Cerebral Perfusion Studies

Number: 0663


Aetna considers cerebral computed tomography (CT) perfusion studies medically necessary for the emergent evaluation of acute cerebral ischemia (acute stroke) when either of the following criteria is met:

  • CT perfusion studies will be used as a supplement to non-contrast head CT; or
  • Magnetic resonance imaging is unavailable or contraindicated.

Aetna considers cerebral CT perfusion studies experimental and investigational for the following indications because there is inadequate scientific evidence to support its use for these indications (not an all-inclusive list):

  • Confirmation of brain death
  • Differentiation of lung cancer from benign lesions
  • Evaluation of vasospasm and delayed cerebral ischemia following aneurysmal subarachnoid hemorrhage
  • Evaluation of cerebral gliomas (including differentiation of high-grade gliomas from low-grade gliomas, lymphomas, metastases and abscess)
  • Evaluation of cerebral vasospasm
  • Evaluation of chronic cerebral ischemia
  • Evaluation of head trauma
  • Evaluation of herpes simplex virus encephalitis
  • Monitoring of Moyamoya disease
  • Prognosis of traumatic brain injury
  • Triaging persons with stroke for thrombolytic therapy
  • Use in the balloon occlusion test
  • Use in vascular neurosurgery.

Aetna considers cerebral magnetic resonance imaging (MRI) perfusion studies (diffusion-weighted or perfusion-weighted) medically necessary for the evaluation of acute cerebral ischemia.

Aetna considers cerebral MRI perfusion studies experimental and investigational for the following indications (not an all-inclusive list) because its effectiveness for these indications has not been established

  • Assessment of response to angiogenesis inhibitors in persons with glioblastomas
  • Diagnosis of recurrent brain metastases after radiotherapy
  • Evaluation of brain arterio-venous malformations
  • Evaluation of head and neck cancers
  • Evaluation of gliomas/glioblastomas (including differentiation of glioma recurrence from pseudo-progression, differentiation of high-grade glioma from primary central nervous system lymphoma, and differentiation of low-grade gliomas from high-grade glioma)
  • Evaluation of idiopathic normal pressure hydrocephalus
  • Evaluation of persistent pain
  • Evaluation of traumatic brain injury
  • Differentiation of radiation-induced necrosis from recurrent brain tumor
  • Identification of new infarcts following ischemic injury (e.g., minor brain infarction or transient ischemic attack)
  • Prognostication of obstructive sleep apnea
  • Use as a putative biomarker of Parkinson’s disease.


Computed Tomography Perfusion Studies

A computed tomography (CT) scan produces cross-sectional images from X-rays processed by a computer. Each image slice corresponds to a thin section of the body that can be examined to reveal internal structures in detail. Such precision is particularly important when considering conditions involving internal tissues and organs. CT scans are useful in detecting disease in symptomatic individuals.

Computed tomography (CT) perfusion imaging provides a quantitative measurement of regional cerebral blood flow.  Cerebral perfusion analysis is used in neuroradiology to assess tissue level perfusion and delivery of blood to the brain and/or tissues of the head.  A perfusion CT study involves sequential acquisition of CT sections during intravenous administration of an iodinated contrast agent. The procedure involves injecting a contrast agent into the individual. The blood carries the contrast agent to the brain and the rate at which it accumulates in the brain is detected by a CT scanner. Analysis of the results allows the physician to calculate the regional cerebral blood volume, the blood mean transit time through the cerebral capillaries, and the regional cerebral blood flow. 

Currently, non-contrast computed tomography is used to detect intracerebral hemorrhage in stroke patients who are being considered for thrombolytic therapy.

Computed tomography perfusion imaging has been proposed to be used primarily as a method of evaluating patients suspected of having an acute stroke whenever thrombolysis is considered.  Computed tomography perfusion imaging may provide information about the presence and site of vascular occlusion, the presence and extent of ischemia, and about tissue viability.  This information may help the clinician determine whether thrombolysis is appropriate.

Potential advantages of CT perfusion imaging are that it can be performed using standard CT scanners, which are more widely available and less expensive than magnetic resonance imaging (MRI), and it is less invasive than CT angiography.  Computed tomography perfusion imaging can be performed rapidly, and involves injection of a relatively small amount of contrast agent.

Current literature on CT perfusion imaging has focused on its feasibility and technical capabilities.  Prospective clinical studies are needed to determine the clinical value of CT perfusion imaging over standard non-contrast computed tomography in the assessment of patients with symptoms suggestive of acute stroke, and in the triage of patients in whom thrombolytic therapy is contemplated.

The Council on Cardiovascular Radiology of the American Heart Association provided guidelines and recommendations for perfusion imaging in cerebral ischemia (Latchaw et al, 2003).  It stated that quantitative CT perfusion may possibly be useful to differentiate between reversibly and irreversibly ischemic tissues in patients with acute stroke.  However, large prospective and appropriately blinded studies are needed to ascertain the value of this technique.  There are no data regarding the ability of this technique to predict the potential for hemorrhage following thrombolysis, as there is for the diffusible tracer techniques.  Furthermore, no recommendation can be made for the use of CT perfusion in patients with chronic ischemia, vasospasm, head trauma, or as part of the balloon occlusion test, the traditional method for identifying patients at risk for stroke.

In a review on imaging viable brain tissue with CT scan during acute stroke, Meuli (2004) stated that perfusion CT is now ready to be used in clinical trials as a decision-making tool to tailor more precisely the thrombolytic therapy to the individual patient.

Ding et al (2006) simultaneously examined regional cerebral blood volume (rCBV) and permeability surfaces (rPS) in glioma patients to determine their correlation with histological grade using CT perfusion imaging.  A total of 22 patients with gliomas underwent multi-slice CT perfusion imaging pre-operatively.  Low-grade and high-grade groups were categorized corresponding to World Health Organization (WHO) grade II gliomas and WHO grade III or IV gliomas, respectively, as determined by histopathological examination.  Regional cerebral blood volume and rPSs were obtained from regions of maximal abnormality in tumor parenchyma on CBV and PS color perfusion maps.  Perfusion parameters were compared using the Kruskal-Wallis test in order to evaluate the differences in relation to tumor grade.  The Pearson coefficients of rCBV and rPS for each tumor grade were assessed using SPSS 13.0 software.  Regional cerebral blood volume and rPS provided significant P-value in differentiating glioma grade (low-grade gliomas 3.28 +/- 2.01 versus 2.12 +/- 3.19 ml/100 g/min, high-grade gliomas 8.87 +/- 4.63 versus 12.11 +/- 3.18 ml/100 g/min, p < 0.05).  Receiver operating characteristic (ROC) curves revealed better specificity and sensitivity in PS than in CBV for glioma grade.  A significant correlation between rCBV and rPS was observed in high-grade gliomas (r = 0.684).  Regional cerebral blood volume in oligodendrogliomas were higher than in other low-grade gliomas, whereas their rPS values did not show a parallel difference.  The authors concluded that perfusion CT provides useful information for glioma grading and might have the potential to significantly impact clinical management and follow-up of cerebral gliomas.

Marco de Lucas et al (2006) noted that an early diagnosis is crucial in herpes simplex virus encephalitis patients in order to institute acyclovir therapy and reduce mortality rates.  Magnetic resonance imaging is considered the gold standard for evaluation of these patients, but is frequently not available in the emergency setting.  These investigators reported the first case of a CT perfusion study that helped to establish a prompt diagnosis revealing abnormal increase of blood flow in the affected temporo-parietal cortex at an early stage.

Sajjad (2008) noted that cerebral perfusion imaging allows blood flow to the cerebral tissue to be imaged.  It has been used in the management of acute ischemic stroke.  Using either CT or MRI techniques, perfusion maps can be created in a short enough time to allow their routine use in clinical practice.  Perfusion imaging enables physicians to directly estimate the tissue at risk, which can be salvaged with reperfusion, enabling appropriate patient selection.  However, perfusion imaging has its limitations that need to be kept in mind when these studies are interpreted.  Although perfusion imaging is widely used, the evidence to support its routine use in acute stroke is somewhat sparse and therefore there are no clear cut guidelines as to its role in this context.

Parsons (2008) stated that combining perfusion CT with CT angiography (CTA) and non-contrast CT (NCCT) provides much more information about acute stroke pathophysiology than NCCT alone.  This multi-modal CT approach adds only a few minutes to the standard NCCT and is more accessible and rapidly available in most centers than MRI.  Perfusion CT can distinguish between infarct core and penumbra, which is not possible with NCCT alone.  A small infarct core and large penumbra, plus the presence of vessel occlusion on CTA may be an ideal imaging "target" for thrombolysis.  To date, multi-modal CT has predominantly been assessed in hemispheric stroke due to its limited spatial coverage.  This will become less of an issue as slice coverage continues to improve with new generation CT scanners.  Apart from the concepts above, more specific perfusion CT and CTA criteria that increase (or decrease) probability of response to thrombolytic treatment are yet to be determined. Nonetheless, perfusion CT thus has the potential to improve patient selection for thrombolysis.

Provenzale et al (2008) performed a meta-analysis on perfusion imaging to determine its role in clinical decision making for patients with acute cerebral ischemia.  These investigators searched Medline by using a strategy that combined terms related to perfusion imaging with terms related to acute cerebral ischemia and brain tumors.  They identified 658 perfusion imaging articles and classified them according to the clinical usefulness criteria of Thornbury and Fryback; and found 59 articles with promise of indicating usefulness in clinical decision making.  These researchers devised and implemented a clinical decision-making scoring scale more appropriate to the topic of acute cerebral ischemia.  Several articles provided important insights into the physiological processes underlying acute cerebral ischemia by correlation of initial perfusion imaging deficits with clinical outcome or ultimate size of the infarct.  However, most articles showed relatively low relevance to influencing decisions in implementing treatment.  The authors concluded that most perfusion imaging articles were oriented toward important topics such as optimization of imaging parameters, determination of ischemia penumbra, and prediction of outcome.  However, information as to the role of perfusion imaging in clinical decision-making is lacking.  They stated that studies are needed to demonstrate that use of perfusion imaging changes outcome of patients with acute cerebral ischemia.

Wang et al (2010) noted that CT perfusion (CTP) mapping has been reported to be useful in the differentiation of the infarct core and ischemic penumbra.  However, the value of the CTP source imaging (CTP-SI) during the arterial and venous phases has not been fully investigated.  These researchers developed a CTP-SI methodology for acute ischemic stroke and compared its effectiveness with cerebral blood flow (CBF) and cerebral blood volume (CBV) in predicting infarct core and penumbra.  Computed tomographic examinations, including NCCT, CTP, and CTA, were performed in 42 patients with symptoms of stroke for less than 9 hours.  The Alberta Stroke Program Early CT Score (ASPECTS) was analyzed on the arterial phase CTP-SI and venous phase CTP-SI and then compared with the ASPECTS on CBF and CBV for effectiveness assessment.  The ASPECTS on the arterial phase CTP-SI was closely correlated with the ASPECTS on CBF, the Pearson correlation coefficient was 0.88 (p < 0.001), and the concordance correlation coefficient was 0.7603 (95 % confidence interval [CI]: 0.6331 to 0.8476).  The ASPECTS on the venous phase CTP-SI revealed a significant correlation with the ASPECTS on CBV, the Pearson correlation coefficient was 0.92 (p < 0.001), and the concordance correlation coefficient was 0.8880 (95 % CI: 0.8148 to 0.9334).  Significant differences were shown between the arterial phase CTP-SI/ venous phase CTP-SI (p < 0.001) and CBF/CBV (p < 0.001).  The authors concluded that this study provides preliminary evidence that the arterial phase and venous phase CTP-SI mis-match model could possibly be applied to ischemic regions in the acute stage of stroke to determine penumbra and infarct core.

In a prospective, pilot series, Schichor et al (2010) analyzed the feasibility of intra-operative CTA and brain perfusion mapping using an up-to-date multi-slice CT scanner.  A total of 10 patients with unruptured aneurysms underwent intra-operative scanning with a 40-slice sliding-gantry CT scanner.  Multi-modal CT acquisition was obtained in 8 patients consisting of dynamic CTP scanning followed by intra-cranial CTA.  Two of these patients underwent CTA and CTP 2 times in 1 session as a control after re-positioning cerebral aneurysm clips.  In another 2 patients, CTA was performed alone.  The quality of all imaging obtained was assessed in a blinded consensus reading performed by an experienced neurosurgeon and an experienced neuroradiologist.  A 6-point scoring system ranging from excellent to insufficient was used for quality evaluation of CTP and CTA.  In 9 of 10 CTP data sets, the quality was rated excellent or good.  In the remaining case, the quality was rated insufficient for diagnostic evaluation due to major streak artifacts induced by the titanium pins of the head clamp.  In this particular case, the quality of the related CTA was rated good and sufficient for intra-operative decision making.  The quality of all 12 CTA data sets was rated excellent or good.  In 1 patient with an anterior communicating artery aneurysm, CTP scanning led to a re-positioning of the clip because of an ischemic pattern of the perfusion parameter maps due to clip stenosis of an artery.  The subsequent CTP scan obtained in this patient revealed an improved perfusion of the related vascular territory, and follow-up MRI showed only minor ischemia of the anterior cerebral artery territory.  The authors concluded that intra-operative CTA and CTP scanning were shown to be feasible with short acquisition time, little interference with the surgical workflow, and very good diagnostic imaging quality.  Thus, these modalities might be very helpful in vascular neurosurgery.  They stated that having demonstrated their feasibility, the impact of these methods on patients' outcomes has now to be analyzed prospectively in a larger series.

Silvennoinen et al (2010) stated that the routine diagnostic tool of acute ischemic stroke is NCCT.  Modern multi-slice CT scanners also allow functional imaging with brain perfusion and CTA.  Wider adoption of thrombolytic therapy in acute stroke have advanced their application.  Computed tomography perfusion is fast and widely available.  It allows verification of cerebral ischemia, and may potentially assist in determining the extent of the ischemic tissue that still is salvageable with thrombolytic therapy.  Major cerebral arteries can also be visualized to detect occlusions or stenosis, which also assists in clinical decision making.  Non-contrast CT still remains the mainstay of acute stroke imaging.  Furthermore, Warren et al (2010) noted that integrated stroke imaging, including demonstration of potentially salvageable tissue with either MR perfusion/diffusion studies or CT perfusion, is increasingly likely to play a central role in future management strategies and widening of the potential therapeutic window.

Lovblad and Baird (2010) noted that over the past 10 years, there has been a parallel in progress in techniques in both diagnostic and therapeutic options for acute cerebral ischemia.  While previously only used for excluding hemorrhage, imaging now has the possibility to detect ischemia, vascular occlusion, and tissue at risk in one setting.  It also allow clinicians to monitor treatment and predict/exclude therapeutic complications.  Parallel to advances in MRI of stroke, CT has markedly improved over the past 10 years as a result of the development of faster CT scanners, which allow clinicians to acquire CTP or CTA in a reliable way. Computed tomography can detect many signs that might help clinicians detect impending signs of massive infarction, but there is still a lack of experience in the use of these techniques to guide possible therapy.

