Periodic Alternating Gaze Deviation
Quantifying T2-FLAIR Mismatch Using Geographically Weighted Regression and Predicting Molecular Status in Lower-Grade Gliomas
BACKGROUND AND PURPOSE/OBJECTIVE:-mutant 1p/19q noncodeleted gliomas with a high positive predictive value. We have developed an approach to quantify the T2-FLAIR mismatch signature and use it to predict the molecular status of lower-grade gliomas. MATERIALS AND METHODS/METHODS:We used multiparametric MR imaging scans and segmentation labels of 108 preoperative lower-grade glioma tumors from The Cancer Imaging Archive. Clinical information and T2-FLAIR mismatch sign labels were obtained from supplementary material of relevant publications. We adopted an objective analytic approach to estimate this sign through a geographically weighted regression and used the residuals for each case to construct a probability density function (serving as a residual signature). These functions were then analyzed using an appropriate statistical framework. RESULTS:-mutant 1p/19q noncodeleted class of tumors versus other categories. Our classifier predicts these cases with area under the curve of 0.98 and high specificity and sensitivity. It also predicts the T2-FLAIR mismatch sign within these cases with an under the curve of 0.93. CONCLUSIONS:-mutation and 1p/19q codeletion status with high predictive power. The utility of the proposed quantification of the T2-FLAIR mismatch sign can be potentially validated through a prospective multi-institutional study.
Increase in Ventricle Size and the Evolution of White Matter Changes on Serial Imaging in Critically Ill Patients with COVID-19
BACKGROUND:Evolution of brain magnetic resonance imaging (MRI) findings in critically ill patients with coronavirus disease 2019 (COVID-19) is unknown. METHODS:We retrospectively reviewed 4530 critically ill patients with COVID-19 admitted to three tertiary care hospitals in New York City from March 1 to June 30, 2020 to identify patients who had more than one brain MRI. We reviewed the initial and final MRI for each patient to (1) measure the percent change in the bicaudate index and third ventricular diameter and (2) evaluate changes in the presence and severity of white matter changes. RESULTS:Twenty-one patients had two MRIs separated by a median of 22 [Interquartile range (IQR) 14-30] days. Ventricle size increased for 15 patients (71%) between scans [median bicaudate index 0.16 (IQR 0.126-0.181) initially and 0.167 (IQR 0.138-0.203) on final imaging (pâ€‰<â€‰0.001); median third ventricular diameter 6.9Â mm (IQR 5.4-10.3) initially and 7.2Â mm (IQR 6.4-10.8) on final imaging (pâ€‰<â€‰0.001)]. Every patient had white matter changes on the initial and final MRI; between images, they worsened for seven patients (33%) and improved for three (14%). CONCLUSIONS:On serial imaging of critically ill patients with COVID-19, ventricle size frequently increased over several weeks. White matter changes were often unchanged, but in some cases they worsened or improved, demonstrating there is likely a spectrum of pathophysiological processes responsible for these changes.
COVID-19 associated brain/spinal cord lesions and leptomeningeal enhancement: A meta-analysis of the relationship to CSF SARS-CoV-2
BACKGROUND AND PURPOSE/OBJECTIVE:We reviewed the literature to evaluate cerebrospinal fluid (CSF) results from patients with coronavirus disease 2019 (COVID-19) who had neurological symptoms and had an MRI that showed (1) central nervous system (CNS) hyperintense lesions not attributed to ischemia and/or (2) leptomeningeal enhancement. We sought to determine if these findings were associated with a positive CSF severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR). METHODS:We performed a systematic review of Medline and Embase from December 1, 2019 to November 18, 2020. CSF results were evaluated based on the presence/absence of (1) â‰¥ 1 CNS hyperintense lesion and (2) leptomeningeal enhancement. RESULTS:In 117 publications, we identified 193 patients with COVID-19 who had an MRI of the CNS and CSF testing. There were 125 (65%) patients with CNS hyperintense lesions. Patients with CNS hyperintense lesions were significantly more likely to have a positive CSF SARS-CoV-2 PCR (10% [9/87] vs. 0% [0/43], p = 0.029). Of 75 patients who had a contrast MRI, there were 20 (27%) patients who had leptomeningeal enhancement. Patients with leptomeningeal enhancement were significantly more likely to have a positive CSF SARS-CoV-2 PCR (25% [4/16] vs. 5% [2/42], p = 0.024). CONCLUSION/CONCLUSIONS:The presence of CNS hyperintense lesions or leptomeningeal enhancement on neuroimaging from patients with COVID-19 is associated with increased likelihood of a positive CSF SARS-CoV-2 PCR. However, a positive CSF SARS-CoV-2 PCR is uncommon in patients with these neuroimaging findings, suggesting they are often related to other etiologies, such as inflammation, hypoxia, or ischemia.
