Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model

BACKGROUND AND PURPOSE:Malignant melanoma is an aggressive skin cancer in which brain metastases are common. Our aim was to establish and evaluate a deep learning model for fully automated detection and segmentation of brain metastases in patients with malignant melanoma using clinical routine MR imaging.MATERIALS AND METHODS:Sixty-nine patients with melanoma with a total of 135 brain metastases at initial diagnosis and available multiparametric MR imaging datasets (T1-/T2-weighted, T1-weighted gadolinium contrast-enhanced, FLAIR) were included. A previously established deep learning model architecture (3D convolutional neural network; DeepMedic) simultaneously operating on the aforementioned MR images was trained on a cohort of 55 patients with 103 metastases using 5-fold cross-validation. The efficacy of the deep learning model was evaluated using an independent test set consisting of 14 patients with 32 metastases. Manual segmentations of metastases in a voxelwise manner (T1-weighted gadolinium contrast-enhanced imaging) performed by 2 radiologists in consensus served as the ground truth.RESULTS:After training, the deep learning model detected 28 of 32 brain metastases (mean volume, 1.0 [SD, 2.4] cm³) in the test cohort correctly (sensitivity of 88%), while false-positive findings of 0.71 per scan were observed. Compared with the ground truth, automated segmentations achieved a median Dice similarity coefficient of 0.75.CONCLUSIONS:Deep learning–based automated detection and segmentation of brain metastases in malignant melanoma yields high detection and segmentation accuracy with false-positive findings of <1 per scan.

Malignant melanoma is an aggressive skin cancer associated with high mortality and morbidity rates.^1,2 Brain metastases are common in malignant melanoma,^3,4 subsequently causing potential severe neurologic impairment and worsened outcome. Therefore, it is recommended that melanoma patients with an advanced stage undergo MR imaging of the head for screening purposes to detect metastases.^5-8Owing to an increased workload of radiologists, repetitive evaluation of MR imaging scans can be tiresome, hence bearing an inherent risk of missed diagnosis for subtle lesions, with satisfaction of search effects leading to decreased sensitivity for additional lesions.^9,10 Automatization of detection could serve as an adjunct tool for lesion preselection that can support image evaluation by radiologists and clinicians.^11,12 Furthermore, automated segmentations may be used as a parameter to evaluate therapy response in oncologic follow-up imaging.^13,14 Additionally, exact lesion determination and delineation of size are required for stereotactic radiosurgery.^15,16 In clinical routine, brain lesions have to be segmented manually by the radiosurgeon. This task proves to be time-consuming, in particular if multiple metastases are present. Furthermore, manual segmentation is potentially hampered by interreader variabilities with reduced reproducibility, hence resulting in inaccuracies of lesion delineation.^17,18 In this context, accurate objective and automated segmentations of brain metastases would be highly beneficial.^17-19Recently, deep learning models (DLMs) have shown great potential in detection, segmentation and classification tasks in medical image analysis while having the potential to improve clinical workflow.^20-25 The models apply multiple processing layers that result in deep convolutional neural networks (CNNs). Training data are used to create complex feature hierarchies.^26-28 In general, a DLM includes different layers for convolution, pooling, and classification.²⁸ The required training data are supplied by manual segmentations, which usually serve as the segmentation criterion standard.^18,28,29Previous studies on brain metastases from different tumor entities have demonstrated promising results, reporting a sensitivity for automated deep learning–based detection of lesions of around 80% or higher.^17,30-32 However, the often reported relatively high number of false-positive findings questions their applicability in clinical routine.^17,30The purpose of this study was to develop and evaluate a DLM for automated detection and segmentation of brain metastases in patients with malignant melanoma using heterogeneous MR imaging data from multiple vendors and study centers.     

White Matter Hyperintensity Volume and Cerebral Perfusion in Older Individuals with Hypertension Using Arterial Spin-Labeling

BACKGROUND AND PURPOSE:White matter hyperintensities of presumed vascular origin in elderly patients with hypertension may be part of a general cerebral perfusion deficit, involving not only the white matter hyperintensities but also the surrounding normal-appearing white matter and gray matter. We aimed to study the relation between white matter hyperintensity volume and CBF and assess whether white matter hyperintensities are related to a general perfusion deficit.MATERIALS AND METHODS:In 185 participants of the Prevention of Dementia by Intensive Vascular Care trial between 72 and 80 years of age with systolic hypertension, white matter hyperintensity volume and CBF were derived from 3D FLAIR and arterial spin-labeling MR imaging, respectively. We compared white matter hyperintensity CBF, normal-appearing white matter CBF, and GM CBF across quartiles of white matter hyperintensity volume and assessed the continuous relation between these CBF estimates and white matter hyperintensity volume by using linear regression.RESULTS:Mean white matter hyperintensity CBF was markedly lower in higher quartiles of white matter hyperintensity volume, and white matter hyperintensity volume and white matter hyperintensity CBF were negatively related (standardized β = −0.248, P = .001) in linear regression. We found no difference in normal-appearing white matter or GM CBF across quartiles of white matter hyperintensity volume or any relation between white matter hyperintensity volume and normal-appearing white matter CBF (standardized β = −0.065, P = .643) or GM CBF (standardized β = −0.035, P = .382) in linear regression.CONCLUSIONS:Higher white matter hyperintensity volume in elderly individuals with hypertension was associated with lower perfusion within white matter hyperintensities, but not with lower perfusion in the surrounding normal-appearing white matter or GM. These findings suggest that white matter hyperintensities in elderly individuals with hypertension relate to local microvascular alterations rather than a general cerebral perfusion deficit.

White matter hyperintensities (WMHs) of presumed vascular origin are a common finding on brain MR imaging in elderly individuals. WMH prevalence estimates in asymptomatic older individuals range from 45% to >90%, depending on age and severity.¹ Clinically, WMHs are associated with cognitive decline, neuropsychiatric symptoms, loss of functional independence, and increased mortality.^2,3 Advanced age and hypertension are the strongest risk factors for WMHs, especially for the confluent subtype.^1–4The pathophysiology of WMHs has not yet been fully elucidated. They often appear together with other signs of cerebral small-vessel disease, an umbrella term for neuroradiologic anomalies often found in asymptomatic elderly individuals.^4,5 Histologically, confluent WMHs appear as a continuum of increasing tissue damage resembling chronic low-grade ischemia.^1,5 Therefore, WMHs may be the result of chronic low-grade white matter hypoperfusion.^1,5,6 In agreement, CBF within WMHs is lower compared with normal-appearing WM (NAWM).^7–14Whether WMHs are associated with a lower cerebral perfusion in general, also involving the surrounding NAWM and gray matter, is unclear. Some findings suggest that WMHs may relate to lower whole-brain or GM perfusion,^7,11,15,16 and WMHs have been associated with reduced blood flow velocity in the large intracranial arteries, outside the WM.^17–19 On a broader level, the association between WMHs and chronic cardiac disease also hints at a relation with general perfusion.²⁰ WMHs primarily originate in physiologically poorly perfused areas (ie, the periventricular and deep WM), explaining how even a slight cerebral perfusion deficit could provoke low-grade ischemia in those regions associated with WMHs.^21,22 Low perfusion in NAWM has also been associated with subsequent WMH development.²³ While these findings seem to suggest that WMHs are related to a perfusion deficit extending beyond the WMHs, current evidence remains circumstantial.In this study, we address the hypothesis that WMHs are associated with lower cerebral perfusion, not only within the WMHs but also in the surrounding NAWM and GM. If so, this could be a first step in determining why WMHs form in elderly individuals and toward preventive treatment. Because age and hypertension are the strongest risk factors for asymptomatic WMHs, we tested this hypothesis in a large cohort of community-dwelling elderly with hypertension, by using noninvasive arterial spin-labeling MR imaging. Arterial spin-labeling was chosen because this method of perfusion measurement allows noninvasive (ie, without contrast) MR imaging measurement of CBF within a scanning time of as little as 4 minutes, facilitating large-scale CBF measurement in research settings and eventually enabling clinical application.     

Improved Lesion Conspicuity with Contrast-Enhanced 3D T1 TSE Black-Blood Imaging in Cranial Neuritis: A Comparative Study of Contrast-Enhanced 3D T1 TSE, 3D T1 Fast-Spoiled Gradient Echo,and 3D T2 FLAIR

BACKGROUND AND PURPOSE:Contrast-enhanced 3D-turbo spin-echo (TSE) black-blood sequence has gained attention, as it suppresses signals from vessels and provides an increased contrast-noise ratio. The purpose was to investigate which among the contrast-enhanced 3D T1 TSE, 3D T1 fast-spoiled gradient echo (FSPGR), and 3D T2 FLAIR sequences can better detect cranial nerve contrast enhancement.MATERIALS AND METHODS:Patients with cranial neuritis based on clinical findings (n = 20) and control participants (n = 20) were retrospectively included in this study. All patients underwent 3T MR imaging with contrast-enhanced 3D T1 TSE, 3D T1 FSPGR, and 3D T2 FLAIR. Experienced and inexperienced reviewers independently evaluated the 3 sequences to compare their diagnostic performance and time required to reach the diagnosis. Additionally, tube phantoms containing varying concentrations of gadobutrol solution were scanned using the 3 sequences.RESULTS:For the inexperienced reader, the 3D T1 TSE sequence showed significantly higher sensitivity (80% versus 50%, P = .049; 80% versus 55%; P = .040), specificity (100% versus 65%, P = .004; 100% versus 60%; P = .001), and accuracy (90% versus 57.5%, P = .001; 90% versus 57.5%, P = .001) than the 3D T1 FSPGR and 3D T2 FLAIR sequences in patients with cranial neuritis. For the experienced reader, the 3D T1-based sequences showed significantly higher sensitivity than the 3D T2 FLAIR sequence (85% versus 30%, P < .001; 3D T1 TSE versus 3D T2 FLAIR, 85% versus 30%, P < .001; 3D T1 FSPGR versus 3D T2 FLAIR). For both readers, the 3D T1 TSE sequence showed the highest area under the curve (inexperienced reader; 0.91, experienced reader; 0.87), and time to diagnosis was significantly shorter with 3D T1 TSE than with 3D T1 FSPGR.CONCLUSIONS:The 3D T1 TSE sequence may be clinically useful in evaluating abnormal cranial nerve enhancement, especially for inexperienced readers.

