children (area under the curve [AUC], 0.76).  The authors concluded that a model based on pre- and intra-operative pupillometry measures including CONQ, MIN, along with weight-based morphine dose-predicted post-operative RD in this cohort of children undergoing tonsillectomy.  Moreover, these researchers stated that further investigations with a larger sample size are needed to validate these findings.

Yang et al (2023) stated that elaborative affective processing is observed in depression, and pupillary reactivity, a continuous, sensitive, and reliable indicator of physiological arousal and neurocognitive processing, is increasingly used in studies of depression-related characteristics.  As a 1st attempt to quantitively summarize existing evidence on depression-related pupillary reactivity alterations, this review and meta-analysis evaluated the direction, magnitude, and specificity of pupillary indices of affective processing towards positively, negatively, and neutrally-valenced stimuli among individuals diagnosed with depression or with elevated risk of depression.  Studies on pupillary responses to affective stimuli in the target groups were identified in PsycINFO and PubMed databases.  A total of 22 studies met inclusion criteria for the qualitative review and 16 for the quantitative review; 3-level frequentist and Bayesian models were employed to summarize pooled effects from baseline-controlled stimuli-induced average changes in pupillary responses.  In general, compared to non-depressed individuals, individuals with depression or elevated risk of depression exhibited higher pupillary reactivity (d = 0.15) towards negatively-valenced stimuli during affective processing.  The authors concluded that pupillary motility towards negatively-valenced stimuli may be a promising trait-like marker for depression vulnerability.

Management of Patients Undergoing Surgical Resection of Pituitary Tumors

Lenga et al (2022) stated that pituitary tumors may cause compression of the optic chiasm, resulting in decreased VA; thus, decompression of the optic chiasm is a major objective of surgical treatment in such patients.  Quantitative pupillometry has been used in various clinical settings for evaluating the optic system but has not been used in patients with pituitary tumors.  These researchers examined the potential of this technique to improve treatment modalities in patients undergoing surgical resection of pituitary tumors.  Pupillometry using the automated NPi 200 Pupillometer was carried out in 7 patients who underwent surgical resection of large pituitary tumors at the University of Heidelberg in 2018.  The NPi was evaluated pre-operatively and post-operatively, and correlations with VA and magnetic resonance imaging (MRI) findings regarding optic chiasm compression were determined.  All patients experienced visual disturbance due to a large pituitary tumor.  The NPi was less than 4.0 in all patients in at least 1 pupil.  Intra-operative MRI demonstrated successful decompression of the optic chiasm in all cases.  Post-operatively, the NPi values increased, and this increase was correlated with improved VA.  The authors found that quantitative pupillometry could detect optic chiasm compression in patients with pituitary tumors.  Furthermore, post-operative improvement of NPi values may indicate sufficient decompression of the optic chiasm.  Moreover, these researchers stated that although automated pupillometry may represent a valuable tool in the surgical treatment of pituitary tumors, these findings must be considered preliminary, and further studies are needed before firm conclusions can be drawn. 

The authors stated that this study had several drawbacks.  First, 1 patient exhibited a slight NPi decrease in 1 pupil post-operatively, and this finding was contradictory to the intra-operative imaging findings and improved VA following tumor resection, suggesting other factors may have an impact on the NPi.  Thus, the mass effects of pituitary tumors on the optic system and their impact on pupillometry results should be studied in larger patient cohorts.  Second, since there is a lack of clinical data concerning the minimal clinical difference (MCID) between 2 NPi values, as well as due to the small number of patients (n = 7) included in this technical report, these investigators did not define this important parameter.  Third, standardized pre-operative and post-operative VA assessments are needed in order to confirm the validity of NPi results with regard to improvement of VA.

Prediction of Anisocoria in Patients with Acute Neurologic Injuries

Prescott et al (2022) described the prevalence and associated risk factors of new onset anisocoria (new pupil size difference of at least 1 mm) and its subtypes (new onset anisocoria accompanied by abnormal and normal pupil reactivities) in patients with acute neurologic injuries.  These investigators tested the association of patients who experienced new onset anisocoria subtypes with degree of mid-line shift using linear regression.  They further examined differences between quantitative pupil characteristics associated with 1st-time new onset anisocoria and non-new onset anisocoria at preceding observations using mixed effects logistic regression, adjusting for possible confounders.  All quantitative pupil observations were collected at 2 neuro-ICUs by nursing staff as standard of care (SOC).  These researchers carried out a retrospective, 2-center study of adult patients with intra-cranial pathology in the ICU with at least a 24-hour stay and 3 or more quantitative pupil measurements between 2016 and 2018.  They studied 221 patients (mean age of 58 years, 41 % women); 63 % experienced new onset anisocoria.  New onset anisocoria accompanied by objective evidence of abnormal pupil reactivity occurring at any point during hospitalization was significantly associated with maximum mid-line shift (β = 2.27 per mm; p = 0.01).  The occurrence of new onset anisocoria accompanied by objective evidence of normal pupil reactivity was inversely associated with death (OR, 0.34; 95 % CI: 0.16 to 0.71; p = 0.01) in adjusted analyses.  Sub-clinical continuous pupil size difference distinguished 1st-time new onset anisocoria from non-new onset anisocoria in up to 4 preceding pupil observations (or up to 8 hours prior).  Minimum pupil reactivity between eyes also distinguished new onset anisocoria accompanied by objective evidence of abnormal pupil reactivity from new onset anisocoria accompanied by objective evidence of normal pupil reactivity before 1st-time new onset anisocoria occurrence.  The authors concluded that new onset anisocoria occurred in over 60 % of patients with neurologic emergencies.  Pupil reactivity may be an important distinguishing characteristic of clinically relevant new onset anisocoria phenotypes.  New onset anisocoria accompanied by objective evidence of abnormal pupil reactivity was associated with mid-line shift, and new onset anisocoria accompanied by objective evidence of normal pupil reactivity had an inverse relationship with death.  Distinct quantitative pupil characteristics preceded new onset anisocoria occurrence and may allow for earlier prediction of neurologic decline.  Moreover, these researchers stated that further investigation is needed to examine if quantitative pupillometry sensitively/specifically predicts clinically relevant anisocoria, enabling possible earlier treatments.