In a pilot study, Michel and colleagues (2012) examined the feasibility of a trial of perfusion computed tomography (PCT)-guided thrombolysis in patients with ischemic tissue at risk of infarction and unknown stroke onset.  Patients with a supra-tentorial stroke of unknown onset in the middle cerebral artery territory and significant volume of at-risk tissue on PCT were randomized to intravenous thrombolysis with alteplase (0.9 mg/kg) or placebo.  Feasibility endpoints were randomization and blinded treatment of patients within 2 hrs after hospital arrival, and the correct application (estimation) of the perfusion imaging criteria.  At baseline, there was a trend towards older age [69.5 (57 to 78) versus 49 (44 to 78) years] in the thrombolysis group (n = 6) compared to placebo (n = 6).  Regarding feasibility, hospital arrival to treatment delay was above the allowed 2 hrs in 3 patients (25 %).  There were 2 protocol violations (17 %) regarding PCT, both under-estimating the predicted infarct in patients randomized in the placebo group.  No symptomatic hemorrhage or death occurred during the first 7 days.  Three of the 4 (75 %) and 1 of the 5 (20 %) patients were re-canalized in the thrombolysis and placebo group respectively.  The volume of non-infarcted at-risk tissue was 84 (44 to 206) cm(3) in the treatment arm and 29 (8 to 105) cm(3) in the placebo arm.  The authors concluded that this pilot study shoeds that a randomized PCT-guided thrombolysis trial in patients with stroke of unknown onset may be feasible if issues such as treatment delays and reliable identification of tissue at risk of infarction tissue are resolved.  Safety and efficiency of such an approach need to be established.

Recent guidelines regarding CT perfusion for evaluating acute cerebral ischema included the following:

  • The European Federation of Neurological Societies' guideline on neuroimaging in acute stroke (Masdeu et al, 2006) stated that perfusion CT is helpful when MRI is not available and for the study of stroke patients for whom MRI is contraindicated (class IV, level GCPP).  Class IV: Any design where test is not applied in blinded evaluation or evidence provided by expert opinion alone or in descriptive case series (without controls).  Good clinical practice point (GCPP) supported primarily by expert opinion.
  • The American Heart Association, American Stroke Association Stroke Council, and Clinical Cardiology Council's guidelines for the early management of adults with ischemic stroke (Adams et al, 2007) stated multi-modal CT and MRI may provide additional information that will improve diagnosis of ischemic stroke (Class I, Level of Evidence A).  Class I Conditions for which there is evidence for and/or general agreement that the procedure or treatment is useful and effective.  Level of Evidence "A" Data derived from multiple randomized clinical trials
  • The American Association of Neuroscience Nurses' guide to the care of the hospitalized patient with ischemic stroke (2008) stated that the use of CT angiography (CTA) and CT perfusion (CTP) is growing in popularity and usefulness for acute stroke management.  CTA/CTP imaging at admission assists in evaluating the cervical vessels and determining infarct localization and site of vascular occlusion.  As this technology improves and is studied further, the use of CTA and CTP may increase.
  • The American College of Radiology's Appropriateness Criteria on cerebrovascular disease (De La Paz et al, 2010) noted that advanced CTP methods improve sensitivity to acute ischemia and are increasingly used with CTA to evaluate acute stroke as a supplement to the non-contrast head CT.
  • The Institute for Clinical Systems Improvement's guideline on the diagnosis and treatment of ischemic stroke (2010) stated that although ischemic brain swelling typically peaks between 3 and 5 days after stroke onset, marked early swelling (in the first 24 to 48 hours) causing mass effect and tissue shift can occur in the most severe cases ("malignant" ischemic brain edema).  Low attenuation changes exceeding 2/3 of the middle cerebral artery territory and large areas of hypoperfusion on perfusion scans (CT perfusion or MRI perfusion) on initial radiological evaluation are associated with high risk of developing malignant brain edema.  Patients with these features should be strictly monitored with serial neurological examinations, ideally in a stroke unit.  Repeating CT scan of the brain to evaluate for progression of regional mass effect is indicated if the patient develops any signs of neurological deterioration.  The value of serial CT scans of the brain in the absence of clinical changes remains to be established.

Shibamoto et al (2012) reported the case of a 31-year old male presenting with intra-cranial hemorrhage manifesting as deep coma and anisocoria underwent immediate emergency surgery.  Three-dimensional computed tomography (CT) angiography revealed stenosis of the right middle cerebral artery (MCA) and perfusion CT immediately after the surgery suggested severe hypo-perfusion in the right MCA territory.  Post-operative angiography demonstrated right unilateral moyamoya disease.  These researchers predicted that brain edema and intra-cranial pressure (ICP) elevation occurring after the hemorrhage might result in cerebral infarction.  Hyper-osmotic drugs were contraindicated by dehydration.  Therefore, therapeutic hypothermia was induced that controlled the ICP.  These researchers considered that the increased ICP, dehydration, vasospasm, and shrinkage of the ruptured vessel comprised the pathogenesis of acute cerebral ischemia after intra-cranial bleeding.  They stated that cerebral hemodynamics should be evaluated during the acute phase of cerebral hemorrhage to prevent subsequent cerebral infarction.

Furthermore, an UpToDate review on “Moyamoya disease: Prognosis and treatment” (Suwanwela, 2013) stated that “Preoperative cerebral angiography with bilateral injections of the internal and external carotid arteries and vertebral arteries is generally recommended to evaluate the sites of occlusion and collateral circulation and to identify donor vessels.  Cerebral perfusion and autoregulation studies using xenon CT, perfusion CT, and/or perfusion MRI, with or without acetazolamide, may also be helpful in evaluating cerebrovascular reserve".

While CT perfusion may be useful for the evaluation of moyamoya disease patients who present with acute cerebral ischemic attacks, there is inadequate evidence to support CT perfusion for monitoring of the disease.

Cremers et al (2014) stated that delayed cerebral ischemia (DCI) is at presentation a diagnosis per exclusion, and can only be confirmed with follow-up imaging. For treatment of DCI, a diagnostic tool is needed. These researchers performed a systematic review to evaluate the value of CTP in the prediction and diagnosis of DCI. They searched PubMed, Embase, and Cochrane databases to identify studies on the relationship between CTP and DCI. A total of 11 studies (570 patients) were included. On admission, CBF, CBV, mean transit time (MTT), and time to peak (TTP) did not differ between patients who did and did not develop DCI. In the DCI time-window (4 to 14 days after SAH), DCI was associated with a decreased CBF (pooled mean difference -11.9 ml/100 g per minute (95 % CI: -15.2 to -8.6)) and an increased MTT (pooled mean difference 1.5 seconds (0.9 to 2.2)). Cerebral blood volume did not differ and TTP was rarely reported. Perfusion thresholds reported in studies were comparable, although the corresponding test characteristics were moderate and differed between studies. The authors concluded that CTP can be used in the diagnosis but not in the prediction of DCI. They stated that there is a need to standardize the method for measuring perfusion with CTP after SAH, and optimize and validate perfusion thresholds.

Mir et al (2014) stated that DCI is a significant cause of morbidity and mortality after aneurysmal SAH, leading to poor outcomes. These investigators evaluated the usefulness of CTP in determining DCI in patients with aneurysmal SAH. They conducted a systematic review evaluating studies that assessed CTP in patients with aneurysmal SAH for determining DCI. Studies using any of the following definitions of DCI were included in the systematic review:
  1. new onset of clinical deterioration,
  2. cerebral infarction identified on follow-up CT or MRI, and
  3. functional disability.

A random-effects meta-analysis was performed assessing the strength of association between a positive CTP result and DCI. The systematic review identified 218 studies that met the screening criteria, of which 6 cohort studies met the inclusion criteria. These studies encompassed a total of 345 patients, with 155 (45 %) of 345 patients classified as having DCI and 190 (55 %) of 345 patients as not having DCI. Admission disease severity was comparable across all groups. Four cohort studies reported CTP test characteristics amenable to the meta-analysis. The weighted averages and ranges of the pooled sensitivity and specificity of CTP in the determination of DCI were 0.84 (0.7 to 0.95) and 0.77 (0.66 to 0.82), respectively. The pooled odds ratio of 23.14 (95 % CI: 5.87 to 91.19) indicated that patients with aneurysmal SAH with positive CTP test results were approximately 23 times more likely to experience DCI compared with patients with negative CTP test results. The authors concluded that perfusion deficits on CTP are a significant finding in determining DCI in aneurysmal SAH. They noted that this may be helpful in identifying patients with DCI before development of infarction and neurologic deficits.

Rawal et al (2015) stated that DCI is a serious complication after aneurysmal SAH. If DCI is suspected clinically, imaging methods designed to detect angiographic vasospasm or regional hypo-perfusion are often used before instituting therapy. Uncertainty in the strength of the relationship between imaged vasospasm or perfusion deficits and DCI-related outcomes raises the question of whether imaging to select patients for therapy improves outcomes in clinical DCI. These researchers performed a decision analysis using Markov models. Strategies were either to treat all patients immediately or to first undergo diagnostic testing by digital subtraction angiography or CTA to assess for angiographic vasospasm, or CTP to assess for perfusion deficits. According to current practice guidelines, treatment consisted of induced hypertension. Outcomes were survival in terms of life-years and quality-adjusted life-years. When treatment was assumed to be ineffective in non-vasospasm patients, treat all and digital subtraction angiography were equivalent strategies; when a moderate treatment effect was assumed in non-vasospasm patients, treat all became the superior strategy. Treating all patients was also superior to selecting patients for treatment via CTP. One-way sensitivity analyses demonstrated that the models were robust; 2- and 3-way sensitivity analyses with variation of disease and treatment parameters reinforced dominance of the treat all strategy. The authors concluded that imaging studies to test for the presence of angiographic vasospasm or perfusion deficits in patients with clinical DCI do not seem helpful in selecting which patients should undergo treatment and may not improve outcomes. They stated that future directions include validating these results in prospective cohort studies.

Furthermore, an UpToDate review on “Etiology, clinical manifestations, and diagnosis of aneurysmal subarachnoid hemorrhage” (Singer et al, 2015) does not mention CT perfusion as a diagnostic tool.

Confirmation of Brain Death

Brasil et al (2016) noted that several complications make the diagnosis of brain death (BD) medically challenging and a complimentary method is needed for confirmation. In this context, CTA and CTP could represent valuable alternatives; however, the reliability of CTA and CTP for confirming brain circulatory arrest remains unclear.  These investigators performed a systematic review to identify relevant studies regarding the use of CTA and CTP as ancillary tests for BD confirmation. A total of 322 patients were eligible for the meta-analysis, which exhibited 87.5 % sensitivity; CTA image evaluation protocol exhibited variations between medical institutions regarding which intra-cranial vessels should be considered to determine positive or negative test results.  The authors concluded that for patients who were previously diagnosed with BD according to clinical criteria, CTA demonstrated high sensitivity to provide radiologic confirmation.  

An UpToDate review on “Diagnosis of brain death” (Young, 2016) states that “The clinical utility of computed tomographic angiography (CTA) and computed tomographic perfusion in the evaluation of brain death is uncertain. These tests are somewhat more invasive than MRA, in that contrast injection is required.  Case reports document findings of absent cerebral circulation perfusion on CTA in patients with brain death.  However, systematic reviews of studies comparing CTA to an alternative brain death determination have concluded that the reported sensitivities are variable and appear low overall (ranging from 62 to 99 %).  The highest sensitivity was achieved when the absence of opacification of the internal cerebral veins was used as a criterion.  The absence of studies examining CTA findings in patients who are comatose but not brain dead preclude an assessment of this test’s specificity”.

CT Perfusion for Detection of Cerebral Perfusion Impairment after Aneurysmal Subarachnoid Hemorrhage

In a retrospective study, Afat and colleagues (2018) evaluated the diagnostic accuracy of low-dose volume perfusion (VP) CT compared with original VP CT regarding the detection of cerebral perfusion impairment following aneurysmal subarachnoid hemorrhage (ASH).  A total of 85 patients (mean age of 59.6 years; 62 women) with ASH and who were suspected of having cerebral vasospasm at un-enhanced CT and VP CT (tube voltage, 80 kVp; tube current-time product, 180 mAs) were included, 37 of whom underwent digital subtraction angiography (DSA) within 6 hours.  Low-dose VP CT data sets at tube current-time product of 72 mAs were retrospectively generated by validated realistic simulation.  Perfusion maps were generated from both data sets and reviewed by 2 neuro-radiologists for overall image quality, diagnostic confidence and presence and/or severity of perfusion impairment indicating vasospasm.  An interventional neuro-radiologist evaluated 16 vascular segments at DSA.  Diagnostic accuracy of low-dose VP CT was calculated with original VP CT as reference standard.  Agreement between findings of both data sets was assessed by using weighted Cohen κ and findings were correlated with DSA by using Spearman correlation.  After quantitative volumetric analysis, lesion volumes were compared on both VP CT data sets.  Low-dose VP CT yielded good ratings of image quality and diagnostic confidence and classified all patients correctly with high diagnostic accuracy (sensitivity, 99.0 %; specificity, 99.5 %) without significant differences regarding presence and/or severity of perfusion impairment between original and low-dose data sets (Z = -0.447; p = 0.655).  Findings of both data sets correlated significantly with DSA (original, r = 0.671; low-dose, r = 0.667).  Lesion volume was comparable for both data sets (relative difference, 5.9 % ± 5.1 [range of 0.2 % to 25.0 %; median of 4.0 %]) with strong correlation (r = 0.955).  The authors concluded that these findings suggested that radiation dose reduction to 40 % of original dose levels (tube current-time product, 72 mAs) may be performed in VP CT imaging of patients with ASH without compromising the diagnostic accuracy regarding detection of cerebral perfusion impairment indicating vasospasm.

In a retrospective study, Afat and colleagues (2018) examined the diagnostic accuracy of low-dose volume perfusion (VP) CT compared with original VP CT regarding the detection of cerebral perfusion impairment after ASH.  This trial included 85 patients (62 women; mean age of 59.6 years) with ASH and who were suspected of having cerebral vasospasm at unenhanced CT and VP CT (tube voltage, 80 kVp; tube current-time product, 180 mAs), 37 of whom underwent DSA within 6 hours.  Low-dose VP CT data sets at tube current-time product of 72 mAs were retrospectively generated by validated realistic simulation.  Perfusion maps were generated from both data sets and reviewed by 2 neuroradiologists for overall image quality, diagnostic confidence and presence and/or severity of perfusion impairment indicating vasospasm.  An interventional neuroradiologist evaluated 16 vascular segments at DSA.  Diagnostic accuracy of low-dose VP CT was calculated with original VP CT as reference standard.  Agreement between findings of both data sets was assessed by using weighted Cohen κ and findings were correlated with DSA by using Spearman correlation.  After quantitative volumetric analysis, lesion volumes were compared on both VP CT data sets.  Low-dose VP CT yielded good ratings of image quality and diagnostic confidence and classified all patients correctly with high diagnostic accuracy (sensitivity, 99.0 %; specificity, 99.5 %) without significant differences regarding presence and/or severity of perfusion impairment between original and low-dose data sets (Z = -0.447; p = 0.655).  Findings of both data sets correlated significantly with DSA (original, r = 0.671; low dose, r = 0.667).  Lesion volume was comparable for both data sets (relative difference, 5.9 % ± 5.1 [range of 0.2 % to 25.0 %; median of 4.0 %]) with strong correlation (r = 0.955).  The authors concluded that these findings suggested that radiation dose reduction to 40 % of original dose levels (tube current-time product, 72 mAs) may be performed in VP CT imaging of patients with ASH without compromising the diagnostic accuracy regarding detection of cerebral perfusion impairment indicating vasospasm.