Cranial neuropathies can have multiple causes, including infectious, neoplastic, inflammatory, traumatic, and idiopathic pathologies.¹ Such conditions cause disruption of the blood–nerve barrier, which is sustained by the combined actions of tight junctions in the endothelium of the endoneurial capillaries and of the inner layers of the perineurium.² Contrast-enhanced (CE) MR imaging plays an important role in the diagnosis of cranial neuritis by visualizing nerve enhancement attributed to leakage forcing spillage and accumulation of contrast material surrounded by CSF.³To date, no standard protocol has been established for evaluating cranial nerve enhancement, whereas several sequences have been proposed for detecting leptomeningeal enhancement. CE 3D T1 gradient-echo (GRE) sequences have been widely used in the clinical setting to detect leptomeningeal pathology.^4-7 Furthermore, the CE 3D FLAIR sequence is advantageous because it can sensitively detect low concentrations of gadolinium.^8,9 Recently, a CE 3D turbo spin-echo (TSE) black-blood sequence has gained attention because it provides an increased contrast to noise ratio (CNR) and suppresses diverting signals from vessels.^10-13To the best of our knowledge, no study has explored the value of CE 3D T1 TSE black-blood imaging in the diagnosis of cranial neuritis. Although the CE 3D T1 GRE sequence is generally used for the evaluation of cranial nerve enhancement,^3,14 its ability to evaluate the cisternal segment of cranial nerves is limited owing to the surrounding prominent vessel enhancement. Moreover, hyperintensities on FLAIR are also associated with various conditions, such as subarachnoid hemorrhage, sluggish collateral vessels, and supplemental oxygen, which may produce misinterpretations of the cranial nerve enhancement.¹⁵ Therefore, the aim of this study was to investigate which sequence among 3D T1 TSE, 3D T1 fast-spoiled gradient echo (FSPGR), and 3D T2 FLAIR can better detect contrast enhancement in patients with cranial neuritis.     

Development and Validation of a Deep Learning–Based Automatic Brain Segmentation and Classification Algorithm for Alzheimer Disease Using 3D T1-Weighted Volumetric Images

BACKGROUND AND PURPOSE:Limited evidence has suggested that a deep learning automatic brain segmentation and classification method, based on T1-weighted brain MR images, can predict Alzheimer disease. Our aim was to develop and validate a deep learning–based automatic brain segmentation and classification algorithm for the diagnosis of Alzheimer disease using 3D T1-weighted brain MR images.MATERIALS AND METHODS:A deep learning–based algorithm was developed using a dataset of T1-weighted brain MR images in consecutive patients with Alzheimer disease and mild cognitive impairment. We developed a 2-step algorithm using a convolutional neural network to perform brain parcellation followed by 3 classifier techniques including XGBoost for disease prediction. All classification experiments were performed using 5-fold cross-validation. The diagnostic performance of the XGBoost method was compared with logistic regression and a linear Support Vector Machine by calculating their areas under the curve for differentiating Alzheimer disease from mild cognitive impairment and mild cognitive impairment from healthy controls.RESULTS:In a total of 4 datasets, 1099, 212, 711, and 705 eligible patients were included. Compared with the linear Support Vector Machine and logistic regression, XGBoost significantly improved the prediction of Alzheimer disease (P < .001). In terms of differentiating Alzheimer disease from mild cognitive impairment, the 3 algorithms resulted in areas under the curve of 0.758–0.825. XGBoost had a sensitivity of 68% and a specificity of 70%. In terms of differentiating mild cognitive impairment from the healthy control group, the 3 algorithms resulted in areas under the curve of 0.668–0.870. XGBoost had a sensitivity of 79% and a specificity of 80%.CONCLUSIONS:The deep learning–based automatic brain segmentation and classification algorithm allowed an accurate diagnosis of Alzheimer disease using T1-weighted brain MR images. The widespread availability of T1-weighted brain MR imaging suggests that this algorithm is a promising and widely applicable method for predicting Alzheimer disease.

Alzheimer disease (AD) is the most common cause of dementia, with mild cognitive impairment (MCI) regarded as a transitional state between normal cognition and early stages of dementia.¹ Although current therapeutic and preventive options are only moderately effective, a reliable decision-making diagnostic approach is important during early stages of AD.^2,3 The guidelines of the National Institute on Aging–Alzheimer’s Association suggest that MR imaging is a supportive imaging tool in the diagnostic work-up of patients with AD and MCI.^2,3 Imaging biomarkers play an important role in the diagnosis of AD, both in the research field and in clinical practice. The identification of amyloid and the τ PET ligand provided huge advances in understanding the pathophysiologic mechanisms underlying AD and its early diagnosis, even in the preclinical or prodromal stage.^4-6 Although amyloid and τ PET are more sensitive and specific for the diagnosis of AD, they are expensive to perform, have limited availability, and require ionizing radiation, limiting their use in clinical practice. CSF amyloid and τ are also important biomarkers that could be used for AD diagnostics in the clinical research setting.^3,7-9 However, CSF AD biomarkers also have limited availability. MR imaging, however, is widely available and used in standard practice to support the diagnosis of AD and to exclude other causes of cognitive impairment, including stroke, vascular dementia, normal-pressure hydrocephalus, and inflammatory and neoplastic conditions.3D T1-weighted volumetric MR imaging is the most important MR imaging tool in the diagnosis of AD. 3D volumetry has long been used as a morphologic diagnostic tool for AD, not only as a visual assessment or manual segmentation but for semiautomatic and automatic segmentation. Examples include semiautomatic structural changes on MR imaging,¹⁰ automated hippocampal volumetry,¹¹ entorhinal cortex atrophy,¹² and changes in pineal gland volume.¹³ Although user-friendly automated segmentation algorithms were first introduced 20 years ago, evidence supporting the use of 3D volumetry in clinical practice is currently insufficient. Visual assessment requires experience, and automatic 3D volumetry requires a long acquisition time.To our knowledge, limited evidence has suggested that a deep learning automatic brain segmentation and classification method, based on T1-weighted brain MR images, can predict AD.¹⁴ Currently available algorithms have low clinical feasibility because of the long processing time for brain segmentation, and the classification algorithm based on T1-weighted brain MR images needs to be validated in a large external dataset. The purpose of this study was to develop and validate a deep learning–based automatic brain segmentation and classification algorithm for the diagnosis of AD using 3D T1-weighted brain MR images.     

Longitudinal Assessment of Enhancing Foci of Abnormal Signal Intensity in Neurofibromatosis Type 1

BACKGROUND AND PURPOSE:Patients with neurofibromatosis 1 are at increased risk of developing brain tumors, and differentiation from contrast-enhancing foci of abnormal signal intensity can be challenging. We aimed to longitudinally characterize rare, enhancing foci of abnormal signal intensity based on location and demographics.MATERIALS AND METHODS:A total of 109 MR imaging datasets from 19 consecutive patients (7 male; mean age, 8.6 years; range, 2.3–16.8 years) with neurofibromatosis 1 and a total of 23 contrast-enhancing parenchymal lesions initially classified as foci of abnormal signal intensity were included. The mean follow-up period was 6.5 years (range, 1–13.8 years). Enhancing foci of abnormal signal intensity were followed up with respect to presence, location, and volume. Linear regression analysis was performed.RESULTS:Location, mean peak volume, and decrease in enhancing volume over time of the 23 lesions were as follows: 10 splenium of the corpus callosum (295 mm³, 5 decreasing, 3 completely resolving, 2 surgical intervention for change in imaging appearance later confirmed to be gangliocytoma and astrocytoma WHO II), 1 body of the corpus callosum (44 mm³, decreasing), 2 frontal lobe white matter (32 mm³, 1 completely resolving), 3 globus pallidus (50 mm³, all completely resolving), 6 cerebellum (206 mm³, 3 decreasing, 1 completely resolving), and 1 midbrain (34 mm³). On average, splenium lesions began to decrease in size at 12.2 years, posterior fossa lesions at 17.1 years, and other locations at 9.4 years of age.CONCLUSIONS:Albeit very rare, contrast-enhancing lesions in patients with neurofibromatosis 1 may regress over time. Follow-up MR imaging aids in ascertaining regression. The development of atypical features should prompt further evaluation for underlying tumors.

