Optical Coherence Tomography of the Head and Neck

Number: 0928

Table Of Contents

Policy
Applicable CPT / HCPCS / ICD-10 Codes
Background
References


Policy

Aetna considers the following experimental and investgiational because their effectiveness has not been established:

  • Endoscopic OCT for evaluation of tympanoplasty; 
  • OCT for assessment and management of the middle ear;
  • OCT for evaluation of voice disorders.

For OCT for retinal disorders, see CPB 0344 - Optic Nerve and Retinal Imaging Methods.


Table:

CPT Codes / HCPCS Codes / ICD-10 Codes

Code Code Description

Information in the [brackets] below has been added for clarification purposes.   Codes requiring a 7th character are represented by "+" :

CPT codes not covered for indications listed in this CPB:

Optical Coherence Tomography of larynx -no specific code
0485T - 0486T Optical coherence tomography (OCT) of middle ear, with interpretation and report

ICD-10 codes not covered for indications listed in the CPB:

R47.0 - R47.9 Voice and resonance disorders

Background

Optical coherence tomography (OCT) is a non-invasive, non-contrast imaging technology which uses near-infrared light to produce high-resolution cross-sectional images. OCT was developed as a technique enabling high-resolution, real-time and in-situ imaging of tissue microstructure without the need for tissue excision and processing (Popescu, 2011). OCT technology is now emerging as a diagnostic tool for imaging the auditory system. Analogous to ultrasound by measuring the intensity of infrared light rather than acoustical waves, it is suggested that OCT could be a useful tool to see through the tympanic membrane into the middle ear without requiring surgical manipulation, and to help diagnose diseases associated with the tympanic membrane and middle ear (Cho et al., 2015; Pitris et al., 2001).

Monroy et al (2017) conducted a prospective observational case series in which optical coherence tomography (OCT) tracking was used to observe 25 pediatric patients diagnosed with chronic or recurrent otitis media perioperatively. Patients were followed before and throughout their treatment. Following OCT imaging, patient records were observed for an additional 6 months in follow-up. At each time point (preop, intraop, postop), the tympanic membrane (at the light reflex region) and directly adjacent middle-ear cavity were observed in vivo with a handheld OCT probe and portable system. Imaging results were compared with clinical outcomes to correlate the clearance of symptoms in relation to changes in the image-based features of infection. OCT images of most all participants showed the presence of additional infection-related biofilm structures during their initial consultation visit and similarly for patients imaged intraoperatively before myringotomy. Patients with no recurrence of infectious symptoms had no additional structures visible in OCT images during the postoperative visit. OCT image findings suggest surgical intervention consisting of myringotomy and tympanostomy tube placement provides a means to clear the middle ear of infection-related components, including middle-ear fluid and biofilms. Furthermore, the authors concluded that OCT was demonstrated as a rapid diagnostic tool to prospectively monitor patients in both outpatient and surgical settings.

Park et al (2017) conducted a prospective study to examine the tympanic membranes (TMs) of 120 patients with middle ear conditions using a handheld optical coherence tomography-based otoscope (860 nm central wave length, 15 μm axial resolution, 15 μm lateral resolution, and 7 mm scanning range using relay lens). Both OCT and oto-endoscope images were compared according to the clinical characteristics such as perforation, retraction, and postoperative healing process. The objective grade about the thickness of perforation margins and the accurate information about the extent of TM retraction that was not distinguishable by oto-endoscopic exam could be identified using this system. The postoperative healing process of TMs could be also followed using the OCT device. The authors concluded that their findings suggest that the handheld OCT device would be another useful application.