The authors stated that this study had several drawbacks.  The retrospective design of this study was associated with a selection bias; and the relatively small sample size was also a limitation.  The low-dose images were simulated, and thus the lack of real low-dose images was another limitation.  The applied low-dose simulation method has recently been validated and applied in prior studies with satisfactory results.  Finally, the section thickness of CT and particularly of VP CT affected image noise, with higher noise levels in thinner sections.  In this study, these researchers used a section thickness of 10.0 mm.  Thus, these findings should be taken with caution because they cannot easily be transferred to data acquired with thinner sections; further studies regarding the interference of section thickness and radiation dose reduction should be performed.

CT Perfusion for Differentiation of High-Grade Gliomas from Low-Grade Gliomas, Lymphomas, Metastases and Abscess

Karegowda and colleagues (2017) noted that tumoral angioneogenesis and its quantification are important in predicting the tumor grade and in the management with respect to the treatment available and to assess the response to treatment and the prognosis.  It also plays major role in the growth and spread of tumors.  Thus, a need arises for non-invasive in-vivo methods to assess tumor angioneogenesis and tumor grade at the time of presentation and for monitoring the response during treatment and follow-up.  In this regard PCT can be easily added into routine CT studies to obtain such information on lesion physiology along with its morphology.  These investigators performed a prospective evaluation of the efficacy of PCT in differentiating high-grade gliomas from low-grade glioma lymphomas, metastases and abscess.  Perfusion CT was performed in 68 patients (17 high-grade gliomas, 10 low-grade gliomas, 7 lymphomas, 27 metastases and 7 abscess).  Perfusion parameters which include CBV, CBF, MTT and TTP were derived both from the lesion and the normal parenchyma and were normalized (n) by obtaining the ratio.  Statistical analysis for high-grade gliomas versus low-grade gliomas, high-grade gliomas versus lymphomas, metastases and abscess was performed.  Difference in the mean nCBV and nCBF in high-grade gliomas were statistically significant from low-grade gliomas with cut-off of greater than 3.07 for nCBV and greater than 2.08 for nCBF yielding good sensitivity and specificity.  Difference in the mean nCBV and nMTT in the lymphomas were statistically significant from high-grade gliomas (p < 0.05) with cut-off of less than 3.40 for nCBV and greater than 1.83 for nMTT yielding good sensitivity and specificity.  Difference in the mean nCBV and nMTT in the metastases were statistically significant from high-grade gliomas (p < 0.05) with cut-off of greater than 4.95 for nCBV and greater than 1.88 for nMTT yielding a fair sensitivity and specificity.  No statistical significant difference seen among the parameters in differentiating high-grade gliomas and abscess.  The author concluded that cerebral PCT added to the diagnostic accuracy when the diagnosis of a common intra-axial lesion based on morphological characters was uncertain.  Moreover, these investigators stated that the technique potentially has both clinical and research applications in evaluation of brain pathologies.

The authors stated that the main limitation of this study was the restricted slice number during acquisition of perfusion images as only 4 cm of tissue of interest could be imaged with the 64-slice CT scanner.  Thus, the whole tumor volume could not be imaged in full.  In addition, the limited region of interest might have been “non-representative” of whole tumor perfusion, especially in large and heterogeneous lesions.  Finally, a relatively small sample size for each of the conditions was another drawback of the study.

CT Perfusion Studies for Prognosis Following Severe Traumatic Brain Injury

Bendinelli and colleagues (2017) noted that in patients with severe TBI, early CTP provides additional information beyond the NCCT and may alter clinical management.  These researchers hypothesized that this information may prognosticate functional outcome.  They carried out a 5-year prospective observational study in a level-1 trauma center on consecutive severe TBI patients; CTP (obtained in conjunction with first routine NCCT) was interpreted as: abnormal, area of altered perfusion more extensive than on NCCT, and the presence of ischemia; 6 months Glasgow Outcome Scale-Extended of 4 or less was considered an unfavorable outcome.  Logistic regression analysis of CTP findings and core variables (pre-intubation Glasgow Coma Scale (GCS), Rotterdam score, base deficit, age) was conducted using Bayesian model averaging to identify the best predicting model for unfavorable outcome.  A total of 50 patients were investigated with CTP (1 excluded for the absence of TBI) [men: 80 %, median age of 35 (23 to 55), pre-hospital intubation: 7 (14.2 %); median GCS = 5 (3 to 7); median injury severity score = 29 (20 to 36); median head and neck abbreviated injury scale = 4 (4 to 5); median days in ICU = 10 (5 to 15)]; 30 (50.8 %) patients had an unfavorable outcome; GCS was a moderate predictor of unfavorable outcome (area under the curve [AUC] = 0.74), while CTP variables showed greater predictive ability (AUC for abnormal CTP = 0.92; AUC for area of altered perfusion more extensive than NCCT = 0.83; AUC for the presence of ischemia = 0.81).  The authors concluded that following severe TBI, CTP performed at the time of the 1st follow-up NCCT, is a non-invasive and extremely valuable tool for early outcome prediction.  These investigators stated that the potential impact on management and its cost-effectiveness deserves to be evaluated in large-scale studies.  Level of Evidence = III:

CT Perfusion Studies for Selection of Endovascular Therapy in Persons with Ischemic Stroke

Lansberg and associates (2017) examined the utility of CTP for selection of patients for endovascular therapy up to 18 hours after symptom onset.  These researchers conducted a multi-center cohort study of consecutive acute stroke patients scheduled to undergo endovascular therapy within 90 mins after a baseline CTP.  Patients were classified as "target mismatch" if they had a small ischemic core and a large penumbra on their baseline CTP.  Re-perfusion was defined as greater than 50 % reduction in critical hypo-perfusion between the baseline CTP and the 36-hour follow-up MRI.  Of the 201 patients enrolled, 190 patients with an adequate baseline CTP study who underwent angiography were included (mean age of 66 years, median NIH Stroke Scale [NIHSS] = 16, median time from symptom onset to endovascular therapy = 5.2 hours).  Rate of re-perfusion was 89 %.  In patients with target mismatch (n = 131), re-perfusion was associated with higher odds of favorable clinical response, defined as an improvement of greater than or equal to 8 points on the NIHSS (83 % versus 44 %; p = 0.002, adjusted odds ratio [OR] = 6.6, 95 % CI: 2.1 to 20.9).  This association did not differ between patients treated within 6 hours (OR = 6.4, 95 % CI: 1.5 to 27.8) and those treated greater than  6 hours after symptom onset (OR = 13.7, 95 % CI: 1.4 to 140).  The authors concluded that the favorable response to re-perfusion among patients with a CT target mismatch pattern was similar to that observed in the DEFUSE 2 study among patients with an MR target mismatch pattern.  They stated that these studies laid the foundation for the currently ongoing randomized controlled trial (RCT) of endovascular therapy in patients selected with either multi-modal CT or MRI (DEFUSE 3). 

The authors stated that this study had several drawbacks.  First, because CRISP was a cohort study without a control group, no definitive conclusion can be drawn regarding the effect of endovascular treatment.  The results were, however, suggestive that there may be benefit from endovascular therapy, even in the delayed time-window. Second, the very high re-perfusion rate, a tribute to the efficacy of stent-retrievers, was unexpected and limited the ability to compare outcomes between patients with and without re-perfusion.  This was particularly true among patients without a target mismatch because virtually all patients without a target mismatch (68 of 71) re-perfused.  Thus, these investigators could not draw any direct conclusions about the effect of re-perfusion among patients without target mismatch.  The DEFUSE 2 study, which showed no association between re-perfusion and good functional outcome in patients without target mismatch on MRI, suggested that there also was no (strong) association between re-perfusion and good functional outcome in patients without target mismatch on CT.  However, DEFUSE 2 was not powered to demonstrate an effect of reperfusion in patients without target mismatch.  Moreover, results from the MR CLEAN study have shown no effect modification of endovascular treatment according to CT mismatch status.  Also, patients without target mismatch form a heterogeneous population of large, small and matched lesion patients, and it was likely that the response to re-perfusion differed between these subsets.  It is therefore possible that certain patients without a CT target mismatch do benefit from re-perfusion, such as the subset of patients who had an ischemic core less than 70 ml but who were classified as non-target mismatch because of a large (greater than 100 ml) lesion with a Tmax delay greater than 10s.  Third, because the exact time of stroke onset was unknown for most patients, a sub-analysis that excluded these patients was not feasible.  Finally, while investigators were instructed not to use the perfusion maps generated by the automated CT perfusion analysis software for decision-making regarding endovascular therapy, they could use their standard of care perfusion software for this purpose.  Some patients were likely excluded from this study because they did not undergo endovascular therapy based on the results of the standard of care CT perfusion maps.  Exclusion of patients on those grounds may have occurred preferentially in patients presenting late, given that the proportion of target mismatch was higher among patients who were treated beyond 6 hours and given that patients with target mismatch had longer symptom-onset to imaging times.  While enrichment of the study population with target mismatch patients did not bias the main results of this study, the proportion of patients with target mismatch in the general stroke population was likely smaller than the 69 % observed among all patients in this study and certainly lower than the 80 % observed among patients treated after 6 hours.

Shen and colleagues (2017) compared the diagnostic accuracy of CTP, NCCT and CTA in detecting acute ischemic stroke.  These investigators searched 7 databases and screened the reference lists of the included studies.  The risk of bias in the study quality was assessed using QUADASII.  They produced paired forest plots in RevMan to show the variation of the sensitivity and specificity estimates together with their 95 % CI.  They used a hierarchical summary ROC model to summarize the sensitivity and specificity of CTP in detecting ischemic stroke.  These researchers identified 27 studies with a total of 2,168 patients.  The pooled sensitivity of CTP for acute ischemic stroke was 82 % (95 % CI: 75 to 88 %), and the specificity was 96 % (95 % CI: 89 to 99 %); CTP was more sensitive than NCCT and had a similar accuracy with CTA.  There were no statistically significant differences in the sensitivity and specificity between patients who underwent CTP within 6 hours of symptom onset and beyond 6 hours after symptom onset.  No adverse events (AEs) were reported in the included studies.  The authors concluded that CTP is more accurate than NCCT and has similar accuracy to CTA in detecting acute ischemic stroke.  However, the evidence is not strong.  These researchers also stated that there is potential benefit of using CTP to select stroke patients for treatment, but more high-quality evidence is needed to confirm this result.

The authors noted that this study had several drawbacks.  First, in the included studies, the characteristics of the patient varied, and patients in half of the studies may not be representative.  Second, some of the included studies had very small sample size, and it might have influenced the estimation accuracy.  Third, 13 studies did not report whether the investigators were blinded to the results of reference standard test and relevant clinical information, and it might have over-estimated the accuracy of CTP.  Fourth, only 8 of 27 studies had low risk of bias.  Finally, similar to other systematic reviews of the diagnostic test accuracy, the heterogeneities of the sensitivity and specificity in the included studies were high that may have impacted the reliability of the pooled results.

CT Perfusion for Differentiation of Lung Cancer From Benign Pulmonary Lesions

Huang et al (2020) stated that numerous studies have examined diagnosis of pulmonary nodules using perfusion CT; however, findings were not always consistent between studies. These investigators examined the evidence on the diagnostic value of perfusion CT for distinguishing between lung cancer and benign lesions.  They carried out a systematic literature search on lung cancer and benign pulmonary lesions performed with perfusion CT.  The searches were undertaken in English or Chinese language in Medline, PubMed, Embase, Cochrane Library, Web of Science, and China National Knowledge Infrastructure database from January 2010 to November 2018.  Standardized mean differences (SMDs) and 95 % CIs of CBV, CBF, MTT, and PS were calculated using Review Manager 5.3.  Publication bias, sensitivity, specificity, and the area under the curve (AUC) were calculated using Stata12.0.  A total of 14 studies comprising 1,032 malignant and 447 benign pulmonary lesions were analyzed.  Lung cancer had higher BV, BF, MTT, and PS values than benign lesions.  SMDs and 95 % CIs of BV, BF, MTT, and PS were 2.29 (1.43, 3.16), 0.50 (0.14, 0.86), 0.55 (0.39, 0.72), and 1.21 (0.87, 1.56), respectively.  AUC values of BV and PS were 0.92 (0.90, 0.94) and 0.83 (0.80, 0.86), respectively.  The authors concluded that CT perfusion imaging is a valuable technique for the diagnosis of pulmonary nodules.  Lung cancer had higher perfusion and permeability than benign lesions.  The evidence suggested CBV is the best surrogate marker for characterizing the blood supply, while PS has a high specificity in quantifying the vascular permeability.  Moreover, these researchers stated that although shortcomings exist in CT imaging methodologies, future in-depth investigations on low-dose perfusion imaging methods will likely lead to improved differentiation of pulmonary nodules.

The authors stated that this meta-analysis had several drawbacks.  Most of the studies included were performed in China, which may limit the applicability of this study to other countries.  Also, the number of studies concerning the differentiation between lung cancer and inflammatory masses with PS, MTT, or CBF was not large enough to perform a sub-group analysis.  Future studies with larger sample sizes, consistent imaging protocols, and a greater homogeneity of patient demographics are needed to establish credible diagnostic thresholds in the future.  Finally, relevant perfusion studies performed in MRI or PET were not compared in this meta-analysis.  The feasibility of widespread use of CT perfusion imaging for distinguishing between lung cancer and benign lesions needs further investigation.

CT Perfusion in the Prediction of Hemorrhagic Transformation and Prognosis in Acute Ischemic Stroke

Horsch et al (2018) stated that hemorrhagic transformation (HT) in acute ischemic stroke (AIS) can occur as a result of re-perfusion treatment.  While withholding treatment may be warranted in patients with increased risk of HT, prediction of HT remains difficult.  Non-linear regression analysis can be used to estimate blood-brain barrier permeability (BBBP).  These researchers identified a combination of clinical and imaging variables, including BBBP estimations, that could predict HT.  From the Dutch acute stroke study, 545 patients treated with intravenous (IV) recombinant tissue plasminogen activator (rtPA) and/or intra-arterial treatment were selected, with available admission extended CT perfusion and follow-up imaging.  Patient admission treatment characteristics and CT imaging parameters regarding occlusion site, stroke severity, and BBBP were recorded.  HT was assessed on day 3 follow-up imaging.  The association between potential predictors and HT was analyzed using uni-variate and multi-variate logistic regression.  To compare the added value of BBBP, AUCs were created from 2 models, with and without BBBP.  HT occurred in 57 patients (10 %).  In uni-variate analysis, older age (OR 1.03, 95 % CI 1.006-1.05), higher admission NIHSS (OR 1.13, 95 % CI: 1.08 to 1.18), higher clot burden (OR 1.28, 95 % CI: 1.16 to 1.41), poor collateral score (OR 3.49, 95 % CI: 1.85 to 6.58), larger Alberta Stroke Program Early CT Score cerebral blood volume deficit size (OR 1.26, 95 % CI: 1.14 to 1.38), and increased BBBP (OR 2.22, 95 % CI: 1.46 to 3.37) were associated with HT.  In multi-variate analysis with age and admission NIHSS, the addition of BBBP did not improve the AUC compared to both independent predictors alone (AUC 0.77, 95 % CI: 0.71 to 0.83).  The authors concluded that CT perfusion-derived BBBP predicted HT; however, it did not improve prediction with age and admission NIHSS.  These investigators stated that the technique of BBBP measurements needs further improvement before it can be a useful addition to decision-making in patients considered for IV-rtPA treatment.

