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Lower-grade gliomas (WHO grade II/III) have been classified into clinically relevant molecular subtypes based on and 1p/19q mutation status. The purpose was to investigate whether T2/FLAIR MRI features could distinguish between lower-grade glioma molecular subtypes. MRI scans from the TCGA/TCIA lower grade glioma database ( = 125) were evaluated by two independent neuroradiologists to assess (i) presence/absence of homogenous signal on T2WI; (ii) presence/absence of "T2-FLAIR mismatch" sign; (iii) sharp or indistinct lesion margins; and (iv) presence/absence of peritumoral edema. Metrics with moderate-substantial agreement underwent consensus review and were correlated with glioma molecular subtypes. Somatic mutation, DNA copy number, DNA methylation, gene expression, and protein array data from the TCGA lower-grade glioma database were analyzed for molecular-radiographic associations. A separate institutional cohort ( = 82) was analyzed to validate the T2-FLAIR mismatch sign. Among TCGA/TCIA cases, interreader agreement was calculated for lesion homogeneity [ = 0.234 (0.111-0.358)], T2-FLAIR mismatch sign [ = 0.728 (0.538-0.918)], lesion margins [ = 0.292 (0.135-0.449)], and peritumoral edema [ = 0.173 (0.096-0.250)]. All 15 cases that were positive for the T2-FLAIR mismatch sign were -mutant, 1p/19q non-codeleted tumors ( < 0.0001; PPV = 100%, NPV = 54%). Analysis of the validation cohort demonstrated substantial interreader agreement for the T2-FLAIR mismatch sign [ = 0.747 (0.536-0.958)]; all 10 cases positive for the T2-FLAIR mismatch sign were -mutant, 1p/19q non-codeleted tumors ( < 0.00001; PPV = 100%, NPV = 76%). Among lower-grade gliomas, T2-FLAIR mismatch sign represents a highly specific imaging biomarker for the -mutant, 1p/19q non-codeleted molecular subtype..

SUMMARY: Autoimmune encephalitis is a relatively new category of immune-mediated disease involving the central nervous system that demonstrates a widely variable spectrum of clinical presentations, ranging from the relatively mild or insidious onset of cognitive impairment to more complex forms of encephalopathy with refractory seizure. Due to its diverse clinical features, which can mimic a variety of other pathologic processes, autoimmune encephalitis presents a diagnostic challenge to clinicians. Imaging findings in patients with these disorders can also be quite variable, but recognizing characteristic findings within limbic structures suggestive of autoimmune encephalitis can be a key step in alerting clinicians to the potential diagnosis and ensuring a prompt and appropriate clinical work-up. In this article, we review antibody-mediated encephalitis and its various subtypes with a specific emphasis on the role of neuroimaging in the diagnostic work-up. ABBREVIATIONS:

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Adult diffuse gliomas are a diverse group of brain neoplasms that inflict a high emotional toll on patients and their families. The Cancer Genome Atlas and similar projects have provided a comprehensive understanding of the somatic alterations and molecular subtypes of glioma at diagnosis. However, gliomas undergo significant cellular and molecular evolution during disease progression. We review the current knowledge on the genomic and epigenetic abnormalities in primary tumors and after disease recurrence, highlight the gaps in the literature, and elaborate on the need for a new multi-institutional effort to bridge these knowledge gaps and how the Glioma Longitudinal Analysis Consortium (GLASS) aims to systemically catalog the longitudinal changes in gliomas. The GLASS initiative will provide essential insights into the evolution of glioma toward a lethal phenotype, with the potential to reveal targetable vulnerabilities and, ultimately, improved outcomes for a patient population in need.

Coronavirus disease 2019 (COVID-19) is associated with a severe inflammatory response. Inflammation affects atherosclerotic plaque vulnerability and promotes a thrombogenic environment. We report a series of 6 patients with COVID-19 with acute ischemic stroke due to intraluminal carotid artery thrombus presenting during an 8-day period. Six patients were included (5 men) with a mean age of 65.8 years (range, 55-78 years). COVID-19 was diagnosed by detection of Severe Acute Respiratory Syndrome coronavirus 2 in 5 patients and was presumed due to typical clinical and imaging findings in 1 patient. All patients had vascular risk factors including diabetes (83%), hyperlipidemia (100%), and smoking (17%). Four patients presented with large infarcts with initial NIHSS scores of 24-30. During their hospitalization, all patients had elevated D-dimer and C-reactive protein levels, 5 patients had elevated lactate dehydrogenase and ferritin levels, 3 had elevated interleukin-6 levels, and 2 had elevated troponin levels. Inflammation related to COVID-19 may result in rupture of vulnerable atherosclerotic plaques, resulting in thrombosis and acute ischemic stroke.

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Background and Purpose Texture analysis has been applied to medical images to assist in tumor tissue classification and characterization. In this study, we obtained textural features from parametric (rCBV) maps of dynamic susceptibility contrast-enhanced magnetic resonance imaging images in glioblastoma and assessed their relationship with patient survival. Materials and Methods MR perfusion data of 24 patients with glioblastoma from the Cancer Genome Atlas was analyzed in this study. One- and two-dimensional texture feature ratios as well as kinetic textural features based on rCBV values in the contrast-enhancing lesion and the non-enhancing lesion of the tumor were obtained. Receiver Operating Characteristic, Kaplan-Meier analysis, and multivariate Cox proportional hazards regression analyses were used to assess the relationship between texture feature ratios and overall survival. Results Several feature ratios are capable of stratifying survival in a statistically significant manner. These feature ratios correspond to homogeneity (p=0.008, based on log-rank test), angular second moment(p=0.003), inverse difference moment(p=0.013) and entropy(p=0.008). Multivariate Cox proportional hazards regression analysis showed that homogeneity, angular second moment, inverse difference moment, and entropy from the contrast-enhancing lesion are significantly associated with overall survival. For the non-enhancing lesion, skewness and variance ratios of rCBV texture were associated with OS in a statistically significant manner. For the kinetic texture analysis, the Haralick correlation feature showed a p-value close to 0.05. Conclusion Our study reveals that texture feature ratios from contrast-enhancing and non-enhancing lesion and kinetic texture analysis obtained from perfusion parametric maps provide useful information for predicting the survival in the patients with glioblastoma.