Cho et al (2015) report on the application of optical coherence tomography (OCT) for the diagnosis and evaluation of otitis media (OM). They evaluated 39 patients who were diagnosed with OM via standard otoendoscopic examination and audiological tests between July and October 2012. Six volunteers with normal tympanic membrane (TM) on otoendoscopy were also included, with OCT images used as a control. Of the 39 patients, OCT images were acquired from 16 patients (41.0%). The most common cause of failure to acquire an image was a narrow or curved external auditory canal (n=5). Other causes were the presence of obstacles, such as profuse otorrhea (n=3), cholesteatoma material (n=4), and cerumen (n=7), and poor compliance (n=4). OCT could not be obtained for the three patients with chronic OM with cholesteatomas. Despite the benefits such as noninvasiveness, lack of radiation, high resolution and ability to use outpatient, the authors report some limitations, such as, difficulty securing a light pathway for the OCT device, and the diagnostic efficiency of otoendoscopy. The authors concluded that their evaluation suggests that a handheld OCT otoscope can be applied clinically to otology, and that OCT has the potential to facilitate diagnosis of OM; however, further clinical trials are necessary.

MacDougall et al (2015) state that optical coherence tomography (OCT) for imaging the middle ear can present some challenges for real-time clinical use. Although OCT is noninvasive, the challenges included the need to work at a low numerical aperture, the deleterious effects of transtympanic imaging on image quality at the ossicles, sensitivity requirements for clinical fidelity of images at real-time rates, and the high dynamic-range requirements of the ear. (Abstract only)

Nguyen et al (2013) investigated the acoustic effects of bacterial biofilms, confirmed using optical coherence tomography (OCT), in adult ears. Biofilms have been linked to chronic otitis media (OM) and OM with effusion in the middle ear. Non-invasive OCT images were collected to visualize the 2D cross-sectional structure of the middle ear, verifying the presence of a biofilm behind the TM of 5 ears. Wideband measurements of acoustic reflectance and impedance (0.2 to 6 [kHz]) were used to study the acoustic properties of ears with confirmed bacterial biofilms. Compared to known acoustic properties of normal middle ears, each of the ears with a bacterial biofilm had an elevated power reflectance in the 1 to 3 [kHz] range, corresponding to an abnormally small resistance. The authors note that their preliminary study indicates that acoustic reflectance and impedance measurements may have utility for assessment of the presence and acoustic impact of biofilms in the middle ear; however, future study of a wide range of OM-related conditions, with definitive biofilm and non-biofilm classifications, is needed.

UpToDate reviews on “Evaluation and management of middle ear trauma” (Evans and Handler, 2017), “Acute otitis media in adults” (Limb et al., 2017), “Acute otitis media in children: Diagnosis” (Wald, 2017), and “Eustachian tube dysfunction” (Poe and Hanna, 2016) do not mention use of optical coherence tomography for diagnosis or management.

In a prospective, case-series study, Monroy and colleagues (2018) characterized OM-associated structures affixed to the mucosal surface of the tympanic membrane (TM) in-vivo and in surgically recovered in-vitro samples. A total of 40 pediatric subjects scheduled for tympanostomy tube placement surgery were imaged intra-operatively under general anesthesia.  Post-myringotomy, a portable OCT imaging system assessed for the presence of any biofilm affixed to the mucosal surface of the TM.  Samples of suspected microbial infection-related structures were collected through the myringotomy incision. The sampled site was subsequently re-imaged with OCT to confirm collection from the original image site on the TM.  In-vitro analysis based on confocal laser scanning microscope (CLSM) images of fluorescence in-situ hybridization (FISH)-tagged samples and polymerase chain reaction (PCR) provided microbiological characterization and verification of biofilm activity; OCT imaging was achieved for 38 of 40 subjects (95 %).  Images from 38 of 38 (100 %) of subjects observed with OCT showed the presence of additional microbial infection-related structures; 34 samples were collected from these 38 subjects.  CLSM images provided evidence of clustered bacteria in 32 of 33 (97 %) of samples; PCR detected the presence of active bacterial DNA signatures in 20 of 31 (65 %) of samples.  The authors concluded that PCR and CLSM analysis of FISH-stained samples validated the presence of active bacteria that have formed into a middle ear biofilm that extended across the mucosal layer of the TM.  Moreover, these researchers stated that in the future, OCT could be used to rapidly and quantitatively assess for the presence of a middle ear biofilm without invasive sampling, as in the primary care office.  This capability allows for the longitudinal tracking of middle ear biofilms, specifically their formation and resolution at different stages of OM and when exposed to existing or newly developed pharmacologic or surgical treatment strategies.  The OCT system provided an imaging depth up to approximately 2 mm into tissue, even semi-transparent or highly scattering tissues such as the TM.  This capability allowed cross-sectional depth-resolved visualization and quantification of the TM and any adjacent structure in the middle ear cavity (MEC).  Since the middle ear mucosa (MEM) is known to support biofilms, these researchers are developing a swept-source OCT system to provide visualization of deeper structures within the MEC, up to a centimeter or more, including the ossicles and the MEM.