In a systematic review and meta-analysis, Adebayo and Culpan (2020) examined the diagnostic accuracy of CT brain perfusion in the prediction of HT and patient outcome in AIS.  Electronic databases and grey literature published over the last 10 years related to healthcare and radiology were searched using the key terms: “computed tomography perfusion”, “hemorrhagic transformation”, “acute ischemic stroke”, “functional outcome” and their synonyms using both United Kingdom and American spellings.  Inclusion criteria were: sample size at least 30 patients, original research, evaluate ability of CT perfusion to predict hemorrhagic transformation, reports diagnostic accuracy or provide relevant data for a 2 × 2 contingency table, use follow-up non-contrast CT (NCCT) or MRI as reference standard.  A total of 12 studies were included in the review; studies cover a total of 808 patients.  Hemorrhagic transformation occurred in 30.2 % of patients.  Pooled sensitivity and specificity were 85.9 % (95 % CI: 65 to 97 %), 73.9 % (95 % CI: 45 to 92 %) and accuracy of 79.1 % (95 % CI: 57 to 98 %).  Pooled negative predictive value (NPV) was 92.9 % with a high false-positive (FP) rate (19.8 %), which could be explained in terms of outcome classification, acquisition artefact and CT perfusion processing algorithms.  This review examined the importance of using pre-defined threshold measurement for optimal prediction of HT, the relevance of patient pre-treatment clinical parameters to HT occurrence, the CTP parameters and the measurements that are independent predictors of HT, the significance of rtPA rather as an exacerbator of HT and the impact of both minor and major HT/parenchymal hemorrhage on patient secondary functional outcome.  The authors concluded that CT perfusion had a high sensitivity and moderately high specificity for prediction of HT in AIS.  Pre-treatment clinical decision-making requires consideration of clinical factors in addition to imaging findings.  This systematic review and meta-analysis highlighted that pre-treatment CT perfusion added to clinical confidence by predicting potential for hemorrhage, both in thrombolysed and un-thrombolysed patients, and also influenced decisions regarding alternative treatments for patients with AIS.

The authors stated that this systematic review had several drawbacks.  First, the potential for a reviewer to erroneously interpret or report studies and for methodological failures.  However, measures were taken to minimize these errors and bias by re-reading and double-checking every step of the review process and by conducting minor pilots where appropriate.  Second, publication bias cannot be excluded as only English language articles were included.  Third, majority of the selected studies were retrospective with the well-known inherent bias in such studies that may influence accuracy values.  These researchers stated that future research may also consider the cost-effectiveness of CTP against other imaging modalities.

Elsaid and colleagues (2020) noted that HT is one of the most common AEs related to AIS that affects the treatment plan and clinical outcome.  Identification of a sensitive radiological marker may influence the controversial thrombolytic decision in the setting of AIS and may at a minimum indicate more intensive monitoring or further prophylactic interventions.  These investigators summarized possible radiological biomarkers and the role of different radiological modalities including CT, MRI, angiography, and ultrasound (US) in predicting HT.  Different radiological indices of early ischemic changes, large ischemic lesion volume, severe blood flow restriction, BBB disruption, poor collaterals and high blood flow velocities have been reported to be associated with higher risk of HT.  The current levels of evidence of the available studies highlighted the role of the different CT perfusion parameters in predicting HT.  The authors concluded that further large standardized studies are recommended to compare the sensitivity and specificity of the different radiological markers combined and delineate the most reliable predictor.

Magnetic Resonance Imaging Perfusion Studies

Stroke is one of the most common causes of permanent disability and/or death in the Western world.  The majority of strokes is caused by acute ischemia as a consequence of occlusion of the cerebral artery by a clot.  The minority of strokes is related to intra-cerebral hemorrhage or other sources.  Transient ischemic attack (TIA) is defined as symptom duration of less than 24 hrs.  Time from onset of symptoms to treatment is considered to be the key variable that influences the indication of re-canalization therapy for treatment of acute brain infarction.  Early reperfusion has been reported to improve clinical outcomes, yet the majority of patients with acute stroke do not attend in time for thrombolysis, which is the only approved treatment.  To extend the time window for thrombolysis, several imaging parameters in computed tomography and magnetic resonance imaging (MRI) have been investigated.  In particular, multi-modal neuroimaging is increasingly employed in the initial evaluation and management of acute stroke patients in parallel with the expansion of therapeutic options.  Multi-modal MRI can identify the type of stroke (ischemia or hemorrhage), severity and location of the lesion, the patency of the intra-cranial vessels, the degree of cerebral perfusion, as well as the presence and size of the ischemic penumbra (tissue).  This information can be used to guide both acute and long-term treatment decisions for stroke patients (Kloska et al, 2010 ;  Warren et al, 2010; Burgess and Kidwell, 2011; Olivot and Albers, 2011).

Olivot and Albers (2011) noted that preliminary studies suggested that stroke victims with a significant penumbra estimated by the diffusion/perfusion mismatch on MRI benefit from thrombolysis beyond the currently recommended time window of 4.5 hrs.  New software programs can automatically produce reliable perfusion and diffusion maps for use in clinical practice.  Combined diffusion and perfusion MRI reveals an acute ischemic lesion in about 60 % of TIA patients.  Patients with transient symptoms and a restricted diffusion lesion on MRI are considered by the American Heart Association (AHA) scientific committee to have suffered a brain infarction and have a very high risk of early stroke recurrence.  The authors concluded multi-modal MRI provides critical real-time information about ongoing tissue injury as well as the risk of additional ischemic damage.  It is becoming an essential tool for the diagnosis, management and triage of acute TIA and brain infarction (Olivot and Albers, 2011).

Straka et al (2010) noted that diffusion-perfusion mismatch can be used to identify acute stroke patients that could benefit from re-perfusion therapies.  Early assessment of the mismatch facilitates necessary diagnosis and treatment decisions in acute stroke.  These researchers developed the RApid processing of PerfusIon and Diffusion (RAPID) for unsupervised, fully automated processing of perfusion and diffusion data for the purpose of expedited routine clinical assessment.  The RAPID system computes quantitative perfusion maps (CBV, CBF, MTT, and the time until the residue function reaches its peak [T(max)] using deconvolution of tissue and arterial signals.  Diffusion-weighted imaging/perfusion-weighted imaging (DWI/PWI) mismatch is automatically determined using infarct core segmentation of ADC maps and perfusion deficits segmented from T(max) maps.  The performance of RAPID was evaluated on 63 acute stroke cases, in which diffusion and perfusion lesion volumes were outlined by both a human reader and the RAPID system.  The correlation of outlined lesion volumes obtained from both methods was r(2) = 0.99 for DWI and r(2) = 0.96 for PWI.  For mismatch identification, RAPID showed 100 % sensitivity and 91 % specificity.  The mismatch information is made available on the hospital's PACS within 5 to 7 mins.  Results indicate that the automated system is sufficiently accurate and fast enough to be used for routine care as well as in clinical trials.

Kim et al (2010) developed fully automated software for dynamic susceptibility contrast (DSC) MR PWI to efficiently and reliably derive critical hemodynamic information for acute stroke treatment decisions.  Brain MR PWI was performed in 80 consecutive patients with acute non-lacunar ischemic stroke within 24 hrs after onset of symptom.  These studies were automatically processed to generate hemodynamic parameters that included CBF and CBV, and MTT.  To develop reliable software for PWI analysis, these investigators used computationally robust algorithms including the piecewise continuous regression method to determine bolus arrival time (BAT), log-linear curve fitting, arrival time independent de-convolution method as well as sophisticated motion correction methods.  An optimal arterial input function (AIF) search algorithm using a new artery-likelihood metric was also developed.  Anatomical locations of the automatically determined AIF were reviewed and validated.  The automatically computed BAT values were statistically compared with estimated BAT by a single observer.  In addition, gamma-variate curve-fitting errors of AIF and inter-subject variability of AIFs were analyzed.  Lastly, 2 observers independently assessed the quality and area of hypo-perfusion mismatched with restricted diffusion area from motion corrected MTT maps and compared that with TTP maps using the standard approach.  The AIF was identified within an arterial branch and enhanced areas of perfusion deficit were visualized in all evaluated cases.  Total processing time was 10.9 +/- 2.5 s (mean +/- S.D.) without motion correction and 267 +/- 80 s (mean +/- S.D.) with motion correction on a standard personal computer.  The MTT map produced with the authors' software adequately estimated brain areas with perfusion deficit and was significantly less affected by random noise of the PWI when compared with the TTP map.  Results of image quality assessment by 2 observers revealed that the MTT maps exhibited superior quality over the TTP maps (88 % good rating of MTT as compared to 68 % of TTP).  The authors' software allowed fully automated de-convolution analysis of DSC PWI using proven efficient algorithms that can be applied to acute stroke treatment decisions.

Recent guidelines regarding MRI perfusion for evaluating acute cerebral ischema included the following:

  • The European Federation of Neurological Societies' guideline on neuroimaging in acute stroke (Masdeu et al, 2006) stated that MR PWI and MR DWI are very helpful for the evaluation of patients with acute ischemic stroke (class I, level A).
  • The American Heart Association, American Stroke Association Stroke Council, and Clinical Cardiology Council's guidelines for the early management of adults with ischemic stroke (Adams et al, 2007) stated that multi-modal MRI may provide additional information that will improve diagnosis of ischemic stroke (Class I, Level of Evidence A).
  • The American College of Radiology's Appropriateness Criteria on cerebrovascular disease (De La Paz et al, 2010) noted that MR DWI are highly sensitive and specific for acute cerebral ischemia and, when combined with MR PWI, may be used to identify potentially salvageable ischemic tissue, especially in the period greater than 3 hours after symptom onset.
  • The Institute for Clinical Systems Improvement (ICSI)'s guideline on the diagnosis and treatment of ischemic stroke (ICSI, 2010) reported that MRI scans of the brain with diffusion- and susceptibility-weighted sequences are much more sensitive than CT in detecting new infarction and chronic hemorrhage as well as of equal sensitivity for acute hemorrhage.  If the patient is not having symptoms at the time of presentation, a MR DWI is preferred because diffusion-weighted sequences may identify patients at particularly high risk of early major recurrence.
  • On behalf of the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology (AAN), Schellinger et al (2010) evaluated the evidence for the use of MR DWI and MR PWI in the diagnosis of patients with acute ischemic stroke.  These investigators systematically analyzed the literature from 1966 to January 2008 to address the diagnostic and prognostic value of DWI and PWI.  Diffusion-weighted MRI is established as useful and should be considered more useful than non-contrast CT for the diagnosis of acute ischemic stroke within 12 hours of symptom onset.  Diffusion-weighted MRI should be performed for the most accurate diagnosis of acute ischemic stroke (Level A); however, the sensitivity of MR DWI for the diagnosis of ischemic stroke in a general sample of patients with possible acute stroke is not perfect.  On the basis of Class II and III evidence, baseline MR DWI volumes probably predict baseline stroke severity in anterior territory stroke (Level B) but possibly do not in vertebro-basilar artery territory stroke (Level C).  Baseline MR DWI lesion volumes probably predict (final) infarct volumes (Level B) and possibly predict early and late clinical outcome measures (Level C).  Baseline MR PWI volumes predict to a lesser degree the baseline stroke severity compared with DWI (Level C).  There is insufficient evidence to support or refute the value of MR PWI in diagnosing acute ischemic stroke.

Howard et al (2011) stated that development of treatments for acute and chronic pain conditions remains a challenge, with an unmet need for improved sensitivity and reproducibility in measuring pain in patients.  These investigators used pulsed-continuous arterial spin-labeling [pCASL], a relatively novel perfusion MRI technique, in conjunction with a commonly-used post-surgical model, to measure changes in regional cerebral blood flow [rCBF] associated with the experience of being in ongoing pain.  They demonstrated repeatable, reproducible assessment of ongoing pain that is independent of patient self-report.  In a cross-over trial design, 16 participants requiring bilateral removal of lower-jaw 3rd molars underwent pain-free pre-surgical pCASL scans.  Following extraction of either left or right tooth, repeat scans were acquired during post-operative ongoing pain.  When pain-free following surgical recovery, the pre/post-surgical scanning procedure was repeated for the remaining tooth.  Voxel-wise statistical comparison of pre and post-surgical scans was performed to reveal rCBF changes representing ongoing pain.  In addition, rCBF values in pre-defined pain and control brain regions were obtained.  Regional CBF increases (5 to 10 %) representing post-surgical ongoing pain were identified bilaterally in a network including primary and secondary somatosensory, insula and cingulate cortices, thalamus, amygdala, hippocampus, midbrain and brainstem (including trigeminal ganglion and principal-sensory nucleus), but not in a control region in visual cortex.  Regional CBF changes were reproducible, with no rCBF differences identified across scans within-session or between post-surgical pain sessions.  This was the first report of the cerebral representation of ongoing post-surgical pain without the need for exogenous tracers.  Regions of rCBF increases are plausibly associated with pain and the technique is reproducible, providing an attractive proposition for testing interventions for on-going pain that do not rely solely on patient self-report.  The authors concluded that these findings have the potential to improve the understanding of the cerebral representation of persistent painful conditions, leading to improved identification of specific patient sub-types and implementation of mechanism-based treatments.

Howard et al (2012) determined rCBF changes representing ongoing pain experienced by patients with painful osteoarthritis (OA) of the carpometacarpal (CMC) joint and examined rCBF variability across sessions.  These researchers used pCASL, a perfusion MRI technique.  The study included 16 patients with CMC OA and 17 matched controls.  Two pCASL scans and numerical rating scale (NRS) estimates of ongoing pain were acquired in each of 2 identical sessions.  Voxel-wise general linear model analyses were performed to determine rCBF differences between OA and control groups, rCBF differences between sessions within each group, and whether session-wise rCBF differences were related to variability in perceived ongoing pain.  In the OA group, rCBF increases representing ongoing pain were identified in the primary and secondary somatosensory, insula, and cingulate cortices; thalamus; amygdala; hippocampus; and dorsal midbrain/pontine tegmentum, including the peri-aqueductal gray/nucleus cuneiformis.  Session-wise rCBF differences in the OA group in the post-central, rostral/subgenual cingulate, mid/anterior insula, prefrontal, and premotor cortices were related to changes in perceived ongoing pain.  No significant session-wise rCBF differences were observed in controls.  The authors concluded that this was the first quantitative endogenous perfusion MRI study of the cerebral representation of ongoing, persistent pain due to OA.  Observed rCBF changes potentially indicate dysregulated central nervous system appraisal and modulation of pain, most likely the maladaptive neuroplastic sequelae of living with painful OA.  Moreover, the clinical value of cerebral MRI perfusion studies for evaluating persistent pain has yet to be established.

Liu and colleagues (2013) examined the effects of post-herpetic neuralgia (PHN) on resting-state brain activity utilizing ASL techniques.  Features of static and dynamic CBF were analyzed to reflect the specific brain response to PHN pain.  A total of 11 consecutive patients suffering from PHN and 11 age- and gender-matched control subjects underwent perfusion functional MRI brain scanning during the resting state.  Group comparison was conducted to detect the regions with significant changes of CBF in PHN patients.  Then these investigators chose those regions that were highly correlated with the self-reported pain intensity as "seeds" to calculate the functional connectivity of both groups.  Absolute CBF values of these regions were also compared across PHN patients and control subjects.  Significant increases in CBF of the patient group were observed in left striatum, right thalamus, left primary somatosensory cortex (S1), left insula, left amygdala, left primary somatomotor cortex, and left inferior parietal lobule.  Significant decreases in CBF were mainly located in the frontal cortex.  Regional CBF in the left caudate, left insula, left S1, and right thalamus was highly correlated with the pain intensity, and further comparison showed that the regional CBF in these regions is significantly higher in PHN groups.  Functional connectivity results demonstrated that the reward circuitry involved in striatum, prefrontal cortex, amygdala, and parahippocampal gyrus and the circuitry among striatum, thalamus, and insula were highly correlated with each element in PHN patients.  The authors stated that non-invasive brain perfusion imaging at rest may provide novel insights into the central mechanisms underlying PHN pain.