Prediction of Clinical Improvement During Lumbar Drain Trials in Individuals with Normal Pressure Hydrocephalus Undergoing Temporary Cerebrospinal Fluid Diversion

Lussier et al (2022) stated that lumbar drain (LD) trials are used to temporarily divert cerebrospinal fluid (CSF) to predict clinical improvement before definitive CSF diversion in patients with a diagnosis of normal pressure hydrocephalus.  New technology has improved clinical detection of subtle pupillary changes that may occur during CSF diversion trials.  In a prospective study, these researchers examined if pupillary light response as recorded by automated pupillometry could be used to predict response during lumbar drain trials.  These investigators gathered quantitative pupillometry data on admission and following each CSF diversion in a cohort of 30 consecutive patients with a presumptive diagnosis of normal pressure hydrocephalus admitted to a university hospital for elective LD trial between January 1, 2020 and March 30, 2021.  The value of pupillometry in predicting success of LD in alleviating symptoms was correlated to clinical improvement during LD.  Of the 29 patients undergoing a 4-day LD trial, 16 (55.2 %) demonstrated clinical improvement.  Pre-drainage pupillometry values did not differ between patients who had clinical improvement or no clinical improvement.  Constriction velocity improved compared to baseline in patients who had a successful LD trial (LD +).  There was a non-significant trend towards improved constriction velocity and improved dilation velocity found in patients even after the 1st aliquot drainage.  The authors concluded that baseline pupillary function by automated pupillometry did not predict clinical improvement during LD trials.  Improvement in constriction and dilation velocity may be useful to monitor at the outset, after the initial drainage, and at completion of LD trials.

Screening for Elevated Intra-Cranial Pressure

Giede-Jeppe et al (2021) stated that although automated pupillometry is increasingly used in critical care settings, predictive value of automatically assessed pupillary parameters during different ICP levels and possible clinical implications are unestablished.  This retrospective, cohort study, at the neurocritical care unit of the University of Erlangen-Nuremberg (2016 to 2018) included 23 non-traumatic supratentorial intra-cerebral hemorrhage (ICH) patients without signs of abnormal pupillary function by manual assessment, i.e., absent light reflex.  These investigators examined ICP levels by an external ventricular drain simultaneously with parameters of pupillary reactivity [i.e., maximum and minimum apertures, light reflex latency (Lat), constriction and re-dilation velocities (CV, DV), and percentage change of apertures (per-change)] using a portable pupillometer (NeurOptics).  Computed tomography (CT) scans were analyzed to determine lesion location, size, intra-ventricular hemorrhage (IVH), hydrocephalus, mid-line shift, and compression or absence of the basal cisterns.  These researchers carried out ROC analysis to examine associations of ICP levels with pupillary parameters and to ascertain best cut-off values for prediction of ICP elevation.  After dichotomization of assessments according to ICP values (normal: less than 20 mmHg, elevated: 20 mmHg or higher), prognostic performance of the determined cut-off parameters of pupillary function versus of CT-imaging findings was analyzed by calculating sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) (logistic regression, corresponding ORs with 95 % CIs).  In 23 patients (11 women, median age of 59.0 (51.0 to 69.0) years), 1,934 assessments were available for analysis.  A total of 74 ICP elevations of 20 mmHg or higher occurred in 7 patients.  Best discriminative thresholds for ICP elevation were as follows: CV of less than 0.8 mm/s (AUC 0.740), per-change of less than 10 % (AUC 0.743), DV of less than 0.2 mm/s (AUC 0.703), and Lat of greater than 0.3 s (AUC 0.616); PPV of all 4 parameters to indicate ICP elevation ranged between 7.2 % and 8.3 % only and was similarly low for CT abnormalities (9.1 %).  These researchers found high NPVs of pupillary parameters (CV: 99.2 %; 95 % CI: 98.3 to 99.6, per-change: 98.7 %; 95 % CI: 97.8 to 99.2, DV: 98.0 %; 95 % CI: 97.0 to 98.7, Lat: 97.0 %; 95 % CI: 96.0 to 97.7), and CT abnormalities (99.7 %; 95 % CI: 99.2 to 99.9), providing evidence that both techniques adequately identified ICH patients without ICP elevation.  The authors concluded that automated pupillometry revealed associations between pupillary reactivity and ICP levels in sedated neurocritical care patients with supratentorial ICH.  The clinical benefit of automated pupillometry appeared rather limited for identifying ICP elevation.  Yet, automated pupillometry reliably determined ICH patients without ICP elevation; thereby, facilitating routine management by saving invasive ICP monitoring or repeated CT controls in those patients.  Moreover, these researchers stated that prospective studies are needed to validate these findings in order to verify whether automated pupillometry harbors the potential for opening up avenues for a time- and cost-effective clinical decision-making in ICH patients.

The authors stated that this study has certain strengths and several limitations.  They were the first time to examine the prognostic performance of automated pupillometry demonstrating a clinical benefit of automated pupillometry as a stand-alone tool for routine management, while all previous studies examined automated pupillometry as additional diagnostic maneuver only.  Moreover, these investigators focused on patients receiving sedatives and catecholamines both of which represent strong confounders of the pupillary reactivity not accounted for in previous studies.  Thus, these findings that automated pupillometry might not reliably identify ICP elevation in neurocritical care patients are of clinical relevance, beyond the subgroup of patients with supratentorial ICH only.  Yet, obvious limitations undermined generalizability of these findings.  Notably, the specific thresholds obtained by automated pupillometry (i.e., CV of less than 0.8, percentage change of aperture of less than 10 %, latency of greater than 0.3, dilation velocity of less than 0.2) may so far be difficult to be used in clinical practice.  Although the output of automated pupillometers comprises exact parameter values with decimal place accuracy, specific thresholds must be validated in prospective trials before they may be generalized for clinical use.  In manual testing, these researchers did not specify between sluggish and normal pupillary reactivity and only patients with absent light reflex were excluded from the study.  Also, pupillometry readings before external ventricular drain (EVD) placement may clarify whether this method harbors the potential to identify patients in need of invasive ICP measurement; thus, further research is needed to implement the technique as a standard operating procedure within the initial treatment at an emergency department.  For a prospective, randomized study design, a delineated protocol with standardized timing of automated pupillometry, simultaneously assessed ICP along with pre-specified cranial CT scanning time-points may rule out residual bias by indication and repeated measures.  Prospectively assessed, time-point standardized pupillary measurements with quantitative serial assessments of pupillary function and standardized follow-up evaluation might contribute to predicting possible pupillary disturbances before ICP elevation.  Despite the large number of pupillary assessments, the sample size of this patient group may have been too small and both groups might have been too dissimilar with respect to the number of assessments to establish new algorithms for detection of patients with increased ICP.  Furthermore, these investigators did not stratify according to different lesion locations (i.e., lobar versus deep), IVH and ICH volumes, respectively, all of which may vary in their susceptibility in altering pupillary function.  Finally, these researchers did not correlate automated pupillometry findings with clinical outcomes after ICH; that is why clinically relevant associations of automated pupillometry reading, other than with ICP, may have been missed.