The authors stated that this study had several limitations.  First, there was no control group.  No TM mucosa samples were collected for analysis from healthy pediatric subjects undergoing non-OM-related surgeries.  However, it was previously demonstrated that normal ears have no biofilms on the MEM.  Other studies similarly reported that normal ears lack biofilm-related structures, as shown in a rat model with a combination of OCT and histology and in normal adult and pediatric ears with OCT.  Second, prior to sample collection, the MEC was not aspirated to remove any effusion, and samples were not washed before being placed in fixative.  Given the numerous FISH processing steps, it was unlikely that an effusion had any significant effect on these results.  Moreover, positive CLSM images were evaluated by consistent and repeated fluorescent signal embedded within the biofilm matrix, not from the exterior of the structure.  Aspiration of any middle ear effusion (MEE) before imaging and sampling may also inadvertently remove biofilm material and confound sample collection.  Third, it was possible that some samples, once divided for PCR and FISH/CLSM, did not have active bacterial populations.  However, it was likely that in other samples, the amount of genetic material for analysis was simply limited.  Some recovered samples were small (approximately 1 mm3), and no additional culturing to expand bacterial concentration was performed.  While FISH results were able to identify single bacteria, PCR requires a minimum amount of genetic material, which may explain why some samples had no identifiable bacteria.  Furthermore, this study analyzed the 3 most common bacterial species known to cause OM, although many other bacterial strains have been identified.  Thus, these factors may explain why some samples did not confirm the hypothesis with combined PCR and CLSM/FISH imaging results.  However, when sufficient genetic material was present for 1 or both techniques, the resulting measurements were not degraded by the heterogeneous composition of these samples, which can include white and red blood cells, MEE fluid, other bacteria, and cell and biofilm fragments. 

Tan and associates (2018) evaluated the recent developments in OCT for TM and middle ear imaging and identified what further development is needed for the technology to be integrated into common clinical use.  Data sources included PubMed, Embase, Google Scholar, Scopus, and Web of Science.  A comprehensive literature search was performed for English language articles published from January 1966 to January 2018 with the keywords "tympanic membrane or middle ear", "optical coherence tomography" and "imaging".  These investigators stated that conventional imaging techniques cannot adequately resolve the microscale features of TM and middle ear, sometimes necessitating diagnostic exploratory surgery in challenging otologic pathology.  As a high-resolution non-invasive imaging technique, OCT offers promise as a diagnostic aid for otologic conditions, such as OM, cholesteatoma, and conductive hearing loss.  Using OCT vibrometry to image the nanoscale vibrations of the TM and middle ear as they conduct acoustic waves may detect the location of ossicular chain dysfunction and differentiate between stapes fixation and incus-stapes discontinuity. The capacity of OCT to image depth and thickness at high resolution allows 3-dimensional volumetric reconstruction of the ME and has potential use for reconstructive tympanoplasty planning and the follow-up of ossicular prostheses.  These researchers stated that to achieve common clinical use beyond these initial discoveries, future in-vivo imaging devices must feature low-cost probe or endoscopic designs and faster imaging speeds and demonstrate superior diagnostic utility to computed tomography (CT) and magnetic resonance imaging (MRI).  While such technology has been available for OCT, its translation requires focused development through a close collaboration between engineers and clinicians.