Aquino et al (2014) stated that PWI can be used to measure key aspects of tumor vascularity in-vivo and recent studies suggested that perfusion imaging may be useful in the early assessment of response to angiogenesis inhibitors.  These investigators compared Parametric Response Maps (PRMs) with the Region of Interest (ROI) approach in the analysis of tumor changes induced by bevacizumab and irinotecan in recurrent glioblastomas (rGBM), and evaluated if changes in tumor blood volume measured by perfusion MRI may predict clinical outcome.  A total of 42 rGBM patients with KPS greater than or equal to 50 were treated until progression, as defined by MRI with Response Assessment in Neuro-Oncology (RANO) criteria.  Relative CBV variation after 8 weeks of treatment was calculated through semi-automatic ROI placement in the same anatomic region as in baseline.  Alternatively, relative CBV variations with respect to baseline were calculated into the evolving tumor region using a voxel-by-voxel difference.  Parametric Response Maps were created showing where relative CBV significantly increased, decreased or remained unchanged.  An increased blood volume in PRM (PRMCBV+) higher than 18 % (1st quartile) after 8 weeks of treatment was associated with increased progression free survival (PFS; 24 versus 13 weeks, p = 0.045) and overall survival (OS; 38 versus 25 weeks, p = 0.016).  After 8 weeks of treatment ROI analysis showed that mean relative CBV remained elevated in non-responsive patients (4.8 ± 0.9 versus 5.1 ± 1.2, p = 0.38), whereas decreased in responsive patients (4.2 ± 1.3 versus 3.8 ± 1.6 p = 0.04), and re-increased progressively when patients approached tumor progression.  The authors concluded that these findings suggested that PRMs can provide an early marker of response to anti-angiogenic treatment and warrant further confirmation in a larger cohort of GBM patients.

Ziegelitz et al (2014) demonstrated in idiopathic normal pressure hydrocephalus (iNPH) patients by DSC MRI a reduced pre-operative CBF that correlated with the severity of clinical symptoms and predicted shunt outcome. In cortical, sub-cortical, peri-ventricular regions and along peri-and para-ventricular profiles absolute perfusion values were estimated by multi-slice DSC MRI in 21 iNPH patients and 16 age-matched healthy individuals (HI). Relative CBF, calculated with the occipital cortex as internal reference, was used for comparison between groups and for correlation analysis between regional rCBF and symptoms or outcome. Idiopathic NPH patients showed significantly decreased rCBF in the basal medial frontal cortex, hippocampus, lentiform nucleus, peri-ventricular white matter (PVWM), central grey matter and the global parenchyma as compared to HI. Idiopathic NPH patients with higher pre-operative rCBF in the PVWM performed better in clinical tests. A lower overall pre-operative function resulted in a more obvious recovery after shunt insertion. Shunt-responders had higher rCBF values in the basal medial frontal cortex than non-responders. The authors concluded that DSC MRI perfusion is a potentially useful diagnostic tool in iNPH and perfusion based criteria might be possible predictors of shunt response.

Ziegelitz et al (2015) explored relationships between clinical improvement and rCBF changes after shunt-insertion in iNPH as measured by DSC MRI. In 20 iNPH patients, rCBF was measured pre-operatively and 3 months post-operatively. Because of shunt-induced right-sided artefacts, evaluation was restricted to 12 left-sided cortical, sub-cortical, and peri-ventricular regions of interest. Correlations between rCBF and clinical symptoms were analyzed in shunt responders. In responders, the post-operative regions of interest-based rCBF increase of 2 % to 9 % was significant in the parenchyma, the hippocampus, and the anterior periventricular white matter. Perfusion improvement in the cingulus, caudate head, and thalamus correlated with decreased disturbance in 1 or more of the domains neuropsychology, gait, balance, and total performance. The authors concluded that DSC MRI can measure post-operative perfusion changes in responders; post-operative perfusion increase in some grey matter structures seems to determine the degree of clinical improvement.

Furthermore, an UpToDate review on “Normal pressure hydrocephalus” (Graff-Radford, 2015) states that “Other MRI techniques such as cine-MRI and perfusion-weighted MRI have had either mixed or negative results in the evaluation of patients with NPH. A small pilot study of magnetic resonance spectroscopy has shown findings in NPH that appear to correlate with cognitive deterioration”.

Reardon et al (2014) provided historical and scientific guidance on imaging response assessment for incorporation into clinical trials to stimulate effective and expedited drug development for recurrent glioblastoma by addressing 3 fundamental questions:
  1. What is the current validation status of imaging response assessment, and when are we confident assessing response using today's technology?
  2. What imaging technology and/or response assessment paradigms can be validated and implemented soon, and how will these technologies provide benefit?
  3. Which imaging technologies need extensive testing, and how can they be prospectively validated?

These researchers noted that assessment of T1 +/- contrast, T2/FLAIR, diffusion, and perfusion-imaging sequences are routine and provide important insight into underlying tumor activity. Nonetheless, utility of these data within and across patients, as well as across institutions, are limited by challenges in quantifying measurements accurately and lack of consistent and standardized image acquisition parameters. Currently, there exists a critical need to generate guidelines optimizing and standardizing MRI sequences for neuro-oncology patients. Additionally, more accurate differentiation of confounding factors (pseudo-progression or pseudo-response) may be valuable. The authors concluded that although promising, diffusion MRI, perfusion MRI, MR spectroscopy, and amino acid positron emission tomography (PET) require extensive standardization and validation. Moreover, they stated that additional techniques to enhance response assessment, such as digital T1 subtraction maps, warrant further investigation.

Boxerman and Ellingson (2015) noted that there exist multiple challenges associated with the current response assessment criteria for high-grade gliomas, including the uncertain role of changes in non-enhancing T2 hyper-intensity, and the phenomena of pseudo-response and pseudo-progression in the setting of anti-angiogenic and chemo-radiation therapies, respectively. Advanced physiological MRI, including diffusion and perfusion (DSC MRI and dynamic contrast-enhanced MRI) sensitive techniques for overcoming response assessment challenges, has been proposed, with their own potential advantages and inherent shortcomings. Measurement variability exists for conventional and advanced MRI techniques, necessitating the standardization of image acquisition parameters in order to establish the utility of these imaging methods in multi-center trials for high-grade gliomas. This review chapter highlighted the important features of MRI in clinical brain tumor trials, focusing on the current state of response assessment in brain tumors, advanced imaging techniques that may provide additional value for determining response, and imaging issues to be considered for multicenter trials.

Huang et al (2015) stated that glioblastoma is a devastating diagnosis with an average survival of 14 to 16 months using the current standard of care treatment. The determination of treatment response and clinical decision making is based on the accuracy of radiographic assessment. Notwithstanding, challenges exist in the neuroimaging evaluation of patients undergoing treatment for malignant glioma. Differentiating treatment response from tumor progression is problematic and currently combines long-term follow-up using standard MRI, with clinical status and corticosteroid-dependency assessments. In the clinical trial setting, treatment with gene therapy, vaccines, immunotherapy, and targeted biologicals similarly produces MRI changes mimicking disease progression. A neuroimaging method to clearly distinguish between pseudo-progression and tumor progression has unfortunately not been found to-date. With the incorporation of anti-angiogenic therapies, a further pitfall in imaging interpretation is pseudo-response. The Macdonald criteria that correlate tumor burden with contrast-enhanced imaging proved insufficient and misleading in the context of rapid blood-brain barrier normalization following anti-angiogenic treatment that is not accompanied by expected survival benefit. Even improved criteria, such as the RANO criteria, which incorporate non-enhancing disease, clinical status, and need for corticosteroid use, fall short of definitively distinguishing tumor progression, pseudo-response, and pseudo-progression. These investigators focused on advanced imaging techniques including perfusion MRI, diffusion MRI, MR spectroscopy, and new positron emission tomography imaging tracers. They discussed the relevant image analysis algorithms and interpretation methods of these promising techniques in the context of determining response and progression during treatment of glioblastoma both in the standard of care and in clinical trial context.

Filice and Crisi (2016) evaluated the differences in dynamic contrast-enhanced (DCE) MRI perfusion estimates of high-grade gliomas (HGG) due to the use of an input function (IF) obtained respectively from arterial (AIF) and venous (VIF) approaches by 2 different commercially available software applications. This prospective study includes 20 patients with pathologically confirmed diagnosis of HGG. The data source was processed by using 2 DCE dedicated commercial packages, both based on the extended Toft model, but the 1st customized to obtain input function from arterial measurement and the 2nd from sagittal sinus sampling. The quantitative parametric perfusion maps estimated from the 2 software packages were compared by means of a region of interest (ROI) analysis. The resulting input functions from venous and arterial data were also compared. No significant difference has been found between the perfusion parameters obtained with the 2 different software packages (p < 0.05). The comparison of the VIFs and AIFs obtained by the 2 packages showed no statistical differences. The authors concluded that direct comparison of DCE-MRI measurements with IF generated by means of arterial or venous waveform led to no statistical difference in quantitative metrics for evaluating HGG. Moreover, they noted that additional research involving DCE-MRI acquisition protocols and post-processing would be beneficial to further substantiate the effectiveness of venous approach as the IF method compared with arterial-based IF measurement.

Verclytte et al (2016) noted that early-onset Alzheimer's disease (EOAD) is frequently associated with atypical clinical presentations and its early detection remains a challenging issue. In this study, these researchers used arterial spin labeling (ASL), a non-invasive perfusion MRI sequence, and [18 F]-FDG-PET to detect the perfusion and metabolic features in patients with EOAD. All patients were investigated in the French reference center for young-onset dementia and were assessed by MRI, including a pseudo-continuous ASL (pCASL) sequence, and [18 F]-FDG-PET. Quantitative analyses and inter-modality comparison with correlation analysis were made after data processing including correction of partial volume effects, cortical projection, and specific intensity normalization. These investigators prospectively included 37 patients with EOAD with a mean age of 58.3 years. The areas of most severe hypo-perfusion detected with ASL were located in the parietal lobes, the pre-cuneus, the right posterior cingulate cortex, and the frontal lobes (p < 0.05). The areas of lowest glucose metabolism detected by [18 F]-FDG-PET were identified in the temporo-parietal cortex and the pre-cuneus (p < 0.05). Hypo-metabolic regions were more extensive than hypo-perfused regions on ASL maps whereas ASL highlighted alterations in the frontal lobes without apparent hypo-metabolism on [18 F]-FDG-PET maps. The authors concluded that ASL and [18 F]-FDG-PET detected pathological areas of similar distribution mainly located in the inferior parietal lobules and local zones in the temporal cortex in patients with EOAD. They stated that the findings of this preliminary study showed that ASL and [18 F]-FDG-PET may have a complementary role in combination with structural MRI for the assessment of suspected EOAD.

Blauwblomme et al (2015) noted that ASL-MRI is becoming a routinely used sequence for ischemic strokes, as it quantifies CBF without the need for contrast injection. As brain arterio-venous malformations (AVMs) are high-flow vascular abnormalities, increased CBF can be identified inside the nidus or draining veins. These researchers analyzed the relevance of ASL-MRI in the diagnosis and follow-up of children with brain AVM. They performed a retrospective analysis of 21 patients who had undergone DSA and pseudo-continuous ASL-MRI for the diagnosis or follow-up of brain AVM after radiosurgery or embolization. They compared the AVM nidus location between ASL-MRI and 3D contrast-enhanced T1 MRI, as well as the CBF values obtained in the nidus (CBFnidus) and the normal cortex (CBFcortex) before and after treatment. The ASL-MRI correctly demonstrated the nidus location in all cases. Nidal perfusion (mean CBFnidus of 137.7 ml/100 mg/min) was significantly higher than perfusion in the contralateral normal cortex (mean CBFcortex of 58.6 ml/100 mg/min; p < 0.0001, Mann-Whitney test). Among 3 patients followed-up after embolization, a reduction in both AVM size and CBF values was noted. Among 5 patients followed-up after radiosurgery, a reduction in the nidus size was observed, whereas CBFnidus remained higher than CBFcortex. The authors concluded that ASL-MRI revealed nidus location and patency after treatment due to its ability to demonstrate focal increased CBF values. They stated that absolute quantification of CBF values could be relevant in the follow-up of pediatric brain AVM after partial treatment, although this must be confirmed in larger prospective trials.

Innes and colleagues (2015) examined gray matter volume and concentration and cerebral perfusion in people with untreated obstructive sleep apnea (OSA) while awake. These investigators employed voxel-based morphometry to quantify gray matter concentration and volume and ASL perfusion imaging to quantify cerebral perfusion. A total of 19 people with OSA (6 females and 13 males; mean age of 56.7 years, range of 41 to 70; mean apnea hypopnea index [AHI] 18.5, range of 5.2 to 52.8) and 19 controls (13 females and 6 males; mean age of 50.0 years, range of 41 to 81). There were no differences in regional gray matter concentration or volume between participants with OSA and controls. Neither was there any difference in regional perfusion between controls and people with mild OSA (n = 11). However, compared to controls, participants with moderate-severe OSA (n = 8) had decreased perfusion (while awake) in 3 clusters. The largest cluster incorporated, bilaterally, the para-cingulate gyrus, anterior cingulate gyrus, and sub-callosal cortex, and the left putamen and left frontal orbital cortex; the 2nd cluster was right-lateralized, incorporating the posterior temporal fusiform cortex, para-hippocampal gyrus, and hippocampus; the 3rd cluster was located in the right thalamus. The authors concluded that there is decreased regional perfusion during wakefulness in participants with moderate-severe OSA, and these are in brain regions that have shown decreased regional gray matter volume in previous studies in people with severe OSA. Thus, these researchers hypothesized that cerebral perfusion changes are evident before (and possibly underlie) future structural changes. These preliminary findings need to be validated by well-designed studies.

Wang et al (2015) evaluated CBF in chronic pediatric mild traumatic brain injury (mTBI) using ASL MRI perfusion. Patients with mTBI showed lower CBF than controls in bilateral fronto-temporal regions, with no between-group cognitive differences. The authors concluded that these findings suggested ASL MRI perfusion may be useful in evaluating functional abnormalities in pediatric mTBI. These preliminary findings need to be validated by well-designed studies.

Fernndez-Seara et al (2015) stated that neurophysiological changes within the cortico-basal ganglia-thalamocortical circuits appear to be a characteristic of Parkinson's disease (PD) pathophysiology. The sub-thalamic nucleus (STN) is one of the basal ganglia components showing pathological neural activity patterns in PD. In this study, perfusion imaging data, acquired non-invasively using ASL perfusion MRI, were used to assess the resting state functional connectivity (FC) of the STN in 24 early-to-moderate PD patients and 34 age-matched healthy controls, to determine whether altered FC in the very low frequency range of the perfusion time signal occurs as a result of the disease. The results showed that the healthy STN was functionally connected with other nuclei of the basal ganglia and the thalamus, as well as with discrete cortical areas including the insular cortex and the hippocampus. In PD patients, connectivity of the STN was increased with 2 cortical areas involved in motor and cognitive processes. The authors concluded that these findings suggested that hyper-connectivity of the STN could underlie some of the motor and cognitive deficits often present even at early stages of PD. They stated that FC measures provided good discrimination between controls and patients, suggesting that ASL-derived FC metrics could be a putative PD biomarker.