Pansell et al (2022) noted that elevated ICP is a serious complication in brain injury.  Because of the risks involved, ICP is not monitored in all patients at risk.  Non-invasive screening tools to identify patients with elevated ICP are needed.  Anisocoria, abnormal pupillary size, and abnormal pupillary light reflex are signs of high ICP; however, manual pupillometry is arbitrary and subject to inter-rater variability.  In a retrospective, observational study, these researchers examined the use of quantitative pupillometry as a screening tool for elevated ICP.  They carried out a study of the association between Neurological Pupil index (NPi), measured with the Neuroptics NPi-200 pupillometer, and ICP in patients routinely monitored with invasive ICP measurement in the ICU.  These investigators carried out a non-parametric ROC analysis for ICP 20 mm Hg or higher with NPi as a classification variable.  They conducted a Youden analysis for the optimal NPi cut-off value and recorded sensitivity and specificity for this cut-off value.  These researchers also performed a logistic regression with elevated ICP as the dependent variable and NPi as the independent variable.  This study included 65 patients with invasive ICP monitoring.  A total of 2,705 measurements were analyzed.  Using NPi as a screening tool for elevated ICP yielded an AUC of 0.72.  The optimal mean NPi cut-off value to rule out elevated ICP was 3.9 or higher.  The probability of elevated ICP decreased with increasing NPi, with an OR of 0.55 (0.50 to 0.61).  The authors concluded that screening with NPi may inform high stakes clinical decisions by ruling out elevated ICP with a high degree of certainty.  It may also aid in estimating probabilities of elevated ICP.  This could help to weigh the risks of initiating invasive ICP monitoring against the risks of not doing so.  Because of its ease of use and excellent inter-rater reliability, these researchers suggested further studies of NPi as a screening tool for elevated ICP.

The authors stated that although this study was relatively large compared with previous studies, the sample size of only 65 patients must be regarded as a limitation.  The predictive probabilities of elevated ICP as a function of NPi as well as PPV and NPV are dependent on their base rate of 7 % elevated ICP.  A low PPV and a high NPV are to be expected with the pre-test probability of 7 % but will be different in a population with a different proportion of patients with elevated ICP.  The relatively small proportion of elevated ICP and of low NPi were reflected in the wide CIs for predictive probabilities with lower NPi values.  The predictive probabilities and PPV and NPV at the suggested cut-off should be interpreted with caution.  They need to be validated in a different, preferably larger, cohort to draw conclusions on the generalizability of these findings.  Another limitation of this trial was the assumption that recorded ICP equals the true ICP.  Measurement errors may occur for a number of reasons that these investigators were unable to detect because of the retrospective nature of this study.  Likewise, the 12 entries with NPi off the scale showed that data entry errors occurred in this dataset.  Because these were retrospective data, these researchers had no way to examine the extent of data entry errors consisting of erroneous NPi values that were within the NPi scale.  This was another limitation.

Chromatic Pupillography for Detection of Glaucoma

In a cross-sectional study, Rukmini and associates (2015) examined if a chromatic pupillometry test can be used to detect impaired function of intrinsically photosensitive retinal ganglion cells (ipRGCs) in patients with primary open-angle glaucoma (POAG) and determined if pupillary responses correlate with optic nerve damage and visual loss. A total of 161 healthy controls recruited from a community polyclinic (55 men; 151 ethnic Chinese) and 40 POAG patients recruited from a glaucoma clinic (22 men; 35 ethnic Chinese) 50 years of age or older were included in this study.  Subjects underwent monocular exposure to narrowband blue light (469 nm) or red light (631 nm) using a modified Ganzfeld dome.  Each light stimulus was increased gradually over 2 minutes to activate sequentially the rods, cones, and ipRGCs that mediate the pupillary light reflex.  Pupil diameter was recorded using an infrared pupillography system.  Pupillary responses to blue light and red light were compared between control subjects and those with POAG by constructing dose-response curves across a wide range of corneal irradiances (7 to 14 log photons/cm(2)/second).  In patients with POAG, pupillary responses were evaluated relative to standard automated perimetry testing (Humphrey Visual Field [HVF]) and scanning laser ophthalmoscopy parameters (Heidelberg Retinal Tomography [HRT]).  The pupillary light reflex was reduced in patients with POAG only at higher irradiance levels, corresponding to the range of activation of ipRGCs.  Pupillary responses to high-irradiance blue light associated more strongly with disease severity compared with responses to red light, with a significant linear correlation observed between pupil diameter and HVF mean deviation (r = -0.44; p = 0.005) as well as HRT linear cup-to-disc ratio (r = 0.61; p < 0.001) and several other optic nerve head parameters.  The authors concluded that in glaucomatous eyes, reduced pupillary responses to high-irradiance blue light were associated with greater visual field loss and optic disc cupping.  They stated that in POAG, a short chromatic pupillometry test that evaluated the function of ipRGCs can be used to estimate the degree of damage to retinal ganglion cells that mediate image-forming vision; this approach could prove useful in detecting glaucoma.  These findings need to be validated in well-designed studies.

Furthermore, UpToDate reviews on "Overview of glaucoma in infants and children" (Olitsky and Reynolds, 2016) and "Open-angle glaucoma: Epidemiology, clinical presentation, and diagnosis" (Jacobs, 2016) do not mention pupillography as a diagnostic tool.

In a cross-sectional study, Najjar and colleagues (2018) assessed the ability of chromatic pupillometry to reveal abnormal pupillary responses to light in patients with early-stage POAG and to examined if the degree of pupillometric impairment correlated with structural hallmarks of optic nerve damage in the disease.  A total of 46 patients with early-stage POAG (63.4 ± 8.3 years, 63 % men, 87 % ethnic-Chinese) and 90 age-matched healthy controls (61.4 ± 8.6 years, 34 % men, 89 % ethnic-Chinese).  Patients with POAG had a visual field mean deviation (VFMD) of -6 decibels or better on automated perimetry.  Each subject underwent a monocular 2-min exposure to blue light (462 nm) followed by another 2-min exposure to red light (638 nm) using a modified Ganzfeld dome equipped with a light-emitting diode lighting system.  The light stimuli intensity was increased logarithmically to evaluate the combined extrinsic and intrinsic response of intrinsically photosensitive retinal ganglion cells (ipRGCs).  Light-induced changes in horizontal pupil diameter were assessed monocularly using IR pupillography.  Baseline-adjusted, light-induced pupillary constriction amplitudes were calculated, and individual irradiance-response curves were constructed for each stimulus.  Pupillary constriction amplitudes were compared between groups and across light intensities using a linear mixed model analysis.  The linear relationship between pupillometric parameters and different structural and functional features of glaucoma was assessed using Pearson's correlation analysis.  Light-induced pupillary constriction was reduced in patients with early-stage POAG compared with controls at moderate to high irradiances (greater than or equal to 11 Log photons/cm2/s) of blue (p = 0.003) and red (p < 0.001) light.  Maximal pupillary constriction amplitude was correlated with retinal nerve fiber layer thickness (RNFL) thickness (blue: r = 0.51, p < 0.001; red: r = 0.45, p = 0.002) in patients with POAG but not in controls.  Conversely, pupillometric parameters were not correlated with visual field scores in patients with early-stage POAG.  The authors concluded that this study showed that early-stage POAG was associated with altered pupillary responses to ramping-up full-field light stimulations.  These wavelength-independent deficits in pupillary constriction to high irradiances of light correlated with subtle changes in RNFL thickness and were indicative of ipRGC dysfunction or loss early in the disease.  These findings also added to the body of evidence supporting chromatic pupillometry as an objective, functional, and fast method that does not require clinical expertise to evaluate retinal integrity in ophthalmic diseases such as glaucoma.  Moreover, these researchers stated that although these pupillometric findings showed promise for detecting POAG, further improvements are needed to render this approach more viable in a clinical setting.  They noted that with modern technologic advancements, pupillometry-based methods could potentially be refined and adapted into reliable population-based ocular screening tools for early POAG detection.