Neurofibromatosis type 1 (NF-1) is an autosomal dominant tumor predisposition syndrome characterized by optic pathway gliomas, neurofibromas, skin manifestations, iris hamartomas, and bone lesions, affecting approximately 1 in 3000 individuals.^1,2 Foci of abnormal signal intensity, previously known as unidentified bright objects or neurofibromatosis bright objects of the brain, are not among the diagnostic criteria but can be found in 43%–95% of pediatric patients with NF-1.^3-7 On MR imaging, FASI appear as T2/FLAIR hyperintense lesions of the brain with a predilection for the basal ganglia, cerebellum, and brain stem. Although FASI are not completely understood, myelin vacuolization is commonly considered as an underlying feature of these lesions.^1,4,5,7-9Patients with NF-1 are at an increased risk of developing low- and high-grade brain tumors, including cerebral and cerebellar astrocytomas, ependymomas, and brain stem gliomas, many of which can mimic FASI on MR imaging.^3,10-14 On the other hand, FASI are known for their dynamic properties and may increase or decrease in size or resolve over time.⁸ Although the reference standard for differentiating brain lesions is transcranial biopsy with its own inherent risks, brain signal abnormalities in patients with NF-1 are primarily followed up by MR imaging to screen for possible tumors.^15-18 Contrast enhancement after administration of a gadolinium-based contrast agent is usually considered atypical for FASI and likely to indicate the presence of a brain tumor. Reports considering contrast enhancement in FASI are sparse, limited to case reports and small numbers in cohort studies.^3,6,19-29 We therefore aimed to characterize lesions considered to represent enhancing FASI based on location, volume of enhancement, and demographics to advance the understanding of these rare lesions.     

Brain and Lung Imaging Correlation in Patients with COVID-19: Could the Severity of Lung Disease Reflect the Prevalence of Acute Abnormalities on Neuroimaging? A Global Multicenter Observational Study

PURPOSE:Our aim was to study the association between abnormal findings on chest and brain imaging in patients with coronavirus disease 2019 (COVID-19) and neurologic symptoms.MATERIALS AND METHODS:In this retrospective, international multicenter study, we reviewed the electronic medical records and imaging of hospitalized patients with COVID-19 from March 3, 2020, to June 25, 2020. Our inclusion criteria were patients diagnosed with Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) infection with acute neurologic manifestations and available chest CT and brain imaging. The 5 lobes of the lungs were individually scored on a scale of 0–5 (0 corresponded to no involvement and 5 corresponded to >75% involvement). A CT lung severity score was determined as the sum of lung involvement, ranging from 0 (no involvement) to 25 (maximum involvement).RESULTS:A total of 135 patients met the inclusion criteria with 132 brain CT, 36 brain MR imaging, 7 MRA of the head and neck, and 135 chest CT studies. Compared with 86 (64%) patients without acute abnormal findings on neuroimaging, 49 (36%) patients with these findings had a significantly higher mean CT lung severity score (9.9 versus 5.8, P < .001). These patients were more likely to present with ischemic stroke (40 [82%] versus 11 [13%], P < .0001) and were more likely to have either ground-glass opacities or consolidation (46 [94%] versus 73 [84%], P = .01) in the lungs. A threshold of the CT lung severity score of >8 was found to be 74% sensitive and 65% specific for acute abnormal findings on neuroimaging. The neuroimaging hallmarks of these patients were acute ischemic infarct (28%), intracranial hemorrhage (10%) including microhemorrhages (19%), and leukoencephalopathy with and/or without restricted diffusion (11%). The predominant CT chest findings were peripheral ground-glass opacities with or without consolidation.CONCLUSIONS:The CT lung disease severity score may be predictive of acute abnormalities on neuroimaging in patients with COVID-19 with neurologic manifestations. This can be used as a predictive tool in patient management to improve clinical outcome.

Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) began in Wuhan, China, in December 2019 and has rapidly spread around the world to become a pandemic.¹ Extensive studies have described chest and brain imaging characteristics associated with coronavirus disease 2019 (COVID-19).^2-13 The hallmarks of COVID-19 infection on chest imaging are now well-established, including bilateral and peripheral ground-glass and consolidative pulmonary opacities.^2-5 COVID-19-related brain imaging findings such as ischemic infarcts, hemorrhages, and multiple patterns of leukoencephalopathy^6-13 are also well-known. The clinical symptomatology has been linked to the imaging findings with up to 47% of patients with COVID-19 with neurologic symptoms demonstrating acute neuroimaging findings⁶ and patients with high lung severity scores being admitted to the intensive care unit.³ The incidence of neurologic symptoms is higher in patients with more severe respiratory disease.^10,13 There is increasing evidence that patients with acute lung injury are at risk of brain injury through hypoxemia and/or proinflammatory mediators that connect both the brain and the lungs.^14-17 However, little information is available on the potential association between the prevalence of neuroimaging abnormalities and the severity of CT lung findings in patients with COVID-19. The objective of this study was to examine the association between chest and brain imaging abnormalities in patients with COVID-19. We hypothesized that the severity of lung disease may predict acute abnormalities on neuroimaging in patients with COVID-19 with neurologic symptoms.     

Impact of Kidney Function on CNS Gadolinium Deposition in Patients Receiving Repeated Doses of Gadobutrol

BACKGROUND AND PURPOSE:Studies associate repeat gadolinium-based contrast agent administration with T1 shortening in the dentate nucleus and globus pallidus, indicating CNS gadolinium deposition, most strongly with linear agents but also reportedly with macrocyclics. Renal impairment effects on long-term CNS gadolinium deposition remain underexplored. We investigated the relationship between signal intensity changes and renal function in patients who received ≥10 administrations of the macrocyclic agent gadobutrol.MATERIALS AND METHODS:Patients who underwent ≥10 brain MR imaging examinations with administration of intravenous gadobutrol between February 1, 2014, and January 1, 2018, were included in this retrospective study. Dentate nucleus-to-pons and globus pallidus-to-thalamus signal intensity ratios were calculated, and correlations were calculated between the estimated glomerular filtration rate (minimum and mean) and the percentage change in signal intensity ratios from the first to last scan. Partial correlations were calculated to control for potential confounders.RESULTS:One hundred thirty-one patients (73 women; mean age at last scan, 55.9 years) showed a mean percentage change of the dentate nucleus-to-pons of 0.31%, a mean percentage change of the globus pallidus-to-thalamus of 0.15%, a mean minimum estimated glomerular filtration rate of 69.65 (range, 10.16–132.26), and a mean average estimated glomerular filtration rate at 89.48 (range, 38.24–145.93). No significant association was found between the estimated glomerular filtration rate and percentage change of the dentate nucleus-to-pons (minimum estimated glomerular filtration rate, r = –0.09, P = .28; average estimated glomerular filtration rate, r = –0.09, P = .30,) or percentage change of the globus pallidus-to-thalamus (r = 0.07, P = .43; r = 0.07, P = .40). When we controlled for age, sex, number of scans, and total dose, there were no significant associations between the estimated glomerular filtration rate and the percentage change of the dentate nucleus-to-pons (r = 0.16, P = .07; r = 0.15, P = .08) or percentage change of the globus pallidus-to-thalamus (r = –0.14, P = .12; r = –0.15, P = .09).CONCLUSIONS:In patients receiving an average of 12 intravenous gadobutrol administrations, no correlation was found between renal function and signal intensity ratio changes, even in those with mild or moderate renal impairment.

Gadolinium-based contrast agents (GBCAs) are commonly used in imaging to increase conspicuity and reveal enhancement characteristics of lesions. GBCAs can have either a macrocyclic or a linear molecular structure. Recent studies investigating CNS gadolinium deposition following repeat GBCA administrations showed measurable T1 shortening in the dentate nucleus and globus pallidus in patients who received GBCAs with a linear molecular structure.^1-12 Postmortem studies in patients who received linear agents have documented gadolinium deposition in the CNS, again most prominently in the dentate nucleus and globus pallidus, lending further credibility to imaging findings.^13-15The underlying mechanism of gadolinium retention remains unknown, as does the chemical formulation of the accumulated gadolinium. Despite these unknown mechanisms, gadolinium deposition is thought to involve dissociation of gadolinium from its chelating ligand, so macrocyclic agents are thought to be more stable than linear GBCAs due to their lower dissociation constants.¹⁶ Although the CNS deposition of linear GBCAs has been demonstrated previously, most studies failed to show increased signal intensity in the dentate nucleus and globus pallidus^2-10,17-27 after the use of macrocyclic GBCAs. Nevertheless, a few studies do report increased signal in the brain,^20,27-29 including a postmortem study that detected brain gadolinium, even in the setting of macrocyclic GBCA use.³⁰ On the other hand, two studies using highly sensitive inductively coupled plasma mass spectrometry to measure gadolinium in the brain in animal models did not find significant deposition with macrocyclic agents in the parenchyma, so the picture remains mixed.^31,32GBCAs undergo primary renal clearance;³³ hence, determining whether renal impairment could predispose a patient to gadolinium deposition is important. Patients on hemodialysis receiving a linear GBCA have a greater increase in dentate nucleus signal intensity (SI) compared with controls not on dialysis.¹¹ In 2017, Lee et al²⁰ showed that in a subgroup of 28 patients, there was a significant change in SI ratios in patients with estimated glomerular filtration rates (eGFR) between 45 and 60 mL/min/m² who received the macrocyclic agent gadoterate meglumine. Although much has been discussed regarding nephrogenic systemic fibrosis in the context of renal impairment, there is surprisingly little known regarding the potential effects of abnormal renal function on long-term CNS gadolinium deposition.The purpose of this study was to specifically investigate whether a relationship exists between SI and renal function in patients receiving a large number (≥10) of administrations of the macrocyclic GBCA gadobutrol.     