Anticoagulation use and Hemorrhagic Stroke in SARS-CoV-2 Patients Treated at a New York Healthcare System
BACKGROUND AND PURPOSE/OBJECTIVE:While the thrombotic complications of COVID-19 have been well described, there are limited data on clinically significant bleeding complications including hemorrhagic stroke. The clinical characteristics, underlying stroke mechanism, and outcomes in this particular subset of patients are especially salient as therapeutic anticoagulation becomes increasingly common in the treatment and prevention of thrombotic complications of COVID-19. METHODS:We conducted a retrospective cohort study of patients with hemorrhagic stroke (both non-traumatic intracerebral hemorrhage and spontaneous non-aneurysmal subarachnoid hemorrhage) who were hospitalized between March 1, 2020, and May 15, 2020, within a major healthcare system in New York, during the coronavirus pandemic. Patients with hemorrhagic stroke on admission and who developed hemorrhage during hospitalization were both included. We compared the clinical characteristics of patients with hemorrhagic stroke and COVID-19 to those without COVID-19 admitted to our hospital system between March 1, 2020, and May 15, 2020 (contemporary controls), and March 1, 2019, and May 15, 2019 (historical controls). Demographic variables and clinical characteristics between the individual groups were compared using Fischer's exact test for categorical variables and nonparametric test for continuous variables. We adjusted for multiple comparisons using the Bonferroni method. RESULTS:During the study period in 2020, out of 4071 patients who were hospitalized with COVID-19, we identified 19 (0.5%) with hemorrhagic stroke. Of all COVID-19 with hemorrhagic stroke, only three had isolated non-aneurysmal SAH with no associated intraparenchymal hemorrhage. Among hemorrhagic stroke in patients with COVID-19, coagulopathy was the most common etiology (73.7%); empiric anticoagulation was started in 89.5% of these patients versus 4.2% in contemporary controls (pâ€‰â‰¤â€‰.001) and 10.0% in historical controls (pâ€‰â‰¤â€‰.001). Compared to contemporary and historical controls, patients with COVID-19 had higher initial NIHSS scores, INR, PTT, and fibrinogen levels. Patients with COVID-19 also had higher rates of in-hospital mortality (84.6% vs. 4.6%, pâ€‰â‰¤â€‰0.001). Sensitivity analyses excluding patients with strictly subarachnoid hemorrhage yielded similar results. CONCLUSION/CONCLUSIONS:We observed an overall low rate of imaging-confirmed hemorrhagic stroke among patients hospitalized with COVID-19. Most hemorrhages in patients with COVID-19 infection occurred in the setting of therapeutic anticoagulation and were associated with increased mortality. Further studies are needed to evaluate the safety and efficacy of therapeutic anticoagulation in patients with COVID-19.