The authors stated that this study had several drawbacks.  First, because subjects were only briefly (approximately 2 mins) dark-adapted before blue light exposure, these researchers assumed that rhodopsin was not fully regenerated to optimally capture light and rods’ contribution to the pupillary responses to light may have been sub-optimal.  Thus, they could not exclude that a reduction in pupil constriction to dimmer irradiances of blue light or an increased threshold of constriction to this wavelength of light could be observed in patients with POAG after being fully dark adapted.  A dark adaptation of 30 to 45 mins is usually needed to fully regenerate rhodopsin.  Such a procedure is cumbersome in a clinical setting, but could be replaced by a partial dark adaptation period of at least 5 mins (approximately 50 % of regenerated rhodopsin).  Second, these investigators acknowledged that their paradigm may not allow them to fully disentangle the disease-dependent pupil responses from direct pupillometric changes resulting from the lower retinal illumination induced by the gradual pupil constriction.  In fact, these researchers likely under-estimated the pupillary response to both blue and red lights, especially in healthy controls, because subjects’ pupils were not dilated pharmacologically.  Nevertheless, given the potential effect of anti-muscarinics on the physiologic properties of retinal ganglion cells,  they believed that the use of such agents would generate greater uncertainty when testing retinal integrity.  Conversely, adopting a Maxwellian view optical system may improve the control of retinal light exposure during the ramping-up light regimen and across age groups.  Third, PIPR metrics (slope of re-dilation, amplitudes) were unconventional in this study.  This could be due to the duration and pattern of the light exposure paradigm, in addition to the gradual constriction of the pupil and the reduction in the amount of light reaching the retina.  Conventionally, optimal PIPR was induced by short bright stimulations  to a dilated pupil and was reduced under blue background, or subsequently to blue light exposure.  The dynamics of the light stimulation used in this study did not necessarily allow for a direct and isolated assessment of the melanopsin-based response and may have led to gradual light adaptation and to less discernible PIPRs under blue light.  Although PIPR is a proxy to assess the integrity of the melanopsin-signaling pathway, melanopsin is not exclusively affected in glaucoma but rather the ipRGCs expressing the photopigment.  In this study, the authors showed that the amplitudes of pupil constriction during a nonmydriatic full-field light stimulation delivered in a logarithmic ramping-up fashion can be used to detect ipRGC dysfunction in early-stage POAG.  Further experiments in melanopsin knock-out animal models are needed to discern the melanopsin-dependent pupillometric component in the ramping-up paradigm.  Finally, given that the pool of subjects included mainly ethnic Chinese individuals, it would also be important to examine if these findings are generalizable to other ethnic groups.

In summary, there is currently insufficient evidence to support the use of chromatic pupillometry/quantitative pupillometry/pupillography for any clinical application.

Chromatic Pupillography for Hemianopia

Maeda and colleagues (2017) noted that the pupil light reflex is considered to be a simple subcortical reflex.  However, many studies have proven that patients with isolated occipital lesions with homonymous hemianopia show pupillary hemi-hypokinesia.  These researchers hypothesized that the afferent pupillary system consists of 2 pathways:
  1. one via intrinsically photosensitive retinal ganglion cells (ipRGCs),
  2. the other running through the normal RGCs via the visual cortex.
The purpose of this study was to test the hypothesis of these 2 separate pupilometer pathways.  A total of 12 patients (59.1 ± 18.8 years) with homonymous hemianopia due to post-geniculate lesions of the visual pathway and 20 normal controls (58.6 ± 12.9 years) were examined using chromatic pupillography: stimulus intensity was 28 lx corneal illumination, stimulus duration was 4.0 s, and the stimulus wavelengths were 420 ± 20 nm (blue) and 605 ± 20 nm (red), respectively.  The examined parameters were baseline pupil diameter, latency, and relative amplitudes (absolute amplitudes compared to baseline), measured at maximal constriction, at 3 s after stimulus onset, at stimulus offset, and at 3 s and 7 s after stimulus offset.  The relative amplitudes for the red stimulus were significantly smaller for hemianopia patients compared to the normal controls [maximal constriction: 35.6 ± 5.9 % (hemianopia) to 42.3 ± 5.7 % (normal); p = 0.004; 3 s after stimulus onset: p = 0.004; stimulus offset: p = 0.001].  No significant differences in any parameter were found between the 2 groups using the blue stimulus.  The authors concluded that these findings supported the hypothesis that the ipRGC pathway is mainly subcortical, whereas a second, non-ipRGC pathway via the occipital cortex exists.

Chromatic Pupillography for Optic Nerve Diseases and Retinitis Pigmentosa

In a cross-sectional study, Chibel and colleagues (2016) evaluated VF defects as well as retinal function in healthy subjects and patients with retinitis pigmentosa (RP) using a chromatic multi-focal pupillometer.  The right eyes of 16 healthy participants and 13 RP patients were studied.  Pupil responses to red and blue light (peak, 485 and 625 nm, respectively) presented by 76 LEDs, 1.8-mm spot size at different locations of a 16.2° VF were recorded.  Subjective VFs of RP patients were determined using chromatic dark-adapted Goldmann VFs (CDA-GVFs); 6 healthy participants underwent 2 pupillometer examinations to determine test-retest reliability.  Three parameters of pupil contraction were determined automatically:
  1. percentage of change of pupil size (PPC),
  2. maximum contraction velocity (MCV; in pixels per second), and
  3.  latency of MCV (LMCV; in seconds).
The fraction of functional VF was determined by CDA-GVF.  In healthy participants, higher PPC and MCV were measured in response to blue compared with red light.  The LMCV in response to blue light was relatively constant throughout the VF.  Healthy participants demonstrated higher PPC and MCV and shorter LMCV in central compared with peripheral test points in response to red light.  Test-retest correlation coefficients were 0.7 for PPC and 0.5 for MCV.  In RP patients, test point in which the PPC and MCV were lower than 4 standard errors from the mean of healthy participants correlated with areas that were indicated as non-seeing by CDA-GVF.  The mean absolute deviation in LMCV parameter in response to the red light between different test point was significantly higher in RP patients (range of 0.16 to 0.47) than in healthy participants (range of 0.02 to 0.16; p < 0.0001) and indicated its usefulness as a diagnostic tool with high sensitivity and specificity (AUC, 0.97, Mann-Whitney-Wilcoxon analysis).  Randomly reducing the number of test points to a total of 15 points did not significantly reduce the AUC in RP diagnosis based on this parameter.  The authors concluded that this study demonstrated the feasibility of using a chromatic multi-focal pupillometer for objective diagnosis of RP and assessment of VF defects.  These preliminary findings need to be validated by well-designed studies.