Evaluation of Ultrafast Wave–Controlled Aliasing in Parallel Imaging 3D-FLAIR in the Visualization and Volumetric Estimation of Cerebral White Matter Lesions

BACKGROUND AND PURPOSE:Our aim was to evaluate an ultrafast 3D-FLAIR sequence using Wave–controlled aliasing in parallel imaging encoding (Wave-FLAIR) compared with standard 3D-FLAIR in the visualization and volumetric estimation of cerebral white matter lesions in a clinical setting.MATERIALS AND METHODS:Forty-two consecutive patients underwent 3T brain MR imaging, including standard 3D-FLAIR (acceleration factor = 2, scan time = 7 minutes 50 seconds) and resolution-matched ultrafast Wave-FLAIR sequences (acceleration factor  = 6, scan time = 2 minutes 45 seconds for the 20-channel coil; acceleration factor = 9, scan time  = 1 minute 50 seconds for the 32-channel coil) as part of clinical evaluation for demyelinating disease. Automated segmentation of cerebral white matter lesions was performed using the Lesion Segmentation Tool in SPM. Student t tests, intraclass correlation coefficients, relative lesion volume difference, and Dice similarity coefficients were used to compare volumetric measurements among sequences. Two blinded neuroradiologists evaluated the visualization of white matter lesions, artifacts, and overall diagnostic quality using a predefined 5-point scale.RESULTS:Standard and Wave-FLAIR sequences showed excellent agreement of lesion volumes with an intraclass correlation coefficient of 0.99 and mean Dice similarity coefficient of 0.97 (SD, 0.05) (range, 0.84–0.99). Wave-FLAIR was noninferior to standard FLAIR for visualization of lesions and motion. The diagnostic quality for Wave-FLAIR was slightly greater than for standard FLAIR for infratentorial lesions (P < .001), and there were fewer pulsation artifacts on Wave-FLAIR compared with standard FLAIR (P < .001).CONCLUSIONS:Ultrafast Wave-FLAIR provides superior visualization of infratentorial lesions while preserving overall diagnostic quality and yields white matter lesion volumes comparable with those estimated using standard FLAIR. The availability of ultrafast Wave-FLAIR may facilitate the greater use of 3D-FLAIR sequences in the evaluation of patients with suspected demyelinating disease.

White matter lesions secondary to demyelination in multiple sclerosis (MS) and related disorders typically present with high T2 signal and are best evaluated with FLAIR imaging, the standard sequence for cerebral white matter lesion detection. FLAIR is a T2-weighted sequence with nulling of the CSF signal, which increases the contrast between lesions and CSF/cerebral sulci and ventricles and improves white matter lesion detection and analysis.¹Quantification of cerebral white matter lesion volume has become increasingly feasible for routine clinical evaluation and use in clinical trials of MS therapies due to the availability of automated segmentation tools and 3D fast spin-echo FLAIR sequences, which delineate cerebral white matter lesions at high isotropic resolution. The Lesion Segmentation Tool (LST; https://www.applied-statistics.de/lst.html), a promising tool for automated segmentation of T2-hyperintense lesions on FLAIR images, was developed for the quantification of MS lesion volumes and has been shown to have good agreement with manual segmentation by expert reviewers.^2-7 However, the high-resolution 3D-FLAIR images required as input for this tool have long acquisition times, limiting the widespread use of automated lesion segmentation in clinical practice.Wave–controlled aliasing in parallel imaging (CAIPI) is a recently developed fast acquisition technology that synergistically combines and extends 2 controlled aliasing approaches, 2D-CAIPI and bunch phase encoding,⁸ to achieve controlled aliasing in all 3 spatial directions (x, y, z). By taking full advantage of the 3D coil sensitivity information, Wave-CAIPI offers high acceleration factors with negligible artifacts and g-factor penalty.^9,10 3D-FLAIR acquired with Wave-CAIPI cuts the scan time down by more than half, possibly facilitating the broader clinical application of 3D-FLAIR in the evaluation of white matter diseases such as MS.The goal of this study was to evaluate an ultrafast Wave-CAIPI 3D-FLAIR sequence (Wave-FLAIR)^11,12 acquired in less than half the time of standard 3D-FLAIR for quantitative and qualitative analyses of cerebral white matter lesions.     

Congenital Nasal Pyriform Aperture Stenosis: Evidence of Premature Fusion of the Midline Palatal Suture

BACKGROUND AND PURPOSE:Various etiologies have been theorized for the development of congenital nasal pyriform aperture stenosis (CNPAS). Imaging possibly implicates abnormal fusion of the midline palatal suture and deficient lateral growth of the midface in affected neonates.MATERIALS AND METHODS:A single-center, retrospective study was performed at a tertiary care pediatric hospital involving neonates and infants between 0 and 90 days of life. Maxillofacial CT scans of patients were reviewed. Abnormality of the palatal suture and midface transverse dimensions were measured and analyzed in patients with and without CNPAS.RESULTS:A total of 109 patients between 0 and 90 days of life had maxillofacial CT scans. Thirteen patients were classified as having CNPAS, 27 patients had normal scans (control group), and 69 patients were excluded because of the presence of other craniofacial anomalies. All patients with CNPAS had evidence of abnormal fusion of the midline palatal suture. Zero patients without CNPAS had a midline palatal suture abnormality. The mean widths of the pyriform aperture were 5.7 mm (SD, 1.7) in the CNPAS group and 13.1 mm (SD, 2.7) in the control group (P < .0001). The mean distance between the superior portions of the nasolacrimal ducts was 9.1 mm (SD, 2.1) in the CNPAS group, and the mean of the control group was 13.4 mm (SD, 2.2) (P < .0001).CONCLUSIONS:Patients with CNPAS have abnormal fusion of the midline palatal suture and exhibit lateral growth restriction of the midface. This may implicate synostosis of the midline palatal suture and abnormal midface growth.

Infants are obligate nasal breathers. As such, any degree of nasal airway obstruction may result in respiratory distress. Soft tissue edema caused by viral or idiopathic rhinitis is the most common cause of bilateral nasal obstruction in neonates. Less common, though clinically important, causes include choanal atresia and congenital nasal pyriform aperture stenosis (CNPAS).CNPAS was first described in 1988 and 1989 in the radiology and otolaryngology literature, respectively.^1,2 Since then, numerous case reports have highlighted 2 possible theories in the embryogenesis, as well as the presentation, diagnosis, and treatment.^3-8 Historically, the 2 theories of embryogenesis are bony overgrowth of the nasal process of the maxilla and a primary deficiency of the hard palate, with most studies citing the former as the cause. Classically, symptoms include respiratory distress relieved by crying, difficulty feeding, nasal congestion, apnea, and failure to thrive. Physical examination may raise the suspicion for CNPAS when a 5F suction catheter cannot be passed through either nasal cavity; note that choanal atresia could have a similar finding. The diagnosis requires a maxillofacial CT revealing the pyriform aperture width to measure less than 11 mm.^3,4 Associated imaging abnormalities include a median central incisor, a triangular-shaped palate, and a median palatal ridge. The presence of a median central incisor warrants further evaluation with MR imaging of the brain because it can occur as part of the holoprosencephaly spectrum.⁹ Genetic consultation may be useful to help define the presence of a syndrome. Treatment starts with medical therapy and, if needed, surgical therapy. Classically, surgical therapy involves drilling bone from the lateral extent of the pyriform aperture, though other entities such as dilation and rapid maxillary expansion have also been described.^3-13As part of the primary author''s previous work on CNPAS,¹¹ a unique, never described radiographic feature was noted. The midline palatal suture appeared abnormally ossified and potentially fused, raising the possibility that CNPAS may be related to lateral growth restriction of the midface akin to craniosynostosis. Other studies have shown that narrowing of the nasal cavity extends posteriorly to include the middle and posterior portions of the nasal cavity, supporting this theory.^3,14 With this in mind, we hypothesize that patients with CNPAS have abnormal midline palatal sutures and decreased midface dimensions compared with a control population.     