Evaluation of Head and Neck Cancers

Noij and colleagues (2015) provided an extensive overview of the current state of perfusion-weighted MRI for head and neck squamous cell carcinoma (HNSCC). PubMed and Embase were searched for literature until July 2014 assessing the diagnostic and prognostic performance of perfusion-weighted MRI in HNSCC.  A total of21 diagnostic and 12 prognostic studies were included for qualitative analysis; 4 studies used a T2(∗) sequence for dynamic susceptibility (DSC)-MRI, 29 studies used T1-based sequences for dynamic contrast enhanced (DCE)-MRI.  Included studies suffered from a great deal of heterogeneity in study methods showing a wide range of diagnostic and prognostic performance.  Thus, these researchers could not perform any useful meta-analysis.  Perfusion-weighted MRI showed potential in some aspects of diagnosing HNSCC and predicting prognosis; 3 studies reported significant correlations between hypoxia and tumor heterogeneity in perfusion parameters (absolute correlation coefficient |ρ|>0.6, p < 0.05); 2 studies reported synergy between perfusion-weighted MRI and PET parameters; 4 studies showed a promising role for response prediction early after the start of chemo-radiotherapy.  In 2 studies perfusion-weighted MRI was useful in the detection of residual disease.  The authors concluded that more research with uniform study and analysis protocols with larger sample sizes are needed before perfusion-weighted MRI can be used in clinical practice.

Differentiation of Radiation-Induced Necrosis from Recurrent Brain Tumor

In a meta-analysis, Chuang and associates (2016) examined roles of several metabolites in differentiating recurrent tumor from necrosis in patients with brain tumors using MR perfusion and spectroscopy. Medline, Cochrane, Embase, and Google Scholar were searched for studies using perfusion MRI and/or MR spectroscopy published up to March 4, 2015 which differentiated between recurrent tumor versus necrosis in patients with primary brain tumors or brain metastasis.  Only 2-armed, prospective or retrospective studies were included.  A meta-analysis was performed on the difference in relative cerebral blood volume (rCBV), ratios of choline/creatine (Cho/Cr) and/or choline/N-acetyl aspartate (Cho/NAA) between participants undergoing MRI evaluation. A χ2-based test of homogeneity was performed using Cochran's Q statistic and I2.  Of 397 patients in 13 studies who were analyzed, the majority had tumor recurrence.  As there was evidence of heterogeneity among 10 of the studies which used rCBV for evaluation (Q statistic = 31.634, I2 = 97.11 %, p < 0.0001) a random-effects analysis was applied.  The pooled difference in means (2.18, 95 % CI: 0.85 to 3.50) indicated that the average rCBV in a contrast-enhancing lesion was significantly higher in tumor recurrence compared with radiation injury (p = 0.001).  Based on a fixed-effect model of analysis encompassing the 6 studies which used Cho/Cr ratios for evaluation (Q statistic = 8.388, I2 = 40.39 %, p = 0.137), the pooled difference in means (0.77, 95 % CI: 0.57 to 0.98) of the average Cho/Cr ratio was significantly higher in tumor recurrence than in tumor necrosis (p = 0.001).  There was significant difference in ratios of Cho to NAA between recurrent tumor and necrosis (1.02, 95 % CI: 0.03 to 2.00, p = 0.044).  The authors concluded that MR spectroscopy and MR perfusion using Cho/NAA and Cho/Cr ratios and rCBV may increase the accuracy of differentiating necrosis from recurrent tumor in patients with primary brain tumors or metastases.

This study had several drawbacks including the limited number of studies available for the meta-analysis.  In addition, the operators/observers who evaluated rCBV and other MR spectroscopy data might not be blinded to other clinical data.  The MR spectroscopy parameters used across different studies were not consistent, and different studies used different cut-off values of metabolites for comparison.  The authors stated that future studies using multi-voxel spectroscopy may be needed to determine cut-off values for metabolite ratios.  Delayed radiation effects can have a long latency period, as already discussed, and may skew MR spectroscopy results.  The sensitivity of perfusion imaging to artifacts is another drawback.  Finally, there may have been a selection bias with regards to the studies chosen for the meta-analysis.

An UpToDate review on “Delayed complications of cranial irradiation” (Dietrich et al, 2016) states that “Differentiating recurrent tumor from radiation necrosis can be very difficult by imaging. Conventional MRI typically shows a contrast-enhancing mass lesion with central necrosis and reactive edema within or immediately adjacent to the site of the original tumor and/or the site of highest dose of radiation.  These imaging features are entirely overlapping with the radiographic appearance of high-grade primary brain tumors and brain metastases, and therefore image interpretation can be challenging …. Other imaging modalities have been investigated in an attempt to differentiate radiation necrosis from active tumor, however, no single imaging modality has proven to be sufficiently specific to establish a diagnosis.  Perfusion-weighted MRI may show decreased cerebral blood volume (CBV) associated with radiation necrosis, whereas active tumor is more likely to be associated with increased CBV.  Restricted diffusion on diffusion-weighted MRI suggests active tumor.  A high lipid peak on MR spectroscopy suggests necrosis.  Increased uptake with FDG or methionine PET or thallium chloride-201 SPECT all suggest tumor, whereas lack of uptake is more suggestive of necrosis.  Ultimately, biopsy of the suspicious lesion may be required for a definitive diagnosis, particularly in patients who are symptomatic and have worsening imaging findings over time”.

In a systematic review and meta-analysis, Patel and colleagues (2017) examined if dynamic susceptibility contrast-enhanced (DSC) and dynamic contrast enhanced (DCE) perfusion-weighted imaging (PWI) metrics can effectively differentiate between recurrent tumor and post-treatment changes within the enhancing signal abnormality on conventional MRI.  These researchers performed a comprehensive literature search for studies evaluating PWI-based differentiation of recurrent tumor and post-treatment changes in patients with high-grade gliomas (WHO grades III and IV).  Only studies published in the "temozolomide era" beginning in 2005 were included.  Summary estimates of diagnostic accuracy were obtained by using a random-effects model.  Of 1581 abstracts screened, 28 articles were included.  The pooled sensitivities and specificities of each study's best performing parameter were 90 % and 88 % (95 % CI: 0.85 to 0.94; 0.83 to 0.92) and 89 % and 85 % (95 % CI: 0.78 to 0.96; 0.77 to 0.91) for DSC and DCE, respectively.  The pooled sensitivities and specificities for detecting tumor recurrence using the 2 most commonly evaluated parameters, mean relative cerebral blood volume (threshold range of 0.9 to 2.15) and maximum relative cerebral blood volume (threshold range of 1.49 to 3.1), were 88 % and 88 % (95 % CI: 0.81 to 0.94; 0.78 to 0.95) and 93 % and 76 % (95 % CI: 0.86 to 0.98; 0.66 to 0.85), respectively.  The authors concluded that PWI-derived thresholds separating viable tumor from treatment changes demonstrated relatively good accuracy in individual studies.  However, because of significant variability in optimal reported thresholds and other limitations in the existing body of literature, further investigation and standardization is needed before implementing any particular quantitative PWI strategy across institutions.

Identification of New Infarcts Following Ischemic Injury

Wardlaw and associates (2014) stated that patients with transient ischemic attack (TIA) or minor stroke need rapid treatment of risk factors to prevent recurrent stroke.  ABCD2 score or MR DWI may help assessment and treatment.  These researchers examined if MR DWI is cost-effective in stroke prevention compared with CT brain scanning in all patients, in specific subgroups or as “1-stop” brain-carotid imaging?  Data sources included published literature; stroke registries, audit and randomized clinical trials; national databases; survey of UK clinical and imaging services for stroke; expert opinion.  These investigators performed systematic reviews and meta-analyses of published/unpublished data.  Review methods used were decision-analytic model of stroke prevention including on a 20-year time horizon including 9 representative imaging scenarios.  The pooled recurrent stroke rate after TIA (53 studies, 30,558 patients) was 5.2 % [95 % CI: 3.9 % to 5.9 %] by 7 days, and 6.7 % (5.2 % to 8.7 %) at 90 days.  ABCD2 score did not identify patients with key stroke causes or identify mimics: 66 % of specialist-diagnosed true TIAs and 35 to 41 % of mimics had an ABCD2 score of greater than or equal to 4; 20 % of true TIAs with ABCD2 score of less than 4 had key risk factors.  MR DWI (45 studies, 9,078 patients) showed an acute ischemic lesion in 34.3 % (95 % CI: 30.5 % to 38.4 %) of TIA, 69 % of minor stroke patients, i.e.. 2/3 of TIA patients were DWI-negative.  TIA mimics (16 studies, 14,542 patients) made up 40 to 45 % of patients attending clinics.  UK survey (45 % response) showed most secondary prevention started prior to clinic, 85 % of primary brain imaging was same-day CT; 51 to 54 % of patients had MR, mostly additional to CT, on average 1 week later; 55 % omitted blood-sensitive MR sequences.  Compared with “CT scan all patients” MR was more expensive and no more cost-effective, except for patients presenting at greater than 1 week after symptoms to diagnose hemorrhage; strategies that triaged patients with low ABCD2 scores for slow investigation or treated DWI-negative patients as non-TIA/minor stroke prevented fewer strokes and increased costs; “1-stop” CT/MR angiographic-plus-brain imaging was not cost-effective.  The authors concluded that MR DWI was not cost-effective for secondary stroke prevention; MR was most helpful in patients presenting at greater than 1 week after symptoms if blood-sensitive sequences were used.  They stated that ABCD2 score was unlikely to facilitate patient triage by non-stroke specialists; rapid specialist assessment, CT brain scanning and identification of serious underlying stroke causes was the most cost-effective stroke prevention strategy.  The main drawbacks of this analysis were: data on sensitivity/specificity of MR in TIA/minor stroke, stroke costs, prognosis of TIA mimics and accuracy of ABCD2 score by non-specialists were sparse or absent; all analysis had substantial heterogeneity.

In a proof-of-concept study, Lee and colleagues (2017) examined the relationship between acute PWI lesions occurring within the first hours after a TIA or a minor brain infarction (BI) and the incidence of new BI detected on a systematic MRI at 1 week.  Consecutive patients who experienced a TIA or BI with a neurologic deficit that lasted less than 24 hours, did not receive any re-vascularization therapy (thrombolysis/thrombectomy), and underwent DWI/PWI at baseline and fluid-attenuated inversion recovery (FLAIR)/DWI 1 week after symptom onset were enrolled.  Investigators blinded to clinical information independently assessed the presence of acute ischemic lesions on baseline DWI/PWI and follow-up DWI and FLAIR.  Baseline and follow-up MRIs were then compared to determine the occurrence and location of new infarctions.  A total of 64 patients met the inclusion criteria.  Median (IQR) ABCD2 score was 4 (3 to 5).  Median delay from onset to baseline and follow-up MRI was 5 (2 to 10) hours and 6 (5 to 7) days, respectively.  MRI revealed an acute ischemic lesion on DWI and/or PWI in 38 patients; 9 patients (14 %) had a new infarction on follow-up MRI.  Each had a PWI and 4 had a DWI lesion on baseline MRI.  All new BIs except 1 were asymptomatic and in the same location as the acute PWI lesion.  The authors concluded that these findings showed that 30 % of the acute focal PWI lesions detected after a TIA were associated with a new BI at 1 week; and these new BIs may result from the progression of the initial ischemic injury.

The main drawback of this study was: enrolled patients were initially triaged as vascular emergencies and admitted for a week in a stroke unit where they received state-of-the-art prevention management.  Thus, this small cohort of highly selected patients did not reflect the patients with TIA or BI with transient neurologic symptoms routinely evaluated in a TIA clinic or stroke unit.  Because of this selection bias, the rate of positive MRI (59 %) was twice as high than the rate usually observed in TIA cohorts, while the rate of symptomatic recurrence was relatively low.  Thus, the yield of PWI imaging to identify patients with TIA who are at high risk of experiencing debilitating infarction remains to be tested in a large prospective study.

Magnetic Resonance Perfusion for Differentiation of Glioma Recurrence from Pseudo-Progression

In a meta-analysis, Wan and colleagues (2017) evaluated the diagnostic accuracy of perfusion MRI as a method for differentiating glioma recurrence from pseudo-progression.  The PubMed, Embase, Cochrane Library, and Chinese Biomedical databases were searched comprehensively for relevant studies up to August 3, 2016 according to specific inclusion and exclusion criteria.  The quality of the included studies was assessed according to the quality assessment of diagnostic accuracy studies (QUADAS-2).  After performing heterogeneity and threshold effect tests, pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio (OR) were calculated.  Publication bias was evaluated visually by a funnel plot and quantitatively using Deek funnel plot asymmetry test.  The area under the summary receiver operating characteristic curve was calculated to demonstrate the diagnostic performance of perfusion MRI.  A total of 11 studies covering 416 patients and 418 lesions were included in this meta-analysis.  The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic OR were 0.88 (95 % CI: 0.84 to 0.92), 0.77 (95 % CI: 0.69 to 0.84), 3.93 (95 % CI: 2.83 to 5.46), 0.16 (95 % CI: 0.11 to 0.22), and 27.17 (95 % CI: 14.96 to 49.35), respectively.  The area under the summary receiver operating characteristic curve was 0.8899.  There was no notable publication bias.  Sensitivity analysis showed that the meta-analysis results were stable and credible.  The authors concluded that rCBV significantly improved the diagnostic performance of glioma recurrence compared with conventional T1- and T2-weighted imaging, and contrast-enhanced MRI.  The threshold value, rCBV, had moderately high diagnostic accuracy for differentiating glioma recurrence from pseudo-progression.  Moreover, they stated that due to the drawbacks addressed below, additional studies with large sample sizes and standardized methodology are needed to achieve a more robust and credible result.  Perfusion MRI combined with other imaging modalities such as diffusion MRI, magnetic resonance spectroscopy (MRS), SPECT, and PET should be researched further for introduction into routine clinical practice.

The authors stated that this meta-analysis had several drawbacks.  First, during treatment, the appearance of telangiectasis, an aneurysm, or vascular elongation may also cause an increase in rCBV.  Meanwhile, micro-bleeding during radiation treatment can result in a decrease in rCBV in tumor recurrence.  Thus, treatment-related changes could interfere with the real rCBV baseline.  Second, methodological differences limited consistency in the included studies.  The rCBV could be influenced by non-standardized procedures.  Although the authors excluded the influence of arterial spin labeling (ASL) technical factors, different MRI equipment, brands, field strength, scan parameters, therapy methods, frequency, and time intervals after treatment may lead to different results.  Third, for various grades of gliomas, both histopathology and follow-up MRI were the standard diagnostic methods.  Fourth, only English and Chinese language literatures were included in this meta-analysis, which might have resulted in missing some articles and induced potential publication bias.  Finally, the included studies were mostly retrospective in design except for one that was prospective.

