Faculty Bibliography

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 (p ≤ .001) and 10.0% in historical controls (p ≤ .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%, p ≤ 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.

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 (n = 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 (ĸ = 0.49 [- 0.11-1.00]), necrosis (ĸ = 0.55 [0.34-0.76]), fluid attenuation in nCET (ĸ = 0.83 [0.68-0.99]), multifocal disease (ĸ = 0.55 [0.39-0.70]), and primary lobe (ĸ = 0.85 [0.80-0.91]). Mean difference for peritumoral edema width between readers was 0.3 cm [0.2-0.5], p < 0.001. Multivariate analysis uncovered significant associations between IDH-mutation and fluid attenuation in nCET (OR 82.9 [19.22, ∞], p < 0.001), younger age (OR 0.93 [0.86, 0.98], p = 0.009), frontal lobe location (OR 11.08 [1.14, 352.97], p = 0.037), and less peritumoral edema (OR 0.15 [0, 0.65], p = 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.

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.

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.

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.

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.

BACKGROUND AND PURPOSE/OBJECTIVE:Various patterns of leukoencephalopathy have been described in coronavirus disease 2019 (COVID-19). In this article, we aimed to describe the clinical and imaging features of acute disseminated leukoencephalopathy in critically ill patients with COVID-19 and the imaging evolution during a short-term follow-up. MATERIALS AND METHODS/METHODS:We identified and reviewed the clinical data, laboratory results, imaging findings, and outcomes for 8 critically ill patients with COVID-19 with acute disseminated leukoencephalopathy. RESULTS:All patients demonstrated multiple areas of white matter changes in both cerebral hemispheres; 87.5% (7/8) of patients had a posterior predilection. Four patients (50%) had short-term follow-up imaging within a median of 17 days after the first MR imaging; they developed brain atrophy, and their white matter lesions evolved into necrotizing cystic cavitations. All (8/8) patients had inflammatory cytokine release syndrome as demonstrated by elevated interleukin-6, D-dimer, lactate dehydrogenase, erythrocyte sedimentation rate, C-reactive protein, and ferritin levels. Most (7/8; 87.5%) patients were on prolonged ventilator support (median, 44.5 days; interquartile range, 20.5 days). These patients had poor functional outcomes (6/8 [75%] patients were discharged with mRS 5) and high mortality (2/8, 25%). CONCLUSIONS:Critically ill patients with COVID-19 can develop acute disseminated leukoencephalopathy that evolves into cystic degeneration of white matter lesions with brain atrophy during a short period, which we dubbed virus-associated necrotizing disseminated acute leukoencephalopathy. This may be the result of COVID-19-related endothelial injury, cytokine storm, or thrombotic microangiopathy.

OBJECTIVES/OBJECTIVE:Isocitrate dehydrogenase wild-type (IDHwt) lower-grade gliomas of histologic grades II and III follow heterogeneous clinical outcomes, which necessitates risk stratification. We aimed to evaluate whether radiomics from MRI would allow prediction of overall survival in patients with IDHwt lower-grade gliomas and to investigate the added prognostic value of radiomics over clinical features. METHODS:Preoperative MRIs of 117 patients with IDHwt lower-grade gliomas from January 2007 to February 2018 were retrospectively analyzed. The external validation cohort consisted of 33 patients from The Cancer Genome Atlas. A total of 182 radiomic features were extracted. Radiomics risk scores (RRSs) for overall survival were derived from the least absolute shrinkage and selection operator (LASSO) and elastic net. Multivariable Cox regression analyses, including clinical features and RRSs, were performed. The integrated areas under the receiver operating characteristic curves (iAUCs) from models with and without RRSs were calculated for comparisons. The prognostic value of RRS was assessed in the validation cohort. RESULTS:The RRS derived from LASSO and elastic net independently predicted survival with hazard ratios of 9.479 (95% confidence interval [CI], 3.220-27.847) and 6.148 (95% CI, 3.009-12.563), respectively. Those RRSs enhanced model performance for predicting overall survival (iAUC increased to 0.780-0.797 from 0.726), which was externally validated. The RRSs stratified IDHwt lower-grade gliomas in the validation cohort with significantly different survival. CONCLUSION/CONCLUSIONS:Radiomics has the potential for noninvasive risk stratification and can improve prediction of overall survival in patients with IDHwt lower-grade gliomas when integrated with clinical features. KEY POINTS/CONCLUSIONS:• Isocitrate dehydrogenase wild-type lower-grade gliomas with histologic grades II and III follow heterogeneous clinical outcomes, which necessitates further risk stratification. • Radiomics risk scores derived from MRI independently predict survival even after incorporating strong clinical prognostic features (hazard ratios 6.148-9.479). • Radiomics risk scores derived from MRI have the potential to improve survival prediction when added to clinical features (integrated areas under the receiver operating characteristic curves increased from 0.726 to 0.780-0.797).