In a prospective study, Richter and colleagues (2017) compared the chromatic PLR in healthy subjects with those from patients with diseases of the outer or inner retina under various stimulus conditions, and determined the parameters needed to optimally distinguish between disease and control groups.  A total of 15 patients with RP, 19 patients with optic nerve disease (ON), and 16 healthy subjects were enrolled in this study; ON included optic neuritis (NNO) and non-arteritic anterior ischemic optic neuropathy (NAION).  For each subject, the PLR was recorded, to red, yellow, green, and blue stimuli for durations of 4 and 12 s, and for stimulus intensities of 4 lx and 28 lx.  Comparison between control and RP or ON patient results showed that responses after stimulus onset were significantly different for most stimulus conditions, but the post-stimulus amplitudes at 3 s and 7 s after light extinction were not.  On the other hand, the difference between the ON and RP groups was significant only for post-stimuli time-points and only for blue stimuli.  Differences between responses to blue and red were significantly different, predominantly at post stimulus time-points.  A ROC analysis revealed that the maximal constriction amplitudes to a 4 lx, 4 s yellow stimulus were significantly different in ON versus RP patients, and the responses to a 4 s, 28 lx blue stimulus at 7 s post-stimulus were significantly different in controls versus ON versus RP patients with a high specificity.  The authors concluded that pupillary light responses to blue light in healthy, RP, and ON subjects were significantly different from one another; the optimal stimuli for future protocols was found to be a 4 s blue stimulus at 28 lx, and a 4 s yellow stimulus at 4 lx.  These preliminary findings need to be validated by well-designed studies.

Kelbsch and associates (2017) analyzed pupil responses to specific chromatic stimuli in patients with advanced RP to examine if chromatic pupillography can be used as an objective marker for residual retinal function.  These investigators examined correlations between parameters of the pupil response and the perception threshold of electrically evoked phosphenes.  Chromatic pupillography was performed in 40 patients with advanced RP (VA less than 0.02 or VF less than or equal to 5°, non-recordable ERGs) and 40 age-matched healthy subjects.  Pupil responses to full-field red (605 nm) and blue (420 nm) stimuli of 28 lx corneal illumination were recorded and analyzed for 2 stimulus durations (1 and 4 seconds).  The perception threshold of phosphenes to trans-corneal electrostimulation was ascertained and correlated to the pupil responses and VA.  Patients with RP showed significantly reduced pupil responses to red and blue stimuli compared with the controls.  With red stimuli, pupillary escape could be observed; blue stimuli resulted in a well-preserved post-illumination pupil response.  Phosphene thresholds were significantly increased in patients with RP and correlated with the parameters of the pupil response if all subjects were considered.  Within the RP group alone, this relationship was less pronounced and statistically not significant.  The authors concluded that chromatic pupillography demonstrated a significant decrease in outer retinal photoreceptor responses but a persisting and disinhibited intrinsic photosensitive RGC function in advanced RP.  The authors concluded that these phenomena may be useful as an objective marker for the effectiveness of any interventional treatment for hereditary retinal diseases as well as for the selection of suitable patients for an electronic retinal implant.

Furthermore, UpToDate reviews on "Retinitis pigmentosa: Clinical presentation and diagnosis" (Givre and Garg, 2017) and "Nonarteritic anterior ischemic optic neuropathy: Clinical features and diagnosis" (Tamhankar and Volpe, 2017) do not mention pupillometry/pupillography as a diagnostic tool.

Chromatic Pupillography for Detection of Leber Congenital Amaurosis and Monitoring of Progression of Retinal and Optic Nerve Diseases or Recovery After Treatment

Rukmini and associates (2019) stated that the pupillary light reflex is mediated by melanopsin-containing intrinsically-photosensitive retinal ganglion cells (ipRGCs), which also receive input from rods and cones.  Melanopsin-dependent pupillary light responses are short-wavelength sensitive, have a higher threshold of activation, and are much slower to activate and de-activate compared with rod/cone-mediated responses.  Given that rod/cone photoreceptors and melanopsin differ in their response properties, light stimuli can be designed to stimulate preferentially each of the different photoreceptor types, providing a read-out of their function.  This has given rise to chromatic pupillometry methods that aim to examine the health of outer retinal photoreceptors and ipRGCs by measuring pupillary responses to blue or red light stimuli.  These investigators reviewed different types of chromatic pupillometry protocols that have been tested in patients with retinal or optic nerve disease, including approaches that use short-duration light exposures or continuous exposure to light.  Across different protocols, patients with outer retinal disease (e.g., retinitis pigmentosa or Leber congenital amaurosis) showed reduced or absent pupillary responses to dim blue-light stimuli used to examine rod function, and reduced responses to moderately-bright red-light stimuli used to evaluate cone function.  By comparison, patients with optic nerve disease (e.g., glaucoma or ischemic optic neuropathy, but not mitochondrial disease) showed impaired pupillary responses during continuous exposure to bright blue-light stimuli, and a reduced post-illumination pupillary response after light offset, used to examine melanopsin function.  These proof-of-concept studies showed that chromatic pupillometry methods can be used to evaluate damage to rod/cone photoreceptors and ipRGCs.  In future studies, it will be important to examine if chromatic pupillometry methods could be used for screening and early detection of retinal and optic nerve diseases.  Such methods may also prove useful for objectively assessing the degree of recovery to ipRGC function in blind patients who undergo gene therapy or other treatments to restore vision.  These researchers stated that investigators are now in the position to exploit these research findings to examine prospectively the ability of chromatic pupillometry to detect abnormalities in ipRGC function.  Future large-scale studies should focus on optimizing, standardizing, and adapting chromatic pupillometry protocols for early detection of retinal and optic nerve diseases, and for monitoring disease progression or recovery after treatment.