Jeon and co-workers (2019) noted that Doppler OCT (DOCT) is useful for both, the spatially resolved measurement of the TM oscillation and high-resolution imaging.  These investigators demonstrated a new technique capable of providing real-time two-dimensional (2D) Doppler OCT image of rapidly oscillatory latex mini-drum and in-vivo rat TM and ossicles.  Using DOCT system, the oscillation of sample was measured at frequency range of 1- to 4-kHz at an output of 15 W.  After the sensitivity of the DOCT system was verified using a latex mini-drum consisting of a 100 μm-thick latex membrane, changes in displacement of the umbo and contacted area between TM and malleus in normal and pathologic conditions were measured.  The oscillation cycles of the mini-drum for stimulus frequencies were 1.006 kHz for 1-kHz, 2.012 kHz for 2-kHz, and 3.912 kHz for 4-kHz, which meant that the oscillation cycle of the mini-drum became short in proportional to the frequency of stimuli.  The oscillation cycles of umbo area and the junction area in normal TM for frequencies of the stimuli showed similar integer ratio with the data of latex mini-drum for stimuli less than 4-kHz.  In the case of MEM condition, the Doppler signal showed a tendency of attenuation in all frequencies, which was prominent at 1-kHz and 2-kHz.  The TM vibration under sound stimulation with frequencies from 1-kHz to 4-kHz in normal and pathologic conditions was demonstrated using signal demodulation method in in-vivo condition.  The OCT technology could be helpful for functional and structural assessment as an optional modality.  This preliminary study used a signal de-modulation method to demonstrate TM vibration under sound stimulation at frequencies of 1-, 2-, and 4-kHz in a normal ear and an ear under simulated pathological condition in-vivo and implemented three-dimensional (3D) reconstruction of the TM vibration under sound stimulation.  The difference between the oscillation pattern at low-frequency and high-frequency was identified, but further study is needed to validate this method and its results.  These researchers stated that they will conduct detailed studies on abnormal models and further animal and human experiments.

Monroy and colleagues (2019) stated that the diagnosis and treatment of OM is a significant burden on the healthcare system.  Diagnosis relies on observer experience via otoscopy, although for non-specialists or inexperienced users, accurate diagnosis can be difficult.  In past studies, OCT has been used to quantitatively characterize disease states of OM, although with the involvement of experts to interpret and correlate image-based indicators of infection with clinical information.  These investigators presented a flexible and comprehensive framework that automatically extracts features from OCT images, classifies data, and presents clinically relevant results in a user-friendly platform suitable for point-of-care (POC) and primary care settings.  This framework was used to test the discrimination between OCT images of normal controls, ears with biofilms, and ears with biofilms and MEM.  Predicted future performance of this classification platform returned promising results (90 %+ accuracy) in various initial tests.  The authors stated that with integration into patient healthcare workflow, users of all levels of medical experience may be able to collect OCT data and accurately identify the presence of middle ear fluid and/or biofilms.

These researchers stated that “Currently, there is no accepted method to identify the presence of middle ear biofilms (MEBs), although it is likely that biofilms increase the opacity of the TM during infection.  In this study, the development of the “Normal”, “Biofilm”, and “Fluid and Biofilm” states was made possible by observing the image-based features in OCT data in this and past studies.  It was observed that subjects with more severe cases of OM have MEF in addition to an accompanying MEB.  This raises additional questions about the pathogenesis of MEB during OM; questions that are beyond the scope of this present study.  OCT, however, could be one tool that provides a quantitative identification of biofilms and fluid, and in addition, provide further characterization of the purulence or scattering of the fluid.  In this and prior studies, it is common to identify a biofilm layer and middle ear fluid in subjects with more severe cases of OM.  As infections progress, any MEF becomes more purulent and optically scattering, depending on the duration of the infection.  This is likely due to increasing amounts of immune cell activity and biofilm dispersal within the MEC.  Clinicians do not currently diagnose or treat middle ear biofilms as there is no accepted diagnostic tool, nor established or tested/verified treatment regimen.  With these limitations in mind, this platform may offer the immediate potential to identify the presence of MEF and MEB, as well as enable new and expanded capabilities in the future.  The use of machine learning (ML) analysis to classify OCT images from subjects with OM can provide a means to automatically classify data and provide a probable diagnostic outcome.  When an image is successfully collected, a combined OCT + ML platform could ensure the user would have a minimum baseline skill for detecting diagnostic markers for OM.  In its current form, this platform is intended to supplement the assessment of the numerous quantitative details within the data and apparent in tissue, and integrate statistical measures to help guide decision making.  In turn, with an accurate diagnosis, it may then be possible to provide the most appropriate and effective treatment for the current state of infection.  This platform is not intended to replace clinical expertise, but offers the potential for further research and clinical investigations before being validated as an approved technology for clinical decision making”.