Risk factors for intracerebral hemorrhage in patients with COVID-19
Intracerebral hemorrhage (ICH) can be a devastating complication of coronavirus disease (COVID-19). We aimed to assess risk factors associated with ICH in this population. We performed a retrospective cohort study of adult patients admitted to NYU Langone Health system between March 1 and April 27 2020 with a positive nasopharyngeal swab polymerase chain reaction test result and presence of primary nontraumatic intracranial hemorrhage or hemorrhagic conversion of ischemic stroke on neuroimaging. Patients with intracranial procedures, malignancy, or vascular malformation were excluded. We used regression models to estimate odds ratios and 95% confidence intervals (OR, 95% CI) of the association between ICH and covariates. We also used regression models to determine association between ICH and mortality. Among 3824 patients admitted with COVID-19, 755 patients had neuroimaging and 416 patients were identified after exclusion criteria were applied. The mean (standard deviation) age was 69.3 (16.2), 35.8% were women, and 34.9% were on therapeutic anticoagulation. ICH occurred in 33 (7.9%) patients. Older age, non-Caucasian race, respiratory failure requiring mechanical ventilation, and therapeutic anticoagulation were associated with ICH on univariate analysis (p < 0.01 for each variable). In adjusted regression models, anticoagulation use was associated with a five-fold increased risk of ICH (OR 5.26, 95% CI 2.33-12.24, p < 0.001). ICH was associated with increased mortality (adjusted OR 2.6, 95 % CI 1.2-5.9). Anticoagulation use is associated with increased risk of ICH in patients with COVID-19. Further investigation is required to elucidate underlying mechanisms and prevention strategies in this population.
Fluid attenuation in non-contrast-enhancing tumor (nCET): an MRI Marker for Isocitrate Dehydrogenase (IDH) mutation in Glioblastoma
PURPOSE/OBJECTIVE:The WHO 2016 update classifies glioblastomas (WHO grade IV) according to isocitrate dehydrogenase (IDH) gene mutation status. We aimed to determine MRI-based metrics for predicting IDH mutation in glioblastoma. METHODS:This retrospective study included glioblastoma cases (nâ€‰=â€‰199) with known IDH mutation status and pre-operative MRI (T1WI, T2WI, FLAIR, contrast-enhanced T1W1 at minimum). Two neuroradiologists determined the following MRI metrics: (1) primary lobe of involvement (frontal or non-frontal); (2) presence/absence of contrast-enhancement; (3) presence/absence of necrosis; (4) presence/absence of fluid attenuation in the non-contrast-enhancing tumor (nCET); (5) maximum width of peritumoral edema (cm); (6) presence/absence of multifocal disease. Inter-reader agreement was determined. After resolving discordant measurements, multivariate association between consensus MRI metrics/patient age and IDH mutation status was determined. RESULTS:Among 199 glioblastomas, 16 were IDH-mutant. Inter-reader agreement was calculated for contrast-enhancement (Ä¸â€‰=â€‰0.49 [-Â 0.11-1.00]), necrosis (Ä¸â€‰=â€‰0.55 [0.34-0.76]), fluid attenuation in nCET (Ä¸â€‰=â€‰0.83 [0.68-0.99]), multifocal disease (Ä¸â€‰=â€‰0.55 [0.39-0.70]), and primary lobe (Ä¸â€‰=â€‰0.85 [0.80-0.91]). Mean difference for peritumoral edema width between readers was 0.3Â cm [0.2-0.5], pâ€‰<â€‰0.001. Multivariate analysis uncovered significant associations between IDH-mutation and fluid attenuation in nCET (OR 82.9 [19.22, âˆž], pâ€‰<â€‰0.001), younger age (OR 0.93 [0.86, 0.98], pâ€‰=â€‰0.009), frontal lobe location (OR 11.08 [1.14, 352.97], pâ€‰=â€‰0.037), and less peritumoral edema (OR 0.15 [0, 0.65], pâ€‰=â€‰0.044). CONCLUSIONS:Conventional MRI metrics and patient age predict IDH-mutation status in glioblastoma. Among MRI markers, fluid attenuation in nCET represents a novel marker with high inter-reader agreement that is strongly associated with Glioblastoma, IDH-mutant.