Suo and colleagues (2020) noted that computerized pupillary light reflex assessment devices (CPLRADs) may serve as an effective screening tool for glaucomatous optic neuropathy, since they can dynamically detect abnormal pupillary responses from a novel sequence of light stimuli and functionally-shaped stimuli.  These researchers systematically examined the current state of advanced CPLRADs and accuracy of application in detecting glaucoma.  They carried out an electronic literature search of PubMed, Medline, and Embase from data-base inception to December 2019.  Studies that reported data on the use of computer-aided pupillometry with monocular and/or binocular monitoring in glaucoma patients were included.  Two review authors independently conducted the study selection and extracted study data.  A total of 25 studies were included in this review; 8 with a total of 829 subjects were included in this meta-analysis.  Data were pooled using a random-effect model, since the significant heterogeneity (p < 0.1, I2 > 50 %).  The meta-analysis of 8 studies showed reasonably high summary sensitivity and specificity estimates of 0.81 (95 % CI: 0.73 to 0.89) and 0.83 (95 % CI: 0.75 to 0.91), respectively.  Simpler monochromatic devices, such as PupilmetrixTM PLR60, generally performed as well as or slightly better than more complex chromatic devices.  The authors concluded that this review suggested that CPLRADs may facilitate direct clinical decision-making for glaucoma diagnosis and evaluation, and may provide a deeper understanding of the pathomechanism of glaucoma.  These researchers stated that these findings revealed that the diagnostic abilities of even the best CPLRD parameters were only moderate in glaucoma.  The diagnostic abilities of the CPLRAD measurements were significantly influenced by the inter-eye asymmetry and within-eye asymmetry in case of glaucomatous damage.  They stated that further research on the mechanism of intrinsically photosensitive retinal ganglion cells (ipRGCs) in glaucoma should be deeply examined by chromatic pupillography to investigate other factors, such as sleep qualities in glaucoma patients.

The authors stated that this study had several drawbacks.  First, the search strategy was limited to only those articles written in English.  Second, none of the 25 studies, considered how to control the cognitive load and emotional factors that possibly altered both pupil size.  Third, in some of the studies, the glaucomatous subjects were notably older than the control subjects.  Fourth, some of the participants had systemic conditions, such as diabetes and hypertension and were on medications for these conditions.  Moreover, many glaucoma patients were on glaucoma medications with unknown effects on the pupil light reflex (PLR).  Furthermore, some other factors may have affected PLR, further limiting the accuracy of the CPLRADs, including the presence of an abnormal pupil shape, previous ocular surgery or medications (topical and systemic).  Fifth, these researchers did not examine other computer-aided PLR methods, such as pupil perimetry in glaucoma patients.

Evaluation of Hypersomnolence

Dworetz et al (2023) provided a brief overview of current objective measures of hypersomnolence, discussed proposed measure modifications, and reviewed emerging measures.  These investigators stated that there is potential to optimize current tools using novel metrics.  High-density and quantitative EEG-based measures may provide discriminative informative.  Cognitive testing may quantify cognitive dysfunction common to hypersomnia disorders, especially in attention, and objectively measure pathologic sleep inertia.  Structural and functional neuroimaging studies in narcolepsy type 1 have demonstrated considerable variability but so far implicate both hypothalamic and extra-hypothalamic regions; fewer studies of other central disorders of hypersomnolence (CDH) have been carried out.  There is recent renewed interest in pupillometry as a measure of alertness in the evaluation of hypersomnolence.  The authors concluded that no single test captures the full spectrum of disorders and use of multiple measures will likely improve diagnostic precision.  They stated that research is needed to identify novel measures and disease-specific biomarkers, and to define combinations of measures optimal for CDH diagnosis.

Indicator of Mid-Brain Compression Due to Supratentorial Ischemic Stroke or Primary Intra-Parenchymal Hemorrhage

Kim et al (2022) stated that asymmetric pupil reactivity or size can be early clinical indicators of mid-brain compression due to supratentorial ischemic stroke or primary intra-parenchymal hemorrhage (IPH).  Radiographic mid-line shift is associated with worse functional outcomes and life-saving interventions.  Better understanding of quantitative pupil characteristics would be a non-invasive, safe, and cost-effective way to improve identification of life-threatening mass effect and resource utilization of emergent radiographic imaging.  In a retrospective, multi-center, pilot study, these researchers characterized the association between mid-line shift at various anatomic levels and quantitative pupil characteristics.  They examined brain CT images within 75 mins of a quantitative pupil observation from patients admitted to Neuro-ICUs between 2016 and 2020 with large (greater than 1/3 of the middle cerebral artery territory) acute supratentorial ischemic stroke or primary IPH of greater than 30 mm3.  For each image, these investigators measured mid-line shift at the septum pellucidum (MLS-SP), pineal gland shift (PGS), the ratio of the ipsilateral to contralateral mid-brain width (IMW/CMW), and other exploratory markers of radiographic shift/compression.  Pupil reactivity was measured using an automated infrared pupillometer (NeurOptics, Inc.), specifically the proprietary algorithm for NPi.  These researchers used rank-normalization and linear mixed-effects models, stratified by diagnosis and hemorrhagic conversion, to test associations of radiographic markers of shift and asymmetric pupil reactivity (Diff NPi), adjusting for age, lesion volume, GCS, and osmotic medications.  Of 53 patients with 74 CT images, 26 (49.1 %) were women, and median age was 67 years.  MLS-SP and PGS were greater in patients with IPH, compared to patients with ischemic stroke (6.2 versus 4.0 mm, 5.6 versus 3.4 mm, respectively).  These investigators found no significant associations between pupil reactivity and the radiographic markers of shift when adjusting for confounders.  However, they observed potentially relevant relationships between MLS-SP and Diff NPi in the IPH cohort (β = 0.11, SE 0.04, p = 0.01), and PGS and Diff NPi in the ischemic stroke cohort (β = 0.16, SE 0.09, p = 0.07).  The authors found the relationship between mid-line shift and asymmetric pupil reactivity may differ between IPH and ischemic stroke.  These researchers stated that the findings of this study may serve as necessary preliminary data to guide further prospective investigation into how clinical manifestations of radiographic mid-line shift differ by diagnosis and proximity to the mid-brain.

The authors stated that his study had several drawbacks.  First, the sample size is small (n = 53 patients), limiting how definitively these researchers could evaluate potentially significant associations.  Second, in the measurement of the radiographic markers of interest, differences in imaging angle could impact how data was collected within 1 axial plane.  Third, these researchers did not have a baseline scan on each patient to use as a comparison.  They tried to mitigate these limitations by a comprehensive protocol for normalization and measurement and included patients who had multiple scans that met criteria adjusting for correlation using linear mixed effects regression.  However, though inter-rater reliability of MLS-SP and PGS was good-to-excellent, these investigators acknowledged that inter-rater reliability, especially of IMW/CMW, may have limited the ability to accurately observe some relationships.  These researchers performed multiple tests of association, increasing the potential for false positive findings.  The authors tried to allay the limitation by selecting 3 primary hypotheses and an appropriate statistical correction.  The remainder of the analyses were hypothesis-generating for more definitive studies.  The authors noted that given the transformations that were needed to normalize these data, they cautioned any interpretations concerning effect size.  Because this trial was observational and retrospective, these researchers could not exclude residual confounding or establish causal relations.  They did not have information on cognitive load, pain, or ambient light levels, which have been reported to affect pupil characteristics.  These investigators were unable to adjust for all potential residual confounders including potential pupil influencing medications, which could affect pupil size and reactivity.