Magnetic Resonance Perfusion for Differentiation of High-Grade Glioma from Primary Central Nervous System Lymphoma

In a meta-analysis, Xu and colleagues (2017) evaluated the performance of MR perfusion-weighted imaging (PWI) in differentiating HGG from primary central nervous system lymphoma (PCNSL).  The heterogeneity and threshold effect were evaluated, and the sensitivity (SEN), specificity (SPE) and areas under summary receiver operating characteristic curve (SROC) were calculated.  A total of 14 studies (598 participants) were included in this meta-analysis.  The results indicated that PWI had a high level of accuracy (AUC = 0.9415) for differentiating HGG from PCNSL by using the best parameter from each study.  The dynamic susceptibility-contrast (DSC) technique might be an optimal index for distinguishing HGGs from PCNSLs (AUC = 0.9812).  Furthermore, the DSC had the best sensitivity 0.963 (95 % CI: 0.924 to 0.986), whereas the ASL displayed the best specificity 0.896 (95 % CI: 0.781 to 0.963) among those techniques.  The authors concluded that the variability of the optimal thresholds from the included studies suggested that further evaluation and standardization are needed before the techniques can be extensively clinically used.

The authors stated that this meta-analysis had several drawbacks.  First, most of the included studies adopted multiple and different parameters to evaluate the performance of the MR perfusion; therefore, the optimal parameter and threshold value remained difficult to identify due to the highly variable proposed cutoff values, and the conclusion drawn from each study was potentially valuable only as a general guide.  Further evaluation and standardization of the techniques and post-processing methods are needed before the techniques can be extensively clinically used.  Second, these researchers included patients who had been diagnosed with WHO grade III glioma, whereas the majority of the patients included were grade IV.  Thus, the different tumor biology and angiogenesis might have impact on the results.  Third, there was evidence of heterogeneity among the overall and DCE groups.  Factors such as different field strengths, types of techniques and post-processing methods might have contributed to this heterogeneity.  Although heterogeneity was not found in the DSC and ASL groups, there were differences among the studies, such as age, gender, study designs, parameters and MR devices.

In a systematic review and meta-analysis, Suh and colleagues (2019) evaluated the diagnostic performance of MRI for differentiating PCNSL from glioblastoma.  Ovid-Medline and Embase databases were searched to find relevant original articles up to November 25, 2018.  The search term combined synonyms for "lymphoma", "glioblastoma" and "MRI".  Patients underwent at least 1 MRI sequence including DWI, DSC, DCE, arterial spin labeling (ASL), susceptibility-weighted imaging (SWI), intravoxel incoherent motion (IVIM), and MRS using 1.5 or 3 T.  Quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies-2 tool.  Hierarchical logistic regression modeling was used to obtain pooled sensitivity and specificity.  Meta-regression was performed.  A total of 22 studies with 1,182 patients were included.  MRI sequences demonstrated high overall diagnostic performance with pooled sensitivity of 91 % (95 % CI: 87 to 93 %) and specificity of 89 % (95 % CI: 85 to 93 %).  The area under the hierarchical summary ROC was 0.92 (95 % CI: 0.90 to 0.94).  Studies using DSC or ASL showed high diagnostic performance (sensitivity of 93 % [95 % CI: 89 to 97 %] and specificity of 91 % [95 % CI: 86 to 96 %]).  Heterogeneity was only detected in specificity (I2 = 66.84 %) and magnetic field strength was revealed to be a significant factor affecting study heterogeneity.  The authors concluded that MRI showed overall high diagnostic performance for differentiating PCNSL from glioblastoma, with studies using DSC or ASL showing high diagnostic performance.  These researchers stated that MRI sequences including DSC or ASL is a potential diagnostic tool for differentiating PCNSL from glioblastoma.  Level of Evidence = III.

Magnetic Resonance Perfusion for Differentiation of Low-Grade Gliomas from High-Grade Gliomas

Abrigo and colleagues (2018) determined the diagnostic test accuracy of MR perfusion for identifying patients with primary solid and non-enhancing low-grade gliomas (LGGs; WHO Grade II) at first presentation in children and adults.  In performing the quantitative analysis for this review, patients with LGGs were considered disease-positive while patients with high-grade gliomas (HGGs) were considered disease-negative.  The search strategy used 2 concepts: glioma and the various histologies of interest; and MR perfusion.  These researchers used structured search strategies appropriate for each database searched, which included: Medline(Ovid SP), Embase (Ovid SP), and Web of Science Core Collection (Science Citation Index Expanded and Conference Proceedings Citation Index).  The most recent search for this review was run on November 9, 2016.  They also identified “grey literature” from online records of conference proceedings from the American College of Radiology, European Society of Radiology, American Society of Neuroradiology and European Society of Neuroradiology in the last 20 years.  The titles and abstracts from the search results were screened to obtain full-text articles for inclusion or exclusion.  These investigators contacted authors to clarify or obtain missing/unpublished data.  They included cross-sectional studies that performed dynamic susceptibility (DSC) or dynamic contrast-enhanced (DCE) MR perfusion or both of untreated LGGs and HGGs, and where rCBV and/or Ktrans values were reported.  They selected participants with solid and non-enhancing gliomas who underwent MR perfusion within 2 months prior to histological confirmation.  They excluded studies on participants who received radiation or chemotherapy before MR perfusion, or those without histologic confirmation.  Two review authors extracted information on study characteristics and data, and assessed the methodological quality using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool.  These researchers presented  a summary of the study characteristics and QUADAS-2 results, and rate studies as good quality when they had low risk of bias in the domains of reference standard of tissue diagnosis and flow and timing between MR perfusion and tissue diagnosis.  In the quantitative analysis, LGGs were considered disease-positive, while HGGs were disease-negative.  The sensitivity refers to the proportion of LGGs detected by MR perfusion, and specificity as the proportion of detected HGGs.  These investigators constructed 2-by-2 tables with true-positives and false-negatives as the number of correctly and incorrectly diagnosed LGG, respectively, while true-negatives and false-positives were the number of correctly and incorrectly diagnosed HGG, respectively.  Meta-analysis was performed on studies with 2-by-2 tables, with further sensitivity analysis using good quality studies.  Limited data precluded regression analysis to explore heterogeneity but subgroup analysis was performed on tumor histology groups.  A total of 7 studies with small sample sizes (4 to 48) met inclusion criteria.  These were mostly conducted in university hospitals and mostly recruited adult patients.  All studies performed DSC MR perfusion and described heterogeneous acquisition and post-processing methods.  Only 1 study performed DCE MR perfusion, precluding quantitative analysis.  Using patient-level data allowed selection of individual participants relevant to the review, with generally low risks of bias for the participant selection, reference standard and flow and timing domains.  Most studies did not use a pre-specified threshold, which was considered a significant source of bias, however this did not affect quantitative analysis as these researchers adopted a common rCBV threshold of 1.75 for the review.  Concerns regarding applicability were low.  From published and unpublished data, a total of 115 participants were selected and included in the meta-analysis.  Average rCBV (range) of 83 LGGs and 32 HGGs were 1.29 (0.01 to 5.10) and 1.89 (0.30 to 6.51), respectively.  Using the widely accepted rCBV threshold of less than 1.75 to differentiate LGG from HGG, the summary sensitivity/specificity estimates were 0.83 (95 % CI: 0.66 to 0.93)/0.48 (95 % CI: 0.09 to 0.90).  Sensitivity analysis using five good quality studies yielded sensitivity/specificity of 0.80 (95 % CI: 0.61 to 0.91)/0.67 (95 % CI: 0.07 to 0.98).  Subgroup analysis for tumor histology showed sensitivity/specificity of 0.92 (95 % CI: 0.55 to 0.99)/0.42 (95 % CI: 0.02 to 0.95) in astrocytomas (6 studies, 55 participants) and 0.77 (95 % CI: 0.46 to 0.93)/0.53 (95 % CI: 0.14 to 0.88) in oligodendrogliomas + oligoastrocytomas (6 studies, 56 participants).  Data were too sparse to investigate any differences across subgroups.  The authors concluded that limited available evidence precluded reliable estimation of the performance of DSC MR perfusion-derived rCBV for the identification of grade in untreated solid and non-enhancing LGG from that of HGG.  Pooled data yielded a wide range of estimates for both sensitivity (range of 66 % to 93 % for detection of LGGs) and specificity (range of 9 % to 90 % for detection of HGGs).  Other clinical and methodological features affecting accuracy of the technique could not be determined from the limited data.  They stated that a larger sample size of both LGG and HGG, preferably using a standardized scanning approach and with an updated reference standard incorporating molecular profiles, is needed for a definite conclusion.

Okuchi and colleagues (2019) noted that T1-weighted dynamic contrast-enhanced (DCE) MRI perfusion has been broadly utilized in the evaluation of brain tumors.  These researchers examined the diagnostic accuracy of DCE-MRI in discriminating between LGGs and HGGs, between tumor recurrence and treatment-related changes, and between PCNSLs and HGGs.  These researchers carried out this study based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis of Diagnostic Test Accuracy Studies criteria.  They systematically surveyed studies evaluating the diagnostic accuracy of DCE-MRI for the afore-mentioned entities.  Meta-analysis was conducted with the use of a random effects model.  A total of 27 studies were included after screening of 2,945 possible entries.  These investigators categorized the eligible studies into 3 groups: those utilizing DCE-MRI to differentiate between HGGs and LGGs (14 studies, 546 patients), between recurrence and treatment-related changes (9 studies, 298 patients) and between PCNSLs and HGGs (5 studies, 224 patients).  The pooled sensitivity, specificity, and AUC for differentiating HGGs from LGGs were 0.93, 0.90, and 0.96, for differentiating tumor relapse from treatment-related changes were 0.88, 0.86, and 0.89, and for differentiating PCNSLs from HGGs were 0.78, 0.81, and 0.86, respectively.  The authors concluded that DCE-MRI is a promising non-invasive imaging method that has moderate or high accuracy in stratifying gliomas.  DCE-MRI showed high diagnostic accuracy in discriminating between HGGs and LGGs, and moderate diagnostic accuracy in discriminating recurrent lesions and treatment-related changes as well as PCNSLs and HGGs. Moreover, these researchers stated that significant efforts for the standardization of the acquisition parameters and the post-processing should be, however, intensely made.

The authors stated that this study had several drawbacks.  First, the analysis of studies aiming at grading gliomas revealed publication bias and the composition of the 2 groups was imbalanced.  Most analyses indicated substantial heterogeneity in terms of MR field strength, different types of MR coils, pulse sequence parameters, volume of contrast agent, injection time, which all could affect the outcomes.  Some studies performed DCE using only 50 % of contrast agent for DCE‐MRI, followed with DSC‐MRI.  Region of interest (ROI) methodology, DCE parameters, and DCE models (most studies were on the basis of the 2‐compartment Tofts‐Kermode model) also differed substantially prompting these researchers to perform sub-group analyses, which in turn indicated substantial heterogeneity.  Model‐independent analysis papers also reported different parameters on each study.  The study designs of the included studies revealed only retrospective analyses, lack of consensus and blinding in placing ROIs exposing the studies to substantial bias.  Another drawback was the small number studies included in subgroup analyses, and these researchers acknowledged that further studies are needed for adding credibility.  Furthermore, in the era of integrated histo-molecular glioma classification, there was insufficient number of studies that evaluated the diagnostic accuracy of molecular subtype using DCE‐MRI.

MR Perfusion in Diagnosing Recurrent Brain Metastases After Radiotherapy

Kwee and Kwee (2020) stated that the diagnostic performance of DSC MR perfusion in discriminating treatment-related changes from recurrence in irradiated brain metastases is currently un clear.  In a systematic review and meta-analysis, these investigators systematically reviewed the accuracy of DSC MR perfusion in diagnosing recurrent brain metastases after radiotherapy.  Medline and Embase were searched for original studies examining the accuracy of DSC MR perfusion in diagnosing recurrent brain metastases after radiotherapy.  A total of 10 studies (more than 271 metastases) were included.  Quality assessment was performed according to the Quality Assessment of Diagnostic Accuracy Studies-2 tool.  Sensitivity and specificity were pooled with a bivariate random-effects model.  Heterogeneity was assessed by a Chi-squared test.  Potential sources for heterogeneity were explored by subgroup analyses.  In 7 studies the diagnostic criterion was not pre-specified.  In 8 studies it was unclear whether the reference standard was interpreted blindly.  In 7 studies it was unclear whether DSC MR perfusion results influenced which reference standard was used.  Pooled sensitivity and specificity were 81.6 % (95 % CI: 70.6 % to 89.1 %) and 80.6 % (95 % CI: 64.2 % to 90.6 %), respectively.  There was significant heterogeneity in both sensitivity (p = 0.005) and specificity (p < 0.001).  There were no significant differences in relative diagnostic OR according to publication year, country of origin, study size, and DSC MR perfusion interpretation method (visual analysis of CBV map versus relative CBV measurement) (p > 0.2).  Due to insufficiently detailed reporting, it was not possible to examine the influence of primary tumor origin on accuracy.  The authors concluded that these findings suggested that the accuracy of DSC MR perfusion in diagnosing recurrent brain metastases after radiotherapy was fairly high.  However, these researchers stated that these findings should be interpreted with caution because of methodological quality concerns and heterogeneity between studies.  Level of Evidence = III.

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 "+":

Cerebral CT Perfusion Studies:

CPT codes covered if selection criteria are met:

0042T Cerebral perfusion analysis using computed tomography with contrast administration, including post-processing of parametric maps with determination of cerebral blood flow, cerebral blood volume, and mean transit time

Other CPT codes related to the CPB:

37195 Thrombolysis, cerebral, by intravenous infusion
61623 Endovascular temporary balloon arterial occlusion, head or neck (extracranial/intracranial) including selective catheterization of vessel to be occluded, positioning and inflation of occlusion balloon, concomitant neurological monitoring, and radiologic supervision and interpretation of all angiography required for balloon occlusion and to exclude vascular injury post occlusion
70450 - 70470 Computed tomography, head or brain; without contrast material, with contrast material(s), or without contrast material followed by contrast material(s) and further sections
70496 Computed tomographic angiography, head, with contrast material(s), including noncontrast images, if performed, and image post-processing

ICD-10 codes covered if criteria are met:

I63.00 - I63.9 Cerebral infarction
I65.01 - I65.9 Occlusion and stenosis of precerebral arteries, not resulting in cerebral infarction
I66.01 - I66.9 Occlusion and stenosis of cerebral arteries, not resulting in cerebral infarction

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

B00.4 Herpesviral encephalitis
C34.00 - C34.92 Malignant neoplasm of bronchus and lung [differential diagnosis of lung cancer]
C71.0 - C71.9 Malignant neoplasm of brain [glioma]
C79.31 Secondary malignant neoplasm of brain
C79.49 Secondary malignant neoplasm of other parts of nervous system [spinal cord]
G06.0 - G07 Intracranial and intraspinal abscess and granuloma
G45.0 - G45.9 Transient cerebral ischemic attacks and related syndromes
G46.3 - G46.8 Vascular syndromes of brain in cerebrovascular diseases
G47.33 Obstructive sleep apnea (adult) (pediatric)
G91.0 Communicating hydrocephalus
G93.82 Brain death
G91.2 (Idiopathic) normal pressure hydrocephalus
I60.00 - I62.9 Nontraumatic subarachnoid, intracerebral and other and unspecified intracranial hemorrhage
I67.1 - I67.2
I67.4 -I68.8
Other cerebrovascular diseases and cerebrovascular disorders in diseases classified elsewhere
I69.00 - I69.998 Sequelae of cerebrovascular disease
I73.89 - I73.9 Other and unspecified peripheral vascular disease
S02.0xx+ - S02.42x+
S02.60x+ - S02.92x+
Fracture of skull and facial bones [traumatic brain injury]
S06.0x0+ - S06.9x9+ Intracranial injury, excluding those with skull fracture [traumatic brain injury]
S09.10x+ - S09.11x+
S09.8xx+ - S09.90x+
Head injury, unspecified