Oh and colleagues (2020) examined if OCT provides useful information regarding the micro-structures of the middle and inner ear via the extra-tympanic approach and thereby could be utilized as an alternative diagnostic technology in ear imaging.  A total of 5 rats and mice were included, and the swept-source OCT system was used to confirm the extent of visibility of the middle and inner ear and measure the length or thickness of the microstructures in the ear.  The cochlea was subsequently dissected following OCT and histologically evaluated to compare with the OCT images.  The middle ear microstructures such as ossicles, stapedial artery and oval window through the tympanic membrane with the OCT could be confirmed in both rats and mice.  It was also possible to obtain the inner ear images such as each compartment of the cochlea in the mice, but the bone covering bulla needed to be removed to visualize the inner ear structures in the rats, which had thicker bulla.  The bony thickness covering the cochlea could be measured, which showed no significant differences between OCT and histologic image at all turns of cochlea.  The authors concluded that OCT has been shown a promising technology to evaluate real-time middle and inner ear microstructures non-invasively with a high-resolution in the animal model; thus, OCT could be used to provide additional diagnostic information regarding the diseases of the middle and inner ear.

In a cross-sectional study, Preciado and co-workers (2020) examined the feasibility of detecting and differentiating middle ear effusions (MEEs) using an OCT otoscope.  A total of 70 pediatric patients undergoing tympanostomy tube placement were pre-operatively imaged using an OCT otoscope.  A blinded reader quiz was conducted using 24 readers from 4 groups of tiered medical expertise.  The primary outcome was reader ability to detect presence/absence of MEE; a secondary outcome was reader ability to differentiate serous versus non-serous MEE.  OCT image data-sets were analyzed from 45 of 70 total subjects.  Blinded reader analysis of an OCT data subset for detection of MEE resulted in 90.6 % accuracy, 90.9 % sensitivity, 90.2 % specificity, and intra-/inter-reader agreement of 92.9 % and 87.1 %, respectively.  Differentiating MEE type, reader identification of non-serous MEE had 70.8 % accuracy, 53.6 % sensitivity, 80.1 % specificity, and intra-/inter-reader agreement of 82.9 % and 75.1 %, respectively.  Multi-variate analysis revealed that age was the strongest predictor of OCT quality.  The mean age of subjects with quality OCT was 5.01 years (n = 45), compared to 2.54 years (n = 25) in the remaining subjects imaged (p = 0.0028).  The ability to capture quality images improved over time, from 50 % to 69.4 % over the study period.  The authors concluded that OCT otoscopy showed promise for facilitating accurate MEE detection.  The imageability with the prototype device was affected by age, with older children being easier to image, similar to current ear diagnostic technologies.

Prasad and colleagues (2020) summarized the literature regarding clinical and pre-clinical imaging techniques used for optical identification of middle ear infections.  Clinical methods of examining infections using a conventional otoscope, tympanometry, and OCT were discussed along with their advantages and limitations.  The list of clinical trial further presented the current medical devices used to diagnose middle ear infections.  Furthermore, novel pre-clinical approaches and information on non-invasive Raman spectroscopy techniques for the detection of middle ear infection were presented to provide an outline of the current literature and to create a guideline for future progress.  The authors concluded that although these non-invasive techniques are promising, future work should be directed to conducting clinical trials for these emerging imaging techniques to combat the suspected inefficiency in the current otologic diagnosis and help with the accurate treatment of middle ear infection decision-making.