Marker for Depression

Yang et al (2023) noted that elaborative affective processing is observed in depression, and pupillary reactivity, a continuous, sensitive, and reliable indicator of physiological arousal and neurocognitive processing, is increasingly used in studies of depression-related characteristics.  In a systematic review and meta-analysis, these investigators summarized available evidence on depression-related pupillary reactivity alterations; they examined the direction, magnitude, and specificity of pupillary indices of affective processing towards positively, negatively, and neutrally-valenced stimuli among individuals diagnosed with depression or with elevated risk of depression.  Studies on pupillary responses to affective stimuli in the target groups were identified in PsycINFO and PubMed databases.  A total of 22 studies met inclusion criteria for the qualitative review and 16 for the quantitative review; 3-level frequentist and Bayesian models were employed to summarize pooled effects from baseline-controlled stimuli-induced average changes in pupillary responses.  In general, compared to non-depressed individuals, individuals with depression or elevated risk of depression exhibited higher pupillary reactivity (d = 0.15) towards negatively-valenced stimuli during affective processing.  The authors concluded that pupillary motility towards negatively-valenced stimuli may be a promising trait-like marker for depression vulnerability.


The above policy is based on the following references:

  1. Bertinotti L, Pietrini U, Del Rosso A, et al. The use of pupillometry in joint and connective tissue diseases. Ann N Y Acad Sci. 2002;966:446-455.
  2. Bitirgen G, Akpinar Z, Turk HB, Malik RA. Abnormal dynamic pupillometry relates to neurologic disability and retinal axonal loss in patients with multiple sclerosis. Transl Vis Sci Technol. 2021;10(4):30.
  3. Cankurtaran V, Ilhan C, Tekin K, et al. Use of automated quantitative pupillometric evaluation for monitoring the severity of diabetic retinopathy. Arq Bras Oftalmol. 2021;84(1):37-44.
  4. Chang DS, Arora K, Boland MV, Friedman DS. The relationship between quantitative pupillometry and estimated ganglion cell counts in patients with glaucoma. J Glaucoma. 2019;28(3):238-242.
  5. Chang DS, Arora KS, Boland MV, et al. Development and validation of an associative model for the detection of glaucoma using pupillography. Am J Ophthalmol. 2013;156(6):1285-1296.e2.
  6. Chang LY, Turuwhenua J, Qu TY, et al. Infrared video pupillography coupled with smart phone LED for measurement of pupillary light reflex. Front Integr Neurosci. 2017;11:6.
  7. Chen Y, Wyatt HJ, Swanson WH.  Pupillary evaluation of retinal asymmetry: Development and initial testing of a technique. Vision Res. 2005;45(19):2549-2563.
  8. Chibel R, Sher I, Ben Ner D, et al. Chromatic multifocal pupillometer for objective perimetry and diagnosis of patients with retinitis pigmentosa. Ophthalmology. 2016;123(9):1898-1911.
  9. Connelly MA, Brown JT, Kearns GL, et al. Pupillometry: A non-invasive technique for pain assessment in paediatric patients. Arch Dis Child. 2014;99(12):1125-1131
  10. Cornejo AQ, Vilarinho CSF, Crippa IA, et al. The use of automated pupillometry to assess cerebral autoregulation: A retrospective study. J Intensive Care. 2020;8:57.
  11. Dworetz A, Trotti LM, Sharma S. Novel objective measures of hypersomnolence. Curr Sleep Med Rep. 2023;9(1):45-55.
  12. Favre E, Bernini A, Morelli P, et al. Neuromonitoring of delirium with quantitative pupillometry in sedated mechanically ventilated critically ill patients. Crit Care 2020;24(1):66.
  13. Fountas KN, Kapsalaki EZ, Machinis TG, et al. Clinical implications of quantitative infrared pupillometry in neurosurgical patients. Neurocritical Care. 2006;5(1): 55-60.
  14. Freedman N. Quantifying sleepiness. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed November 2013.
  15. Giede-Jeppe A, Sprugel MI, Huttner HB, et al. Automated pupillometry identifies absence of intracranial pressure elevation in intracerebral hemorrhage patients. Neurocrit Care. 2021;35(1):210-220.
  16. Givre S, Garg S. Retinitis pigmentosa: Clinical presentation and diagnosis. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed August 2017.
  17. Godau J, Bharad K, Rosche J, et al. Automated pupillometry for assessment of treatment success in nonconvulsive status epilepticus. Neurocrit Care. 2022;36(1):148-156. 
  18. Godau J, Bierwirth C, Rosche J, Bosel J. Quantitative infrared pupillometry in nonconvulsive status epilepticus. Neurocrit Care. 2021;35(1):113-120.
  19. Heimburger D, Durand M, Gaide-Chevronnay L, et al. Quantitative pupillometry and transcranial Doppler measurements in patients treated with hypothermia after cardiac arrest. Resuscitation. 2016;103:88-93.
  20. Hughes D. Gaucher disease: Initial assessment, monitoring, and clinical course. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed August 2015b
  21. Hughes D. Gaucher disease: Pathogenesis, clinical manifestations, and diagnosis. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed August 2015a
  22. Jacobs DS. Open-angle glaucoma: Epidemiology, clinical presentation, and diagnosis. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed August 2016.
  23. Jahns FP, Miroz JP, Messerer M, et al. Quantitative pupillometry for the monitoring of intracranial hypertension in patients with severe traumatic brain injury. Crit Care. 2019;23(1):155.
  24. Johnson DC. Disorders of ventilatory control. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed November 2013.
  25. Kelbsch C, Maeda F, Lisowska J, et al. Analysis of retinal function using chromatic pupillography in retinitis pigmentosa and the relationship to electrically evoked phosphene thresholds. Acta Ophthalmol. 2017;95(4):e261-e269.
  26. Kim HM, Yang HK, Hwang JM. Quantitative analysis of pupillometry in isolated third nerve palsy. PLoS One. 2018;13(11):e0208259.
  27. Kim ISY, Balogun OO, Prescott BR, et al. Quantitative pupillometry and radiographic markers of intracranial midline shift: A pilot study. Front Neurol. 2022;13:1046548.
  28. Kim J-G, Shin H, Lim T-H, et al. Efficacy of quantitative pupillary light reflex for predicting neurological outcomes in patients treated with targeted temperature management after cardiac arrest: A systematic review and meta-analysis. Medicina (Kaunas). 2022;58(6):804.
  29. Kjesbu SS, Moksnes K, Klepstad P, et al. Application of pupillometry and pupillary reactions in medical research. Tidsskr Nor Laegeforen. 2005;125(1):29-32.