3D Quantitative Synthetic MRI in the Evaluation of Multiple Sclerosis Lesions

BACKGROUND AND PURPOSE:Synthetic MR imaging creates multiple contrast-weighted images based on a single time-efficient quantitative scan, which has been mostly performed for 2D acquisition. We assessed the utility of 3D synthetic MR imaging in patients with MS by comparing its diagnostic image quality and lesion volumetry with conventional MR imaging.MATERIALS AND METHODS:Twenty-four patients with MS prospectively underwent 3D quantitative synthetic MR imaging and conventional T1-weighted, T2-weighted, FLAIR, and double inversion recovery imaging, with acquisition times of 9 minutes 3 seconds and 18 minutes 27 seconds for the synthetic MR imaging and conventional MR imaging sequences, respectively. Synthetic phase-sensitive inversion recovery images and those corresponding to conventional MR imaging contrasts were created for synthetic MR imaging. Two neuroradiologists independently assessed the image quality on a 5-point Likert scale. The numbers of cortical lesions and lesion volumes were quantified using both synthetic and conventional image sets.RESULTS:The overall diagnostic image quality of synthetic T1WI and double inversion recovery images was noninferior to that of conventional images (P = .23 and .20, respectively), whereas that of synthetic T2WI and FLAIR was inferior to that of conventional images (both Ps < .001). There were no significant differences in the number of cortical lesions (P = .17 and .53 for each rater) or segmented lesion volumes (P = .61) between the synthetic and conventional image sets.CONCLUSIONS:Three-dimensional synthetic MR imaging could serve as an alternative to conventional MR imaging in evaluating MS with a reduced scan time.

MS is a chronic, immune-mediated, demyelinating disorder of the CNS that usually affects young adults and leads to chronic disability.^1,2 The diagnostic criteria for MS are based on the lesion number, size, and location.³ Although diffuse periventricular lesions are most commonly observed, previous studies have shown that the cortical and juxtacortical lesion load is associated with cognitive impairment.^4,5 Additionally, the detection of cortical and juxtacortical lesions may contribute to early diagnosis because these lesions are characteristic of MS. MR imaging plays an integral role in the diagnosis and management of patients with MS through the in vivo detection and characterization of lesions. Although MR imaging is highly sensitive in detecting periventricular lesions and is considered as a standard biomarker in the monitoring of treatment response,⁶ conventional MR imaging techniques have a relatively low sensitivity for detecting (juxta)cortical lesions. Phase-sensitive inversion recovery (PSIR) and double inversion recovery (DIR) are recently developed imaging techniques useful for detecting MS lesions, especially (juxta)cortical ones.^7,8 The PSIR preserves the positive and negative polarities of tissues as they recover from the inversion pulse, thus providing a T1-weighted contrast with higher SNR and GM-WM contrast. DIR is an imaging technique that suppresses both WM and CSF signals, thus significantly increasing lesion conspicuity in both GM and WM compared with FLAIR or T2-weighted images. PSIR and DIR have been shown to improve sensitivity compared with FLAIR or T2-weighted images in the detection of cortical lesions. However, the additional scanning time associated with PSIR and DIR has hindered the use of these techniques in clinical practice. Thus, a rapid imaging technique that can acquire these contrast-weighted images with high spatial resolution is desired.Quantitative synthetic MR imaging is a time-efficient MR imaging technique that enables simultaneous quantification of T1 and T2 relaxation times and proton attenuation and allows the creation of any contrast-weighted image, including DIR and PSIR, without additional scanning time.^9–13 Previous studies have shown that synthetic MR imaging is useful for detecting and characterizing MS lesions.^10,11,14 However, these studies were based on a multisection 2D acquisition, providing a relatively low resolution in the section direction. 3D quantitative synthetic MR imaging, enabling the simultaneous quantification of T1, T2, and proton attenuation of the whole brain in 3D,^15–17 with smaller section thickness, should allow for more detailed delineation of MS lesions. With the combination of high spatial resolution 3D acquisition and DIR as well as PSIR contrasts, 3D quantitative synthetic MR imaging could serve as a clinically useful technique for monitoring MS lesions.Here, we assessed the utility of the recently developed 3D quantitative synthetic MR imaging for evaluating MS lesions by comparing the synthetic and conventional MR image sets. We hypothesized that 3D synthetic MR imaging would have a comparable diagnostic quality with that of a conventional image set (including 3D FLAIR and DIR) while shortening the total acquisition time.     

Traumatic Cerebral Microbleeds in the Subacute Phase Are Practical and Early Predictors of Abnormality of the Normal-Appearing White Matter in the Chronic Phase

BACKGROUND AND PURPOSE:In the chronic phase after traumatic brain injury, DTI findings reflect WM integrity. DTI interpretation in the subacute phase is less straightforward. Microbleed evaluation with SWI is straightforward in both phases. We evaluated whether the microbleed concentration in the subacute phase is associated with the integrity of normal-appearing WM in the chronic phase.MATERIALS AND METHODS:Sixty of 211 consecutive patients 18 years of age or older admitted to our emergency department ≤24 hours after moderate to severe traumatic brain injury matched the selection criteria. Standardized 3T SWI, DTI, and T1WI were obtained 3 and 26 weeks after traumatic brain injury in 31 patients and 24 healthy volunteers. At baseline, microbleed concentrations were calculated. At follow-up, mean diffusivity (MD) was calculated in the normal-appearing WM in reference to the healthy volunteers (MD_z). Through linear regression, we evaluated the relation between microbleed concentration and MD_z in predefined structures.RESULTS:In the cerebral hemispheres, MD_z at follow-up was independently associated with the microbleed concentration at baseline (left: B = 38.4 [95% CI 7.5–69.3], P = .017; right: B = 26.3 [95% CI 5.7–47.0], P = .014). No such relation was demonstrated in the central brain. MD_z in the corpus callosum was independently associated with the microbleed concentration in the structures connected by WM tracts running through the corpus callosum (B = 20.0 [95% CI 24.8–75.2], P < .000). MD_z in the central brain was independently associated with the microbleed concentration in the cerebral hemispheres (B = 25.7 [95% CI 3.9–47.5], P = .023).CONCLUSIONS:SWI-assessed microbleeds in the subacute phase are associated with DTI-based WM integrity in the chronic phase. These associations are found both within regions and between functionally connected regions.

The yearly incidence of traumatic brain injury (TBI) is around 300 per 100,000 persons.^1,2 Almost three-quarters of patients with moderate to severe TBI have traumatic axonal injury (TAI).³ TAI is a major predictor of functional outcome,^4,5 but it is mostly invisible on CT and conventional MR imaging.^6,7DTI provides direct information on WM integrity and axonal injury.^5,8 However, DTI abnormalities are neither specific for TAI nor stable over time. Possibly because of the release of mass effect and edema and resorption of blood products, the effects of concomitant (non-TAI) injury on DTI are larger in the subacute than in the chronic phase (>3 months).^4,9,10 Therefore, DTI findings are expected to reflect TAI more specifically in the chronic than in the subacute phase (1 week–3 months).⁴ Even in regions without concomitant injury, the effects of TAI on DTI are dynamic, possibly caused by degeneration and neuroplastic changes.^6,11,12 These ongoing pathophysiological processes possibly contribute to the emerging evidence that DTI findings in the chronic phase are most closely associated with the eventual functional outcome.^12,13Although DTI provides valuable information, its acquisition, postprocessing, and interpretation in individual patients are demanding. SWI, with which microbleeds can be assessed with high sensitivity, is easier to interpret and implement in clinical practice. In contrast to DTI, SWI-detected traumatic microbleeds are more stable¹ except in the hyperacute^14,15 and the late chronic phases.¹⁶ Traumatic cerebral microbleeds are commonly interpreted as signs of TAI. However, the relation is not straightforward. On the one hand, nontraumatic microbleeds may be pre-existing. On the other hand, even if traumatic in origin, microbleeds represent traumatic vascular rather than axonal injury.¹⁷ Indeed, TAI is not invariably hemorrhagic.¹⁸ Additionally, microbleeds may secondarily develop after trauma through mechanisms unrelated to axonal injury, such as secondary ischemia.¹⁸DTI is not only affected by pathophysiological changes but also by susceptibility.¹⁹ The important susceptibility-effect generated by microbleeds renders the interpretation of DTI findings at the location of microbleeds complex. In the chronic phase, mean diffusivity (MD) is the most robust marker of WM integrity.^4,6 For these reasons, we evaluated MD in the normal-appearing WM.Much TAI research focuses on the corpus callosum because it is commonly involved in TAI^5,18,20 and it can reliably be evaluated with DTI,^5,21 and TAI in the corpus callosum is related to clinical prognosis.^6,20 The corpus callosum consists of densely packed WM tracts that structurally and functionally connect left- and right-sided brain structures.²² The integrity of the corpus callosum is associated with the integrity of the brain structures it connects.²³ Therefore, microbleeds in brain structures that are connected through the corpus callosum may affect callosal DTI findings. Analogous to this, microbleeds in the cerebral hemispheres, which exert their function through WM tracts traveling through the deep brain structures and brain stem,^24,25 may affect DTI findings in the WM of the latter.Our purpose was to evaluate whether the microbleed concentration in the subacute phase is associated with the integrity of normal-appearing WM in the chronic phase. We investigated this relation within the cerebral hemispheres and the central brain and between regions that are functionally connected by WM tracts.     