Cerebral MRI Perfusion Studies:

No specific code

Other HCPCS codes related to the CPB:

C9257 Injection, bevacizumab, 0.25 mg
J9035 Injection, bevacizumab, 10 mg

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

C00.0 - C14.8 Malignant neoplasm of lip, oral cavity, and pharynx
C49.0 Malignant neoplasm of connective tissue and soft tissue of head, face and neck
C71.0 - C71.9 Malignant neoplasm of brain [not covered for assessment of response to angiogenesis inhibitors in persons with glioblastoma]
C72.0 - C72.9 Malignant neoplasm of spinal cord, cranial nerves and other parts of central nervous system [glioma of central nervous system]
C76.0 Malignant neoplasm of head face and neck
C81.00 - C88.9 Lymphoma
G20 Parkinson's disease
G30.0 - G30.9 Alzheimer's disease
G89.21 Chronic pain due to trauma
G89.22 Chronic post-thoracotomy pain
G89.28 Other chronic postprocedural pain
G89.29 Other chronic pain
G89.3 Neoplasm related pain (acute) (chronic)
I67.89 Other cerebrovascular disease [radiation-induced necrosis]
Q28.0 Arteriovenous malformation of precerebral vessels
Q28.2 Arteriovenous malformation of cerebral vessels
R52 Pain, unspecified
T66.xxxS Radiation sickness, unspecified, sequela [radiation-induced necrosis]
T88.7xxS Unspecified adverse effect of drug or medicament, sequela [radiation-induced necrosis]
Z13.858 Encounter for screening for other nervous system disorders [not covered for detection of early-onset Alzheimer's disease or as a putative biomarker of Parkinson's disease]

The above policy is based on the following references:

Computed Tomography Perfusion Imaging

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  20. Ding B, Ling HW, Chen KM, et al. Comparison of cerebral blood volume and permeability in preoperative grading of intracranial glioma using CT perfusion imaging. Neuroradiology. 2006;48(10):773-781.
  21. Eastwood JD, Lev MH, Azhari T, et al. CT perfusion scanning with deconvolution analysis: Pilot study in patients with acute middle cerebral artery stroke. Radiology. 2002;222(1):227-236.
  22. Eastwood JD, Lev MH, Provenzale JM. Perfusion CT with iodinated contrast material. AJR Am J Roentgenol. 2003;180(1):3-12.
  23. Eastwood JD, Provenzale JM, Hurwitz LM, Lee TY. Practical injection-rate CT perfusion imaging: Deconvolution-derived hemodynamics in a case of stroke. Neuroradiol. 2001;43(3):223-226.
  24. Elsaid N, Mustafa W, Saied A. Radiological predictors of hemorrhagic transformation after acute ischemic stroke: An evidence-based analysis. Neuroradiol J. 2020;33(2):118-133.
  25. Greenberg ED, Gold R, Reichman M, et al. Diagnostic accuracy of CT angiography and CT perfusion for cerebral vasospasm: A meta-analysis. AJNR Am J Neuroradiol. 2010;31(10):1853-1860.
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  29. Horsch AD, Bennink E, van Seeters T, et al; DUST Investigators. Computed tomography perfusion derived blood-brain barrier permeability does not yet improve prediction of hemorrhagic transformation. Cerebrovasc Dis. 2018;45(1-2):26-32.
  30. Huang C, Liang J, Lei X, et al. Diagnostic performance of perfusion computed tomography for differentiating lung cancer from benign lesions: A meta-analysis. Med Sci Monit. 2019;25:3485-3494.
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  32. Kanazawa R, Kato M, Ishikawa K, et al. Convenience of the computed tomography perfusion method for cerebral vasospasm detection after subarachnoid hemorrhage. Surg Neurol. 2007;67(6):604-611.
  33. Karegowda LH, Kadavigere R, Shenoy PM, Paruthikunnan SM. Efficacy of perfusion computed tomography (PCT) in differentiating high-grade gliomas from low Grade gliomas, lymphomas, metastases and abscess. J Clin Diagn Res. 2017;11(5):TC28-TC33.
  34. Keith CJ, Griffiths M, Petersen B, et al. Computed tomography perfusion imaging in acute stroke. Australas Radiol. 2002;46(3):221-230.
  35. Kidwell CS, Hsia AW. Imaging of the brain and cerebral vasculature in patients with suspected stroke: Advantages and disadvantages of CT and MRI. Curr Neurol Neurosci Rep. 2006;6(1):9-16.
  36. Klotz E, Konig M. Perfusion measurements of the brain: Using dynamic CT for the quantitative assessment of cerebral ischemia in acute stroke. Eur J Radiol. 1999;30(3):170-184.
  37. Koenig M, Klotz E, Luka B, et al. Perfusion CT of the brain: Diagnostic approach for early detection of ischemic stroke. Radiology. 1998;209(1):85-93.
  38. Koenig M, Kraus M, Theek C, et al. Quantitative assessment of the ischemic brain by means of perfusion-related parameters derived from perfusion CT. Stroke. 2001;32(2):431-437.
  39. Konig M. Brain perfusion CT in acute stroke: Current status. Eur J Radiol. 2003;45 Suppl 1:S11-S22.
  40. Kudo K, Sasaki M, Yamada K, et al. Differences in CT perfusion maps generated by different commercial software: Quantitative analysis by using identical source data of acute stroke patients. Radiology. 2010;254(1):200-209.
  41. Kudo K, Terae S, Katoh C, et al. Quantitative cerebral blood flow measurement with dynamic perfusion CT using the vascular-pixel elimination method: Comparison with H(2)(15)O positron emission tomography. AJNR Am J Neuroradiol. 2003;24(3):419-426.
  42. Lansberg MG, Christensen S, Kemp S, et al; CT Perfusion to Predict Response to Recanalization in Ischemic Stroke Project (CRISP) Investigators. Computed tomographic perfusion to predict response to recanalization in ischemic stroke. Ann Neurol. 2017;81(6):849-856.
  43. Latchaw RE, Yonas H, Hunter GJ, et al. Guidelines and recommendations for perfusion imaging in cerebral ischemia: A scientific statement for healthcare professionals by the writing group on perfusion imaging, from the Council on Cardiovascular Radiology of the American Heart Association. Stroke. 2003;34(4):1084-104.
  44. Man K, Kareem AM, Ahmad Alias NA, et al. Computed tomography perfusion of ischaemic stroke patients in a rural Malaysian tertiary referral centre. Singapore Med J. 2006;47(3):194-197.
  45. Marco de Lucas E, González Mandly A, Gutiérrez A, et al. Computed tomography perfusion usefulness in early imaging diagnosis of herpes simplex virus encephalitis. Acta Radiol. 2006;47(8):878-881.
  46. Masaryk T, Drayer BP, Anderson RE, et al. Cerebrovascular disease. American College of Radiology. ACR Appropriateness Criteria. Radiology. 2000;215(Suppl):415-435.
  47. Meuli RA. Imaging viable brain tissue with CT scan during acute stroke. Cerebrovasc Dis. 2004;17 Suppl 3:28-34.
  48. Michel P, Ntaios G, Reichhart M, et al. Perfusion-CT guided intravenous thrombolysis in patients with unknown-onset stroke: A randomized, double-blind, placebo-controlled, pilot feasibility trial. Neuroradiology. 2012;54(6):579-588.
  49. Miles KA. Acute cerebral stroke imaging and brain perfusion with the use of high-concentration contrast media. Eur Radiol. 2003;13 Suppl 5:M117-M120.
  50. Mir DI, Gupta A, Dunning A, et al. CT perfusion for detection of delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage: A systematic review and meta-analysis. AJNR Am J Neuroradiol. 2014;35(5):866-871.
  51. Muizelaar JP, Fatouros PP, Schroder ML. A new method for quantitative regional cerebral blood volume measurements using computed tomography. Stroke. 1997;28:1998-2005.
  52. Mundy L, Merlin T, Parrella A. Perfusion CT scanning to evaluate cerebral perfusion in patients presenting with acute ischaemic stroke symptoms. Horizon Scanning Prioritising Summary - Volume 6. Adelaide, Australia: Adelaide Health Technology Assessment (AHTA) on behalf of National Horizon Scanning Unit (HealthPACT and MSAC); 2004.
  53. Nabavi DG, Cenic A, Henderson S, et al. Perfusion mapping using computed tomography allows accurate prediction of cerebral infarction in experimental brain ischemia. Stroke. 2001;32(1):175-183.
  54. Nabavi DG, Kloska SP, Nam EM, et al. MOSAIC: Multimodal Stroke Assessment Using Computed Tomography: Novel diagnostic approach for the prediction of infarction size and clinical outcome. Stroke. 2002;33(12):2819-2826.
  55. National Institute for Health and Care Excellence (NICE). Stroke and transient ischaemic attack in over 16s: diagnosis and initial management. London, UK: NICE; July 2008.
  56. Parsons MW. Perfusion CT: Is it clinically useful? Int J Stroke. 2008;3(1):41-50.
  57. Provenzale JM, Shah K, Patel U, McCrory DC. Systematic review of CT and MR perfusion imaging for assessment of acute cerebrovascular disease. AJNR Am J Neuroradiol. 2008;29(8):1476-1482.
  58. Rawal S, Barnett C, John-Baptiste A, et al. Effectiveness of diagnostic strategies in suspected delayed cerebral ischemia: A decision analysis. Stroke. 2015;46(1):77-83.
  59. Rosand J, Eskey C, Chang Y, et al. Dynamic single-section CT demonstrates reduced cerebral blood flow in acute intracerebral hemorrhage. Cerebrovasc Dis. 2002;14(3-4):214-220.
  60. Sajjad Z. Perfusion imaging in ischaemic stroke. J Pak Med Assoc. 2008;58(7):391-394.
  61. Schellinger PD, Fiebach JB, Hacke W. Imaging-based decision making in thrombolytic therapy for ischemic stroke: Present status. Stroke. 2003;34(2):575-583.
  62. Schichor C, Rachinger W, Morhard D, et al. Intraoperative computed tomography angiography with computed tomography perfusion imaging in vascular neurosurgery: Feasibility of a new concept. J Neurosurg. 2010;112(4):722-728.
  63. Shen J, Li X, Li Y, Wu B. Comparative accuracy of CT perfusion in diagnosing acute ischemic stroke: A systematic review of 27 trials. PLoS One. 2017;12(5):e0176622.
  64. Silvennoinen H, Lindsberg PJ, Valanne L. Computed tomography perfusion (CTP) imaging in diagnostics of cerebral ischemia. Duodecim. 2010;126(1):33-39.
  65. Singer RJ, Ogilvy CS, Rordorf G. Etiology, clinical manifestations, and diagnosis of aneurysmal subarachnoid hemorrhage. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed May 2015.
  66. Sparacia G, Iaia A, Assadi B, Lagalla R. Perfusion CT in acute stroke: Predictive value of perfusion parameters in assessing tissue viability versus infarction. Radiol Med (Torino). 2007;112(1):113-122.
  67. Sviri GE, Mesiwala AH, Lewis DH, et al. Dynamic perfusion computerized tomography in cerebral vasospasm following aneurysmal subarachnoid hemorrhage: A comparison with technetium-99m-labeled ethyl cysteinate dimer-single-photon emission computerized tomography. J Neurosurg. 2006;104(3):404-410.
  68. Tan JC, Dillon WP, Liu S, et al. Systematic comparison of perfusion-CT and CT-angiography in acute stroke patients. Ann Neurol. 2007;61(6):533-543.
  69. Wang XC, Gao PY, Xue J, et al. Identification of infarct core and penumbra in acute stroke using CT perfusion source images. AJNR Am J Neuroradiol. 2010;31(1):34-39.
  70. Warren DJ, Musson R, Connolly DJ, et al. Imaging in acute ischaemic stroke: Essential for modern stroke care. Postgrad Med J. 2010;86(1017):409-418.
  71. Wintermark M, Maeder P, Verdun FR, et al. Using 80 kVp versus 120 kVp in perfusion CT measurement of regional cerebral blood flow. AJNR Am J Neuroradiol. 2000;21(10):1881-1884.
  72. Wintermark M, Thiran JP, Maeder P, et al. Simultaneous measurement of regional cerebral blood flow by perfusion CT and stable xenon CT: A validation study. AJNR Am J Neuroradiol. 2001;22(5):905-914.
  73. Xin Y, Han FG. Diagnostic accuracy of computed tomography perfusion in patients with acute stroke: A meta-analysis. J Neurol Sci. 2016;360:125-130.
  74. Young CB. Diagnosis of brain death. UpToDate [online serial]. Waltham, MA; UpToDate; reviewed May 2016.

Magnetic Resonance Imaging Perfusion Imaging

  1. Abrigo JM, Fountain DM, Provenzale JM, et al. Magnetic resonance perfusion for differentiating low-grade from high-grade gliomas at first presentation. Cochrane Database Syst Rev. 2018;1:CD011551.
  2. Adams HP Jr, del Zoppo G, Alberts MJ, et al, American Heart Association, American Stroke Association Stroke Council, Clinical Cardiology Council. Guidelines for the early management of adults with ischemic stroke: A guideline from the American Heart Association/American Stroke Association Stroke Council, Clinical Cardiology Council, Cardiovascular Radiology [trunc]. Stroke 2007;38(5):1655-1711.
  3. Aquino D, Di Stefano AL, Scotti A, et al. Parametric response maps of perfusion MRI may identify recurrent glioblastomas responsive to bevacizumab and irinotecan. PLoS One. 2014;9(3):e90535.
  4. Blauwblomme T, Naggara O, Brunelle F, et al. Arterial spin labeling magnetic resonance imaging: Toward noninvasive diagnosis and follow-up of pediatric brain arteriovenous malformations. J Neurosurg Pediatr. 2015;15(4):451-458.
  5. Boxerman JL, Ellingson BM. Response assessment and magnetic resonance imaging issues for clinical trials involving high-grade gliomas. Top Magn Reson Imaging. 2015;24(3):127-136.
  6. Burgess RE, Kidwell CS. Use of MRI in the assessment of patients with stroke. Curr Neurol Neurosci Rep. 2011;11(1):28-34
  7. Castellano A, Falini A. Progress in neuro-imaging of brain tumors. Curr Opin Oncol. 2016;28(6):484-493.
  8. Chuang MT, Liu YS, Tsai YS, et al. Differentiating radiation-induced necrosis from recurrent brain tumor using MR perfusion and spectroscopy: A meta-analysis. PLoS One. 2016;11(1):e0141438.
  9. De La Paz RL, Wippold FJ II, Cornelius RS, et al, Expert Panel on Neurologic Imaging. ACR Appropriateness Criteria cerebrovascular disease. [online publication]. Reston, VA: American College of Radiology (ACR); 2010.
  10. Dietrich J, Gondi V, Mehta M. Delayed complications of cranial irradiation. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed May 2016.
  11. Fernndez-Seara MA, Mengual E, Vidorreta M, et al. Resting state functional connectivity of the subthalamic nucleus in Parkinson's disease assessed using arterial spin-labeled perfusion fMRI. Hum Brain Mapp. 2015;36(5):1937-1950.
  12. Filice S, Crisi G. Dynamic contrast-enhanced perfusion MRI of high grade brain gliomas obtained with arterial or venous waveform input function. J Neuroimaging. 2016;26(1):124-129.
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