Synthesizing Contrast-Enhanced MR Images from Noncontrast MR Images Using Deep Learning.

Background And Purpose: Recent developments in deep learning methods offer a potential solution to the need for alternative imaging methods due to concerns about the toxicity of gadolinium-based contrast agents. The purpose of the study was to synthesize virtual gadolinium contrast-enhanced T1-weighted MR images from noncontrast multiparametric MR images in patients with primary brain tumors by using deep learning.

Materials And Methods: We trained and validated a deep learning network by using MR images from 335 subjects in the Brain Tumor Segmentation Challenge 2019 training data set.

Alterations in the RB Pathway With Inactivation of RB1 Characterize Glioblastomas With a Primitive Neuronal Component.

A primitive neuronal component is a feature of some glioblastomas but defining molecular alterations of this histologic variant remains uncertain. We performed next-generation sequencing of 1500 tumor related genes on tissue from 9 patients with glioblastoma with a primitive component (G/PN) and analyzed 27 similar cases from the Cancer Genome Atlas (TCGA) dataset. Alterations in the RB pathway were identified in all of our patients' tumors and 81% of TCGA tumors with the retinoblastoma tumor suppressor gene (RB1) commonly affected.

Neurological emergencies associated with COVID-19: stroke and beyond.

Novel coronavirus disease (COVID-19) was declared a global pandemic on March 1, 2020. Neurological manifestations are now being reported worldwide, including emergent presentation with acute neurological changes as well as a comorbidity in hospitalized patients. There is limited knowledge on the neurologic manifestations of COVID-19 at present, with a wide array of neurological complications reported, ranging from ischemic stroke to acute demyelination and encephalitis.