MRI Shrimp Sign in Cerebellar Progressive Multifocal Leukoencephalopathy: Description and Validation of a Novel Observation

BACKGROUND AND PURPOSE:There are no validated imaging criteria for the diagnosis of progressive multifocal leukoencephalopathy in the cerebellum. Here we introduce the MR imaging shrimp sign, a cerebellar white matter lesion identifiable in patients with cerebellar progressive multifocal leukoencephalopathy, and we evaluate its sensitivity and specificity.MATERIALS AND METHODS:We first identified patients with progressive multifocal leukoencephalopathy seen at Massachusetts General Hospital between 1998 and 2019 whose radiology reports included the term “cerebellum.” Drawing on a priori knowledge, 2 investigators developed preliminary diagnostic criteria for the shrimp sign. These criteria were revised and validated in 2 successive stages by 4 additional blinded investigators. After defining the MR imaging shrimp sign, we assessed its sensitivity, specificity, positive predictive value, and negative predictive value.RESULTS:We identified 20 patients with cerebellar progressive multifocal leukoencephalopathy: 16 with definite progressive multifocal leukoencephalopathy (mean, 46.4 [SD, 9.2] years of age; 5 women), and 4 with possible progressive multifocal leukoencephalopathy (mean, 45.8 [SD, 8.5] years of age; 1 woman). We studied 40 disease controls (mean, 43.6 [SD, 21.0] years of age; 16 women) with conditions known to affect the cerebellar white matter. We defined the MR imaging shrimp sign as a T2- and FLAIR-hyperintense, T1-hypointense, discrete cerebellar white matter lesion abutting-but-sparing the dentate nucleus. MR imaging shrimp sign sensitivity was 0.85; specificity, 1; positive predictive value, 1; and negative predictive value, 0.93. The shrimp sign was also seen in fragile X–associated tremor ataxia syndrome, but radiographic and clinical features distinguished it from progressive multifocal leukoencephalopathy.CONCLUSIONS:In the right clinical context, the MR imaging shrimp sign has excellent sensitivity and specificity for cerebellar progressive multifocal leukoencephalopathy, providing a new radiologic marker of the disease.

Progressive multifocal leukoencephalopathy (PML) is an opportunistic demyelinating disease in which the human JC polyomavirus (JCV) causes lytic infection of oligodendrocytes, astrocytes, and, rarely, neurons.¹ It affects immunosuppressed patients with an impaired T-lymphocyte response, including patients with chronic lymphocytic leukemia, Hodgkin lymphoma, and HIV/AIDS.^2-5 The increase in the PML incidence associated with immune therapies such as natalizumab for multiple sclerosis^6-8 underscores the importance of developing early, validated diagnostic criteria for PML.^6-8Cerebellar and brainstem involvement in PML was identified 4 decades ago. There are few studies of the diagnostic specificity of pontocerebellar findings on MR imaging in PML.^9,10 A punctate pattern of T2 and FLAIR hyperintensity is described in natalizumab-associated PML and in PML–immune reconstitution inflammatory syndrome.^11,12 The hot cross bun sign, a cruciform T2 hyperintense signal in the midpons, has been noted late in the course of PML, affecting posterior fossa structures, when both the brainstem and the cerebellum have lost considerable volume (olivopontocerebellar atrophy). The hot cross bun sign was described initially in the cerebellar subtype of multiple system atrophy^13,14 and is also seen in spinocerebellar ataxia, particularly spinocerebellar ataxia 1 and 2,¹⁵ and in variant Creutzfeldt-Jakob disease¹⁶ and cerebral vasculitis.¹⁷ Conditions other than PML affect the middle cerebellar peduncles, and disorders of immunocompromised patients such as toxoplasmosis, lymphoma, posterior reversible encephalopathy syndrome (PRES), neuro-Behçet disease, or HIV encephalitis may pose a diagnostic challenge. Cerebellar neuroimaging markers specific to PML may, therefore, aid diagnosis and preempt invasive procedures like brain biopsy.¹⁰The shrimp sign was first proposed as a marker of cerebellar PML 25 years ago by N.V., who characterized it as a well-defined T2- or FLAIR-hyperintense and T1-hypointense lesion in the cerebellar white matter that abuts-but-spares the dentate nucleus and has the shape of a shrimp. It may also involve the hilum of the dentate nucleus. On axial MR imaging, the well-defined white matter lesion outlines the serrated, curvilinear-shaped dentate nucleus.We designed this study to determine whether the shrimp sign is, indeed, a reliable indicator of cerebellar PML and to assess its sensitivity and specificity.     

Value of Emergent Neurovascular Imaging for “Seat Belt Injury”: A Multi-institutional Study

BACKGROUND AND PURPOSE:Screening for blunt cerebrovascular injury in patients after motor vehicle collision (MVC) solely based on the presence of cervical seat belt sign has been debated in the literature without consensus. Our aim was to assess the value of emergent neurovascular imaging in patients after an MVC who present with a seat belt sign through a large-scale multi-institutional study.MATERIALS AND METHODS:The electronic medical records of patients admitted to the emergency department with CTA/MRAs performed with an indication of seat belt injury of the neck were retrospectively reviewed at 5 participating institutions. Logistic regression analysis was used to determine the association among age, sex, and additional trauma-related findings with blunt cerebrovascular injury.RESULTS:Five hundred thirty-five adult and 32 pediatric patients from June 2003 until March 2020 were identified. CTA findings were positive in 12/567 (2.1%) patients for the presence of blunt cerebrovascular injury of the vertebral (n = 8) or internal carotid artery (n = 4) in the setting of acute trauma with the seat belt sign. Nine of 12 patients had symptoms, signs, or risk factors for cervical blunt cerebrovascular injury other than the seat belt sign. The remaining 3 patients (3/567, 0.5%) had Biffl grades I–II vascular injury with no neurologic sequelae. The presence of at least 1 additional traumatic finding or the development of a new neurologic deficit was significantly associated with the presence of blunt cerebrovascular injury among adult patients, with a risk ratio of 11.7 (P = .001). No children had blunt cerebrovascular injury.CONCLUSIONS:The risk of vascular injury in the presence of the cervical seat belt sign is small, and most patients diagnosed with blunt cerebrovascular injury have other associated findings. Therefore, CTA based solely on this sign has limited value (3/567 =  a 0.5% positivity rate). We suggest that in the absence of other clinical findings, the seat belt sign does not independently justify neck CTA in patients after trauma.

Motor vehicle collision (MVC) is a major cause of blunt cerebrovascular injury (BCVI).¹ Historically, the incidence of BCVI was reported to be as low as 0.1%–0.67% among patients with blunt trauma.^2,3 However, implementation of more rigorous screening protocols in trauma centers has revealed a 10-fold higher rate of BCVI, as high as 2.7%, among severely injured patients.^4-6 Although uncommon, the neurologic sequelae of BCVI are potentially serious. Many patients do not manifest stroke symptoms until hours to days after the injury,⁷ and when not treated in a timely fashion, up to 80% develop permanent neurologic sequelae with an estimated 40% mortality rate.^3,8,9 Thus, screening CTA or MRA for BCVI has become commonplace in the management of patients after an MVC.^10,11 However, the selection of which patients to screen has been a controversial topic during the past 4 decades.⁶Various screening algorithms, including the modified Memphis and Denver criteria or the Western Trauma Association algorithm, may be used as guidelines (Online Supplemental Data). These guidelines, developed on the basis of observational studies and expert opinion, have adopted a liberal approach to imaging patients with possible BCVI.^7,12,13 Although this approach helps avoid missing occult injuries, it may lead to unnecessary imaging, discovery of incidental findings, increased radiation exposure, and low-value health care expenditures.^14-17 Many believe that advanced imaging studies are being overused in many medical centers, in part, due to a “defensive medicine” mentality. It is estimated that up to 50% of ordered studies lead to no improvement in patient welfare.^15,18One of the controversial indications for BCVI is the physical sign of neck abrasion or contusion caused by a seat belt, the so-called cervical seat belt sign. Screening for BCVI solely based on the presence of this sign has been debated in the literature without consensus.^19-22 The existing guidelines also recommend contradictory approaches regarding the use of the seat belt sign as a sole indicator to stratify patients for screening (Online Supplemental Data). Despite some single-center studies suggesting that discoloration of the skin from the seat belt is not a reliable indicator of risk to the cervical vessels,^23-25 many trauma centers persist in ordering emergent CTAs to exclude BCVI in patients with this finding because of continued debate as to the validity of the seat belt sign as an indicator of vascular injury. To address this controversy, we aimed to assess the value of emergent neurovascular imaging in patients with a seat belt sign after an MVC through a large-scale multi-institutional study that would identify the situations in which the seat belt sign may be predictive of cervical vascular injury. We hypothesized that cervical CTA performed solely on the basis of a seat belt sign has limited value.     