Byun and colleagues (2021) noted that imaging the Eustachian tube is challenging because of its complex anatomy and limited accessibility.  These researchers fabricated a fiber-based OCT catheter and examined its potential for evaluating the Eustachian tube anatomy.  A customized OCT system and an imaging catheter, termed the Eustachian OCT, were developed for visualizing the Eustachian tube.  Three male swine cadaver heads were used to study OCT image acquisition and for subsequent histologic correlation.  The imaging catheter was introduced via the nasopharyngeal opening and reached toward the middle ear.  The OCT images were acquired from the superior to the nasopharyngeal opening before and after Eustachian tube balloon dilatation.  The histological anatomy of the Eustachian tube was compared with corresponding OCT images.  The new, Eustachian OCT catheter was successfully inserted in the tubal lumen without damage.  Cross-sectional images of the tube were successfully obtained, and the margins of the anatomical structures including cartilage, mucosa lining, and fat could be successfully delineated.  After balloon dilatation, the expansion of the cross-sectional area (CSA) could be identified from the OCT images.  The authors concluded that the use of the OCT technique to evaluate the Eustachian tube anatomy was shown to be feasible, and the fabricated OCT image catheter was determined to be suitable for Eustachian tube assessment.  These researchers expect the fabrication of the Eustachian OCT catheter to be an initial step in the clinical application of OCT in Eustachian tube assessment.

Won and associates (2021) stated that a middle ear infection is a prevalent inflammatory disease most common in the pediatric population, and its financial burden remains substantial.  Current diagnostic methods are highly subjective, relying on visual cues gathered by an otoscope.  To address this shortcoming, OCT has been integrated into a hand-held imaging probe.  This system can non-invasively and quantitatively evaluate middle ear effusions and identify the presence of bacterial biofilms in the middle ear cavity during ear infections.  Furthermore, the complete OCT system is housed in a standard briefcase to maximize its portability as a diagnostic device.  Nonetheless, interpreting OCT images of the middle ear more often requires expertise in OCT as well as middle ear infections, making it difficult for an untrained user to operate the system as an accurate stand-alone diagnostic tool in clinical settings.  These researchers presented a briefcase OCT system implemented with a real-time machine learning (ML) platform for middle ear infections.  A random forest-based classifier can categorize images based on the presence of middle ear effusions and biofilms.  This study demonstrated that the briefcase OCT system coupled with machine learning could provide user-invariant classification results of middle ear conditions, which may greatly improve the use of this technology for the diagnosis and management of middle ear infections.

The authors stated that this study had several drawbacks.  In general, the processing power and memory of the laptop were limiting factors in the speed of OCT processing and display, as well as for the ML classifier.  Note that all the hardware and optical components used in the system were off-the-shelf products.  Implementing graphic processing units (GPUs) will further accelerate the speed of the system.  With emerging technologies and products in compact OCT waveguides that integrate a light source and detector, the size of the system can be further reduced in the future.  As the briefcase system did not use a lateral scanning element to generate B-mode images of the middle ear, the measurements can be affected by the spatial locations of the focused beam on the tympanic membrane (TM).  Implementing a compact lateral scanning mechanism using a microelectromechanical systems (MEMS)-based mirror can reliably provide lateral information, which would aid in minimizing the spatial dependence of the measurements.  This may further improve the usability and system performance.  In the future, with a larger database and an improved model, hyperparameter tuning will be carried out to compare different ML models.  This model has been internally validated and examined using the leave-one-out cross-validation method.  External validation was limited due to the small size of the dataset.  With the increasing number of ear OCT images and datasets in the future, the model will be further improved by external validation using a held-out, independent dataset.  The spatial dependence of measurements from the TM can also be overcome with an improved ML classifier (e.g., the dataset of OCT images containing different regions on the TM can be obtained and trained in the ML classifier).  OCT images with various image artifacts (mirror artifacts, flipped image and strong reflections) can also be collected and included in the training dataset.  This would exclude the measurements with artifacts and could potentially guide the users to avoid these artifacts during imaging.  It was also observed that the novice users heavily relied on the surface images of the TM to guide and focus the laser beam during the imaging.  In the future, a CCD camera with a higher resolution, a larger field-of-view and a greater depth-of-focus to capture the entire TM will be helpful for users without prior knowledge of OCT.  The surface images of the TM were not included in the classifier, as the properties of the CCD images (i.e., lighting, field-of-view, depth-of-focus and resolution) from the briefcase system were different from the trained otoscopy images in the previously developed classifier.  With greater computing power in the future, providing the surface images of the TM to the classifier may enhance the classification accuracy.  Finally, having rigid time constraints to image patients’ ears in a busy clinical environment may have resulted in suboptimal image quality in some cases.  While trained users without prior experience of OCT and otoscopy attempted to image the subjects diagnosed with OM, not all users were successful to acquire reliable datasets because of the given time constraints.  Allowing for a longer imaging time window with more training and practice will improve image quality.  A larger number of subjects diagnosed with OM are needed in future clinical studies to better characterize the clinical significance and accuracy of the system.  Furthermore, this study only recruited adult subjects because participants needed to be tolerant to allow 3 different users to image their ears.  A future study will include pediatric subjects as well and examine differences that may emerge in this patient population.  Lastly, more researchers are needed to correlate and examine the dataset, ground truth, and the label, to determine the diagnostic importance of AI-assisted OCT otoscopy in clinical practice.

