Improved Glioma Grading Using Deep Convolutional Neural Networks
Editor’s Choice Convolutional neural networks are able to learn discriminating features automatically, and these features provide added value for grading gliomas.
Centrally Reduced Diffusion Sign for Differentiation between Treatment-Related Lesions and Glioma Progression: A Validation Study
Editor’s Choice Images of 231 patients who underwent an operation for suspected glioma recurrence were reviewed. Patients with susceptibility artifacts or without central necrosis were excluded. The final diagnosis was established according to histopathology reports. Two neuroradiologists classified the diffusion
Performance of Standardized Relative CBV for Quantifying Regional Histologic Tumor Burden in Recurrent High-Grade Glioma: Comparison against Normalized Relative CBV Using Image-Localized Stereotactic Biopsies
Editor’s Choice This study compares the predictive performance of relative CBV standardization against relative CBV normalization for quantifying recurrent tumor burden in high-grade gliomas relative to posttreatment radiation effects. The authors recruited 38 previously treated patients with high-grade gliomas (World
Deep Transfer Learning and Radiomics Feature Prediction of Survival of Patients with High-Grade Gliomas
Fellows’ Journal Club Fifty patients with high-grade gliomas from the authors’ hospital and 128 patients with high-grade gliomas from The Cancer Genome Atlas were included in this study. For each patient, the authors calculated 348 hand-crafted radiomics features and 8192
Whole-Tumor Histogram and Texture Analyses of DTI for Evaluation of IDH1-Mutation and 1p/19q-Codeletion Status in World Health Organization Grade II Gliomas
Fellows’ Journal Club Ninety-three patients with World Health Organization grade II gliomas with known IDH-mutation and 1p/19q-codeletion status (18 IDH1 wild-type, 45 IDH1-mutant and no 1p/19q codeletion, 30 IDH-mutant and 1p/19q codeleted tumors) underwent DTI. ROIs were drawn on every section of the T2-weighted images
MR Elastography Analysis of Glioma Stiffness and IDH1-Mutation Status
Editor’s Choice Tumor stiffness properties were prospectively quantified in 18 patients with histologically proved gliomas using MR elastography. Images were acquired on a 3T MR imaging unit with a vibration frequency of 60 Hz. Tumor stiffness was compared with unaffected
Real-Time Motor Cortex Mapping for the Safe Resection of Glioma: An Intraoperative Resting-State fMRI Study
Editor’s Choice The authors conducted preoperative and intraoperative resting-state intrinsic functional connectivity analyses of the motor cortex in 30 patients with brain tumors. Factors that may influence intraoperative imaging quality, including anesthesia type and tumor cavity, were studied. Additionally, direct
3D Pseudocontinuous Arterial Spin-Labeling MR Imaging in the Preoperative Evaluation of Gliomas
Editor’s Choice Fifty-eight patients with pathologically confirmed gliomas underwent preoperative 3D pseudocontinuous arterial spin-labeling and ROC curves were generated for parameters to distinguish high-grade from low-grade gliomas. Both maximum CBF and maximum relative CBF were significantly higher in high-grade than
Differentiation of Enhancing Glioma and Primary Central Nervous System Lymphoma by Texture-Based Machine Learning
Fellows’ Journal Club The authors evaluated the diagnostic performance of a machine-learning algorithm by using texture analysis of contrast-enhanced T1-weighted images for differentiation of primary central nervous system lymphoma (n=35) and enhancing glioma (n=71). The mean areas under the receiver
Journal Scan – This Month in Other Journals, November 2015
Please check out the accompanying podcast of this blog post (also known as “Annotated Bibliography”): Crowley RW, Ducruet AF, Kalani MYS, Kim LJ, Albuquerque FC, McDougall CG. Neurological morbidity and mortality associated with the endovascular treatment of cerebral arteriovenous malformations