  30. Koller D, Saiz-Rodríguez M, Zubiaur P, et al. The effects of aripiprazole and olanzapine on pupillary light reflex and its relationship with pharmacogenetics in a randomized multiple-dose trial. Br J Clin Pharmacol. 2020;86(10):2051-2062.
  31. Lenga P, Jakobs M, Jesser J, et al. The use of quantitative pupillometry in patients with pituitary tumors: A technical note. Acta Neurochir (Wien). 2022;164(6):1599-1604.
  32. Lussier BL, Erapuram M, White JA, et al. Predictive value of quantitative pupillometry in patients with normal pressure hydrocephalus undergoing temporary CSF diversion. Neurol Sci. 2022;43(9):5377-5382.
  33. Maeda F, Kelbsch C, Straßer T, et al. Chromatic pupillography in hemianopia patients with homonymous visual field defects. Graefes Arch Clin Exp Ophthalmol. 2017;255(9):1837-1842.
  34. Martinez-Ricarte F, Castro A, Poca MA, et al. Infrared pupillometry. Basic principles and their application in the non-invasive monitoring of neurocritical patients. Neurologia. 2013;28(1):41-51.
  35. Morelli P, Oddo M, Ben-Hamouda N. Role of automated pupillometry in critically ill patients. Minerva Anestesiol. 2019;85(9):995-1002.
  36. Najjar RP, Sharma S, Atalay E, et al. Pupillary responses to full-field chromatic stimuli are reduced in patients with early-stage primary open-angle glaucoma. Ophthalmology. 2018;125(9):1362-1371.
  37. Narayan V, Mohammed N, Savardekar AR, et al. Noninvasive intracranial pressure monitoring for severe traumatic brain injury in children: A concise update on current methods. World Neurosurg. 2018;114:293-300.
  38. Narita A, Shirai K, Kubota N, et al. Abnormal pupillary light reflex with chromatic pupillometry in Gaucher disease. Ann Clin Transl Neurol. 2014;1(2):135-140
  39. Nyholm B, Obling LER, Hassager C, et al. Specific thresholds of quantitative pupillometry parameters predict unfavorable outcome in comatose survivors early after cardiac arrest. Resusc Plus. 2023;14:100399.
  40. Oddo M, Friberg H. Neuroprognostication after cardiac arrest in the light of targeted temperature management. Curr Opin Crit Care. 2017;23(3):244-250.
  41. Olgun G, Newey CR, Ardelt A. Pupillometry in brain death: Differences in pupillary diameter between paediatric and adult subjects. Neurol Res. 2015;37(11):945-850
  42. Olitsky SE, Reynolds JD. Overview of glaucoma in infants and children. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed August 2016.
  43. Olson DM, Stutzman S, Saju C, et al. Interrater reliability of pupillary assessments. Neurocrit Care. 2016;24(2):251-257.
  44. Opic P, Ruegg S, Marsch S, et al. Automated quantitative pupillometry in the critically ill: A systematic review of the literature. Neurology. 2021;97(6):e629-e642.
  45. Packiasabapathy S, Zhang X, Ding L, et al. Quantitative pupillometry as a predictor of pediatric postoperative opioid-induced respiratory depression. Anesth Analg. 2021;133(4):991-999.
  46. Pansell J, Hack R, Rudberg P, et al. Can quantitative pupillometry be used to screen for elevated intracranial pressure? A retrospective cohort study. Neurocrit Care. 2022;37(2):531-537.
  47. Paramanathan S, Grejs AM, Soreide E, et al. Quantitative pupillometry in comatose out-of-hospital cardiac arrest patients: A post-hoc analysis of the TTH48 trial. Acta Anaesthesiol Scand. 2022;66(7):880-886.
  48. Patwari PP, Stewart TM, Rand CM, et al. Pupillometry in congenital central hypoventilation syndrome (CCHS): Quantitative evidence of autonomic nervous system dysregulation. Pediatr Res. 2012;71(3):280-285.
  49. Payen JF, Isnardon S, Lavolaine J, et al. Pupillometry in anesthesia and critical care. Ann Fr Anesth Reanim. 2012;31(6):e155-e159.
  50. Prescott BR, Saglam H, Duskin JA, et al. Anisocoria and poor pupil reactivity by quantitative pupillometry in patients with intracranial pathology. Crit Care Med. 2022;50(2):e143-e153.
  51. Richter P, Wilhelm H, Peters T, et al. The diagnostic accuracy of chromatic pupillary light responses in diseases of the outer and inner retina. Graefes Arch Clin Exp Ophthalmol. 2017;255(3):519-527.
  52. Rukmini AV, Milea D, Baskaran M, et al. Pupillary responses to high-irradiance blue light correlate with glaucoma severity. Ophthalmology. 2015;122(9):1777-1785.
  53. Rukmini AV, Milea D, Gooley JJ. Chromatic pupillometry methods for assessing photoreceptor health in retinal and optic nerve diseases. Front Neurol. 2019;10:76.
  54. Suo L, Zhang D, Qin X, et al. Evaluating state-of-the-art computerized pupillary assessments for glaucoma detection: A systematic review and meta-analysis. Front Neurol. 2020;11:777.
  55. Takayama K, Ito Y, Kaneko H, et al. Cross-sectional pupillographic evaluation of relative afferent pupillary defect in age-related macular degeneration. Medicine (Baltimore). 2016;95(39):e4978.
  56. Tamhankar M, Volpe NJ. Nonarteritic anterior ischemic optic neuropathy: Clinical features and diagnosis. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed August 2017.
  57. Taylor WR, Chen JW, Meltzer H, et al. Quantitative pupillometry, a new technology: Normative data and preliminary observations in patients with acute head injury. Technical note. J Neurosurg. 2003;98(1):205-213.
  58. Traylor JI, El Ahmadieh TY, Bedros NM, et al. Quantitative pupillometry in patients with traumatic brain injury and loss of consciousness: A prospective pilot study. J Clin Neurosci. 2021;91:88-92.
  59. Trent T, Vashisht A, Novakovic S, et al. Pupillary light reflex measured with quantitative pupillometry has low sensitivity and high specificity for predicting neuroworsening after traumatic brain injury. J Am Assoc Nurse Pract. 2023;35(2):130-134.
  60. Truong JQ, Ciuffreda KJ. Comparison of pupillary dynamics to light in the mild traumatic brain injury (mTBI) and normal populations. Brain Inj. 2016;30(11):1378-1389.
  61. Wilson MH, Edsell M, Imray C, et al. Changes in pupil dynamics at high altitude -- an observational study using a handheld pupillometer. High Alt Med Biol. 2008;9(4):319-325.
  62. Yan S, Tu Z, Lu W, et al. Clinical utility of an automated pupillometer for assessing and monitoring recipients of liver transplantation. Liver Transpl. 2009;15(12):1718-1727.
  63. Yang X, Fridman AJ, Unsworth N, Casement MD. Pupillary motility responses to affectively salient stimuli in individuals with depression or elevated risk of depression: A systematic review and meta-analysis. Neurosci Biobehav Rev. 2023;148:105125.