Lui et al (2021) described an OCT and vibrometry system designed for portable hand-held usage in the otology clinic on awake patients.  The system provides clinically relevant POC morphological imaging with 14 to 44 µm resolution and functional vibratory measures with sub-nanometer sensitivity.  These researchers examined various new approaches for extracting functional information including a multi-tone stimulus, a continuous chirp stimulus, and alternating air and bone stimulus.  They also examined the vibratory response over an area of the TM and generated TM thickness maps.  The authors concluded that these findings suggested that the system could provide real-time in-vivo imaging and vibrometry of the ear and could prove useful for investigating otologic pathology in the clinic setting.  Moreover, these investigators stated that the clinical utility of this device will require validation in large patient populations; and follow-up studies are needed to demonstrate the effectiveness of OCT in the clinic to detect and diagnose middle ear pathology.

Endoscopic OCT for the Evaluation of Tympanoplasty Outcome

Morgenstern and associates (2020) noted that after tympanoplasty, it is often challenging to differentiate between different causes of a remaining air bone gap (ABG); OCT offers a new approach for combined morphologic and functional measurements of the tympanic membrane and adjacent parts of the middle ear.  It provides diagnostic information in patients with a reduced sound transfer after middle ear surgery.  In this single-case study, a patient with history of tympanoplasty and a persistent ABG was examined with endoscopic OCT prior to revision surgery.  The oscillation behavior and the thickness of the reconstructed tympanic membrane was determined.  The oscillation amplitudes of the inserted prosthesis were compared to a finite element model simulation and to the clinical findings and the audiometric data of the patient.  OCT measurements showed a reduced oscillation amplitude of the prosthesis while revealing an aerated middle ear and good coupling of the prosthesis.  Transfer loss measured by OCT showed a similar progression as the ABG measured by pure-tone audiometry with a mean divergence of 4.45 dB.  The authors concluded that endoscopic OCT is a promising tool for the evaluation of tympanoplasty outcome; it supports established otologic diagnostics and could aid in differentiating between different causes of conductional hearing loss.

Optical Coherence Tomography for Evaluation of Voice Disorders

Benboujja and Hartnick (2021) stated that identifying distinct normal extracellular matrix (ECM) features from pathology is of the upmost clinical importance for laryngeal diagnostics and therapy.  Despite remarkable histological contributions, the understanding of the vocal fold (VF) physiology remains murky.  The emerging field of non-invasive 3D optical imaging may be well-suited to unravel the complexity of the VF microanatomy.  These researchers characterized the entire VF ECM in length and depth with optical imaging.  A quantitative morphometric evaluation of the human VF lamina propria using two-photon excitation fluorescence (TPEF), second harmonic generation (SHG), and OCT was examined.  Fibrillar morphological features, such as fiber diameter, orientation, anisotropy, waviness and 2nd-order statistics features were evaluated and compared according to their spatial distribution.  The evidence acquired in this study suggested that the VF ECM is not a strict discrete 3-layer structure as traditionally described but instead a continuous assembly of different fibrillar arrangement anchored by predominant collagen transitions zones.  These investigators demonstrated that the ECM composition was distinct and markedly thinned in the anterior 1/3 of itself, which may play a role in the development of some laryngeal diseases.  These researchers further examined and extracted the relationship between OCT and multi-photon imaging, promoting correspondences that could lead to accurate 3D mapping of the VF architecture in real-time during phono-surgeries.  As miniaturization of optical probes is consistently improving, a clinical translation of OCT imaging and multi-photon imaging, with valuable qualitative and quantitative features, may have significant implications for treating voice disorders.  Moreover, these researchers stated that further investigations are needed, such as performing real-time imaging while applying a deformation on the laryngeal structure, mimicking stress involved during phonation.