Inversion Recovery Ultrashort TE MR Imaging of Myelin is Significantly Correlated with Disability in Patients with Multiple Sclerosis

BACKGROUND AND PURPOSE:MR imaging has been widely used for the noninvasive evaluation of MS. Although clinical MR imaging sequences are highly effective in showing focal macroscopic tissue abnormalities in the brains of patients with MS, they are not specific to myelin and correlate poorly with disability. We investigated direct imaging of myelin using a 2D adiabatic inversion recovery ultrashort TE sequence to determine its value in assessing disability in MS.MATERIALS AND METHODS:The 2D inversion recovery ultrashort TE sequence was evaluated in 14 healthy volunteers and 31 patients with MS. MPRAGE and T2-FLAIR images were acquired for comparison. Advanced Normalization Tools were used to correlate inversion recovery ultrashort TE, MPRAGE, and T2-FLAIR images with disability assessed by the Expanded Disability Status Scale.RESULTS:Weak correlations were observed between normal-appearing white matter volume (R = –0.03, P = .88), lesion load (R = 0.22, P = .24), and age (R = 0.14, P = .44), and disability. The MPRAGE signal in normal-appearing white matter showed a weak correlation with age (R = –0.10, P = .49) and disability (R = –0.19, P = .31). The T2-FLAIR signal in normal-appearing white matter showed a weak correlation with age (R = 0.01, P = .93) and disability (R = 0.13, P = .49). The inversion recovery ultrashort TE signal was significantly negatively correlated with age (R = –0.38, P = .009) and disability (R = –0.44; P = .01).CONCLUSIONS:Direct imaging of myelin correlates with disability in patients with MS better than indirect imaging of long-T2 water in WM using conventional clinical sequences.

MS is the most common demyelinating disease of the brain.¹ Demyelination affects many aspects of neurologic function, including speech, balance, and cognitive awareness. Across time, this frequently leads to severe and irreversible clinical disability. MR imaging has been widely used for accurate diagnosis of MS, with current techniques focused on imaging the long-T2 water components in WM and GM.^2-4 MS lesions often appear hypointense with T1-weighted gradient recalled-echo sequences² and hyperintense with T2-weighted FSE and T2-weighted FLAIR sequences.³ Active lesions can be highlighted with gadolinium-enhanced imaging.⁴ The magnetization transfer ratio has been used as an indirect marker of myelin disorder in regions of normal-appearing WM (NAWM).⁵ There are also several other advanced imaging techniques for indirect myelin imaging via assessment of myelin water, such as multicomponent T2 or T2* analysis^6,7 and direct visualization of components with short transverse relaxation times.^8,9While conventional MR imaging sequences are highly effective in detecting focal macroscopic brain tissue abnormalities, they are not specific for pathologic substrates of MS lesions such as demyelination and remyelination, and they may not correlate well with patients'' neurologic deficits. Current MR imaging techniques correlate only modestly with disability assessed by the Expanded Disability Status Scale (EDSS).^10-15 The total lesion load showed statistically significant-but-weak correlations with the EDSS score in several large-scale studies (R = 0.1–0.3).^10-12 Composite scores including relaxation times of different tissues and/or volumetric measures generally correlate more strongly with the EDSS score, with a maximum observed correlation of R = 0.34 (P < .001).¹³ Lesions seen with gadolinium-enhanced imaging are only moderately correlated with disability in the first 6 months and are not predictive of changes in the EDSS score in the subsequent 1 or 2 years.¹⁴ A large-scale multicenter study reported very limited correlation between the EDSS score and normalized brain volume (R = –0.18), cross-sectional area (R = –0.26), magnetization transfer ratio of whole-brain tissue (R = –0.16), and GM (R = –0.17).¹⁵The poor performance of conventional MR imaging sequences in assessing disability highlights the need for novel MR imaging techniques that can directly image myelin lipid and enable direct assessment of both myelin damage and repair. However, myelin has an extremely short transverse relaxation time and is not directly detectable with conventional MR images, which typically have TEs of several milliseconds or longer. Ultrashort TE (UTE) sequences can directly detect signal from myelin with ultrashort T2 (ie, excluding water with longer T2s).^16-21 In this study, we describe imaging of WM using a 2D adiabatic inversion recovery prepared UTE (IR-UTE) sequence in healthy volunteers and patients with MS and evaluate its performance in assessing disability in patients with MS compared with 2 conventional clinical sequences.     

Neonatal Developmental Venous Anomalies: Clinicoradiologic Characterization and Follow-Up

BACKGROUND AND PURPOSE:Although developmental venous anomalies have been frequently studied in adults and occasionally in children, data regarding these entities are scarce in neonates. We aimed to characterize clinical and neuroimaging features of neonatal developmental venous anomalies and to evaluate any association between MR imaging abnormalities in their drainage territory and corresponding angioarchitectural features.MATERIALS AND METHODS:We reviewed parenchymal abnormalities and angioarchitectural features of 41 neonates with developmental venous anomalies (20 males; mean corrected age, 39.9 weeks) selected through a radiology report text search from 2135 neonates who underwent brain MR imaging between 2008 and 2019. Fetal and longitudinal MR images were also reviewed. Neurologic outcomes were collected. Statistics were performed using χ², Fisher exact, Mann-Whitney U, or t tests corrected for multiple comparisons.RESULTS:Developmental venous anomalies were detected in 1.9% of neonatal scans. These were complicated by parenchymal/ventricular abnormalities in 15/41 cases (36.6%), improving at last follow-up in 8/10 (80%), with normal neurologic outcome in 9/14 (64.2%). Multiple collectors (P = .008) and larger collector caliber (P < .001) were significantly more frequent in complicated developmental venous anomalies. At a patient level, multiplicity (P = .002) was significantly associated with the presence of ≥1 complicated developmental venous anomaly. Retrospective fetal detection was possible in 3/11 subjects (27.2%).CONCLUSIONS:One-third of neonatal developmental venous anomalies may be complicated by parenchymal abnormalities, especially with multiple and larger collectors. Neuroimaging and neurologic outcomes were favorable in most cases, suggesting a benign, self-limited nature of these vascular anomalies. A congenital origin could be confirmed in one-quarter of cases with available fetal MR imaging.

Developmental venous anomalies (DVAs) are the most frequently diagnosed intracranial vascular malformations, often encountered as incidental neuroimaging findings.^1,2 On MR imaging, DVAs are recognized on postcontrast T1WI as radially oriented veins with a “caput medusae” pattern converging into 1 (or rarely more) dilated venous collector.^3,4 These features may be also detected on precontrast MR images,^3-5 especially if T2*-weighted sequences such as high-resolution SWI are included in the protocol.⁵ In addition, DVAs may be occasionally recognized in utero using fetal MR imaging.⁶DVAs are usually considered benign anatomic variants.⁷ However, they represent areas of venous fragility that can become symptomatic through diverse pathomechanisms.^8,9 Indeed, DVA-associated brain abnormalities are frequently depicted, including-but-not limited-to sporadic cerebral cavernous malformations (CCMs).^8-16 Moreover, a higher prevalence of DVAs has been described in patients with different pathologies and/or genetic conditions.^17-21Although DVAs are widely described and characterized in adults, they remain under-reported in the pediatric population. Indeed, there are noticeably fewer studies focusing exclusively on DVAs in this age group, especially in the neonatal period.^17,18,21-24 In particular, the largest case series of neonatal DVAs described so far included 14 neonates, mostly detected using ultrasound during routine scanning for other reasons,²² with limited information on the prevalence and perinatal characteristics of these vascular abnormalities, including complications and longitudinal evolution. Moreover, additional data on neonatal and fetal DVAs would be of great interest because there is an ongoing debate regarding their congenital or postnatal etiology.²⁵In this study, we aimed to describe the pre- and postnatal appearance of DVAs and associated brain anomalies in a relatively large single-center group of neonates, providing information on their imaging and clinical follow-up. In addition, we tested a possible association between parenchymal and ventricular abnormalities in the drainage territory of neonatal DVAs and their angioarchitectural features.     

Determining the Degree of Dopaminergic Denervation Based on the Loss of Nigral Hyperintensity on SMWI in Parkinsonism

BACKGROUND AND PURPOSE:Nigrostriatal dopaminergic function in patients with Parkinson disease can be assessed using ¹²³I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropan dopamine transporter (¹²³I-FP-CIT) SPECT, and a good correlation has been demonstrated between nigral status on SWI and dopaminergic denervation on ¹²³I-FP-CIT SPECT. Here, we aim to correlate quantified dopamine transporter attenuation on ¹²³I-FP-CIT SPECT with nigrosome-1 status using susceptibility map-weighted imaging (SMWI).MATERIALS AND METHODS:Between May 2017 and January 2018, consecutive patients with idiopathic Parkinson disease (n = 109) and control participants (n = 29) who underwent ¹²³I-FP-CIT SPECT with concurrent 3T SWI were included. SMWI was generated from SWI. Two neuroradiologists evaluated nigral hyperintensity from nigrosome-1 on each side of the substantia nigra. Using consensus reading, we compared the ¹²³I-FP-CIT–specific binding ratio according to nigral hyperintensity status and the ¹²³I-FP-CIT specific binding ratio threshold to confirm the loss of nigral hyperintensity was determined using receiver operating characteristic curve analysis.RESULTS:The concordance rate between SMWI and ¹²³I-FP-CIT SPECT was 65.9%. The ¹²³I-FP-CIT–specific binding ratios in the striatum, caudate nucleus, and putamen were significantly lower when nigral hyperintensity in the ipsilateral substantia nigra was absent than when present (all, P < .001). The ¹²³I-FP-CIT–specific binding ratio threshold values for the determination of nigral hyperintensity loss were 2.56 in the striatum (area under the curve, 0.890), 3.07 in the caudate nucleus (0.830), and 2.36 in the putamen (0.887).CONCLUSIONS:Nigral hyperintensity on SMWI showed high positive predictive value and low negative predictive value with dopaminergic degeneration on ¹²³I-FP-CIT SPECT. In patients with Parkinson disease, the loss of nigral hyperintensity is prominent in patients with lower striatal specific binding ratios.