Performance Comparison of Compressed Sensing Algorithms for Accelerating T1Ï Mapping of Human Brain [Editorial]
BACKGROUND:mapping is useful to quantify various neurologic disorders, but data are currently time-consuming to acquire. PURPOSE/OBJECTIVE:mapping of the human brain with acceleration factors (AFs) of 2, 5, and 10. STUDY TYPE/METHODS:Retrospective. SUBJECTS/METHODS:imaging of the whole brain. FIELD STRENGTH/SEQUENCE/UNASSIGNED:preparation module on a clinical 3T scanner. ASSESSMENT/RESULTS:estimation errors were assessed as a function of AF. STATISTICAL TESTS/UNASSIGNED:estimation errors, respectively. Linear regression plots, Bland-Altman plots, and Pearson correlation coefficients (CC) are shown. RESULTS:estimates. DATA CONCLUSION/UNASSIGNED:mapping of the brain. LEVEL OF EVIDENCE/METHODS:2. TECHNICAL EFFICACY STAGE/UNASSIGNED:1.
Functional connectivity of the default mode, dorsal attention and fronto-parietal executive control networks in glial tumor patients
PURPOSE/OBJECTIVE:Resting state functional magnetic resonance imaging (rsfMRI) is an emerging tool to explore the functional connectivity of different brain regions. We aimed to assess the disruption of functional connectivity of the Default Mode Network (DMN), Dorsal Attention Network(DAN) and Fronto-Parietal Network (FPN) in patients with glial tumors. METHODS:rsfMRI data acquired on 3T-MR of treatment-naive glioma patients prospectively recruited (2015-2019) and matched controls from the 1000 functional-connectomes-project were analyzed using the CONN functional toolbox. Seed-Based Connectivity Analysis (SBCA) and Independent Component Analysis (ICA, with 10 to 100 components) were performed to study reliably the three networks of interest. RESULTS:). For the FPN, increased connectivity was noted in the precuneus, posterior cingulate gyrus, and frontal cortex. No difference in the connectivity of the networks of interest was demonstrated between low- and high-grade gliomas, as well as when stratified by their IDH1-R132H (isocitrate dehydrogenase) mutation status. CONCLUSION/CONCLUSIONS:Altered functional connectivity is reliably found with SBCA and ICA in the DMN, DAN, and FPN in glioma patients, possibly explained by decreased connectivity between the cerebral hemispheres across the corpus callosum due to disruption of the connections.
Fully Automated Hybrid Approach to Predict the IDH Mutation Status of Gliomas via Deep Learning and Radiomics
BACKGROUND:Glioma prognosis depends on the isocitrate dehydrogenase (IDH) mutation status. We aimed to predict the IDH status of gliomas from preoperative MR images using a fully automated hybrid approach with convolutional neural networks (CNNs) and radiomics. METHODS:We reviewed 1,166 preoperative MR images of gliomas (grades II-IV) from Severance Hospital (n=856, Severance Set), Seoul National University Hospital (n=107, SNUH set), and The Cancer Imaging Archive (n=203, TCIA set). The Severance set was subdivided into the development (n=727) and internal test (n=129) sets. Based on T1 postcontrast, T2, and fluid-attenuated inversion-recovery images, a fully automated model was developed that comprised a CNN for tumor segmentation (Model 1) and CNN-based classifier for IDH status prediction (Model 2) that uses a hybrid approach based on 2-dimensional tumor images and radiomic features from 3-dimensional tumor shape and loci guided by Model 1. The trained model was tested on internal (a subset of the Severance set) and external (SNUH and TCIA) test sets. RESULTS:The CNN for tumor segmentation (Model 1) achieved a dice coefficient of 0.86-0.92 across datasets. Our hybrid model achieved accuracies of 93.8%, 87.9%, and 78.8%; with areas under the receiver operating characteristic curves of 0.96, 0.94, and 0.86; and areas under the precision-recall curves of 0.88, 0.82, and 0.81 in the internal test, SNUH, and TCIA sets, respectively. CONCLUSIONS:Our fully automated hybrid model demonstrated the potential to be a highly reproducible and generalizable tool across different datasets for the noninvasive prediction of the IDH status of gliomas.