The authors stated that this study had several drawbacks.  First, the number of specimens in this study was limited and did not highlight differences between age and gender, as previously reported by histological studies.  Although OCT acquisitions were carried out on intact dissected larynges, multi-photon imaging acquisitions were acquired on cross-sections, subject to dehydration and fixation artifacts that inevitably affected the morphological and mechanical features of the VF.  A possible solution would be to image the VF without sectioning; however, this would limit the penetration depth to 250 to 400 μm, but should still be sufficient to access the superficial lamina propria and perhaps the superior transition of the vocal ligament.  Furthermore, this study did not differentiate between collagen fiber types (type I and III to VI) present in the lamina propria, which may be helpful to expose lesions and/or post-scar formation.  Ongoing investigations are examining extracting collagen fiber types via a susceptibility tensor analysis with a polarization-resolved SHG microscope, and combining outcomes to a birefringence analysis using polarization-sensitive OCT.  These investigators anticipated that the spatial arrangement of entangled collagen fibers will generate a different gradient of birefringence.  The system sensitivity in OCT (roll-off effect) is an important factor in estimating the attenuation coefficients.  The system used in this study (VCSEL) has a long coherence length and can maintain its sensitivity at greater than 100 dB over a large imaging depth.  Considering that the imaging window was within 2 mm, the effect of roll-off was negligible.  However, as previously reported, a calibration tool would be a valuable adjunct to improve data analysis and longitudinal or multi-center comparison.  The authors stated that despite the small sample size, it was apparent that predicting surgical outcomes and optimizing voice therapy is contingent on a proper evaluation of the microscopic LP features.  It would be interesting to combine relevant pixel-based, A-Line-based, and layer-based features with a machine learning classifier for automatic recognition of the LP regions.  This study reported the 1st quantitative assessment of the entire vocal fold ECM using multi-photon and OCT.  They stated that future biomechanical investigations may take advantage of those parameters to characterize and quantify the impact of stain-stiffness experiments on collagen fibers at global and local levels in real-time.  Furthermore, as pathophysiology plays a role in the re-modeling of the lamina propria, those quantitative values and features may help understand the etiology of some benign and malignant lesions.

References

The above policy is based on the following references:

  1. Benboujja F, Hartnick C. Quantitative evaluation of the human vocal fold extracellular matrix using multiphoton microscopy and optical coherence tomography. Sci Rep. 2021;11(1):2440.
  2. Byun H, Kim YH, Xing J, et al. Utilization potential of intraluminal optical coherence tomography for the Eustachian tube. Sci Rep. 2021;11(1):6219.
  3. Cho NH, Lee SH, Jung W, et al. Optical coherence tomography for the diagnosis and evaluation of human otitis media. J Korean Med Sci. 2015;30(3):328-335.
  4. Evans AK, Handler SD. Evaluation and management of middle ear trauma. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed November 2017.
  5. Jeon D, Cho NH, Park K, et al. In vivo vibration measurement of middle ear structure using Doppler optical coherence tomography: Preliminary study. Clin Exp Otorhinolaryngol. 2019;12(1):40-49.
  6. Limb CJ, Lustig LR, Klein JO. Acute otitis media in adults.  UpToDate [online serial]. Waltham, MA: UpToDate; reviewed April 2017.
  7. Lui CG, Kim W, Dewey JB, et al. In vivo functional imaging of the human middle ear with a hand-held optical coherence tomography device. Biomed Opt Express. 2021;12(8):5196-5213.
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