The second most common neurodegenerative disorder,^1,2 Parkinson disease (PD) is characterized by dopaminergic cell loss within the substantia nigra (SN) of the midbrain that reportedly progresses from structures called nigrosomes,¹ beginning with the largest subdivision of nigrosome-1.^3,4 The presence of nigrosome-1 can be assessed using high-resolution MR imaging, and its absence can serve as a powerful diagnostic tool for PD.^5-13The standardized assessment of nigrostriatal dopaminergic function in patients with PD has been performed using SPECT, including ¹²³I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (¹²³I-FP-CIT) SPECT as its more common variation.^14-16 Although research has demonstrated a good correlation between nigral status determined with SWI and the status of dopaminergic denervation revealed with ¹²³I-FP-CIT SPECT,^5,7 the 2 methods lack absolute agreement. In addition, denervation can reportedly be observed on ¹²³I-FP-CIT SPECT, but nigral hyperintensity is maintained on MR imaging,^5,7 possibly informing a false-negative diagnosis of PD. To the best of our knowledge, no study has evaluated the relationship between the degree of dopaminergic denervation on ¹²³I-FP-CIT SPECT and the status of nigral hyperintensity on SWI.The present study aims to determine the degree of the dopaminergic denervation on ¹²³I-FP-CIT SPECT according to the presence or loss of nigral hyperintensity on 3T MR imaging in patients with PD. We evaluated the striatal specific binding ratios (SBRs) of the ¹²³I-FP-CIT and used susceptibility map-weighted imaging (SMWI) to enhance the visibility of nigrosome-1.^17,18 The purpose of this study was to correlate quantified dopamine transporter attenuation on SPECT with the status of nigral hyperintensity on MR imaging.     

Cortical Distribution of Fragile Periventricular Anastomotic Collateral Vessels in Moyamoya Disease: An Exploratory Cross-Sectional Study of Japanese Patients with Moyamoya Disease

BACKGROUND AND PURPOSE:Collateral vessels in Moyamoya disease represent potential sources of bleeding. To test whether these cortical distributions vary among subtypes, we investigated cortical terminations using both standardized MR imaging and MRA.MATERIALS AND METHODS:Patients with Moyamoya disease who underwent MR imaging with MRA in our institution were enrolled in this study. MRA was spatially normalized to the Montreal Neurological Institute space; then, collateral vessels were measured on MRA and classified into 3 types of anastomosis according to the parent artery: lenticulostriate, thalamic, and choroidal. We also obtained the coordinates of collateral vessel outflow to the cortex. Differences in cortical terminations were compared among the 3 types of anastomosis.RESULTS:We investigated 219 patients with Moyamoya disease, and a total of 190 collateral vessels (lenticulostriate anastomosis, n = 72; thalamic anastomosis, n = 21; choroidal anastomosis, n = 97) in 46 patients met the inclusion criteria. We classified the distribution patterns of collateral anastomosis as follows: lenticulostriate collaterals outflowing anteriorly (P < .001; 95% CI, 67.0–87.0) and medially (P < .001; 95% CI, 11.0–24.0) more frequently than choroidal collaterals; lenticulostriate collaterals outflowing anteriorly more frequently than thalamic collaterals (P < .001; 95% CI, 34.0–68.0); and choroidal collaterals outflowing posteriorly more frequently than thalamic collaterals (P < .001; 95% CI, 14.0–34.0). Lenticulostriate anastomoses outflowed to the superior or inferior frontal sulcus and interhemispheric fissure. Thalamic anastomoses outflowed to the insular cortex and cortex around the central sulcus. Choroidal anastomoses outflowed to the cortex posterior to the central sulcus and the insular cortex.CONCLUSIONS:Cortical distribution patterns appear to differ markedly among the 3 types of collaterals.

Collateral vessels in Moyamoya disease develop as the disease progresses.¹ Lenticulostriate arteries (LSAs), perforators from the posterior communicating artery (PcomA), and anterior and posterior choroidal arteries (choAs) are representative collateral vessels that supply the cortex.^2-4 Development of such collateral vessels represents a risk factor for intracerebral hemorrhage,^3,5-7 and these vessels have frequently been considered as the vessels responsible for bleeding in recent reports.^8-10 These collateral vessels connect with medullary arteries near the lateral ventricle and thus supply the cortex via the medullary arteries.^3,4 However, no reports have addressed the cortical distributions of these collateral vessels.Bypass surgery reduces the risk of rebleeding in patients with hemorrhagic onset of Moyamoya disease^7,11-13 and also shrinks collateral vessels in Moyamoya disease.^7,12,14,15 Augmentation of cerebral blood flow via bypass seems to decrease the necessity for development of collateral flow and shrinks existing collaterals.¹⁵ To shrink risky collateral vessels effectively and prevent hemorrhage, well-designed and planned bypass surgeries may be required.¹⁶ Comprehension of the nature and cortical distribution of collateral vessels may thus be clinically useful.MRA performed using a 3T scanner has proved useful for detecting the abnormally extended collateral vessels in Moyamoya disease.² We investigated the cortical distribution of collateral vessels using 3T MR imaging and MRA to clarify whether cortical distributions vary among anastomotic subtypes and to better understand collateral networks.     

Clinical,Imaging, and Lab Correlates of Severe COVID-19 Leukoencephalopathy

BACKGROUND AND PURPOSE:Patients infected with the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) can develop a spectrum of neurological disorders, including a leukoencephalopathy of variable severity. Our aim was to characterize imaging, lab, and clinical correlates of severe coronavirus disease 2019 (COVID-19) leukoencephalopathy, which may provide insight into the SARS-CoV-2 pathophysiology.MATERIALS AND METHODS:Twenty-seven consecutive patients positive for SARS-CoV-2 who had brain MR imaging following intensive care unit admission were included. Seven (7/27, 26%) developed an unusual pattern of “leukoencephalopathy with reduced diffusivity” on diffusion-weighted MR imaging. The remaining patients did not exhibit this pattern. Clinical and laboratory indices, as well as neuroimaging findings, were compared between groups.RESULTS:The reduced-diffusivity group had a significantly higher body mass index (36 versus 28 kg/m², P < .01). Patients with reduced diffusivity trended toward more frequent acute renal failure (7/7, 100% versus 9/20, 45%; P = .06) and lower estimated glomerular filtration rate values (49 versus 85 mL/min; P = .06) at the time of MRI. Patients with reduced diffusivity also showed lesser mean values of the lowest hemoglobin levels (8.1 versus 10.2 g/dL, P < .05) and higher serum sodium levels (147 versus 139 mmol/L, P = .04) within 24 hours before MR imaging. The reduced-diffusivity group showed a striking and highly reproducible distribution of confluent, predominantly symmetric, supratentorial, and middle cerebellar peduncular white matter lesions (P < .001).CONCLUSIONS:Our findings highlight notable correlations between severe COVID-19 leukoencephalopathy with reduced diffusivity and obesity, acute renal failure, mild hypernatremia, anemia, and an unusual brain MR imaging white matter lesion distribution pattern. Together, these observations may shed light on possible SARS-CoV-2 pathophysiologic mechanisms associated with leukoencephalopathy, including borderzone ischemic changes, electrolyte transport disturbances, and silent hypoxia in the setting of the known cytokine storm syndrome that accompanies severe COVID-19.

Among the neurologic disorders associated with Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2)^1-3 infection, there have been several reports of diffuse white matter abnormalities, including a “leukoencephalopathy with reduced diffusivity” on diffusion-weighted MR imaging.⁴ This pattern of severe, bilateral white matter involvement appears to develop late in the course of coronavirus disease 2019 (COVID-19) in critically ill patients and may be related to the prolonged hypoxemia that these patients experience, often even while asymptomatic.⁵Indeed, although leukoencephalopathy can result from a diverse group of genetic, toxic/metabolic, inflammatory, and infectious conditions, several well-described leukoencephalopathy syndromes may have direct relevance to COVID-19 pathophysiology. These disorders, which are associated with distinct clinical features, imaging patterns, and laboratory findings, include but are not limited to both delayed posthypoxic leukoencephalopathy (which often develops days or weeks following an initial, typically catastrophic, global hypoxic event, such as carbon monoxide poisoning, drowning, opioid overdose, or other causes of cardiac arrest)^6-9 and sepsis-related leukoencephalopathy (which occurs in critically ill patients and is likely due to deranged blood-brain barrier permeability caused by inflammatory mediators, allowing passage of cytokines and other neurotoxins into the cerebral white matter).^10-13Review of the current literature suggests possible roles for “silent hypoxia” and/or “cytokine storm” in the development of severe COVID-19-related leukoencephalopathy;^5,14,15 the paucity of postmortem studies to date contributes to this uncertainty.¹⁶ Our purpose, therefore, has been to characterize the clinical, imaging, and laboratory correlates of COVID-19 leukoencephalopathy, which may provide insight into the SARS-CoV-2 pathophysiologic mechanisms of severe white matter cellular injury.