Abudumijiti Aibaidula

TL;DR: The data illustrate that IDH mutant lower grade astrocytomas is not a homogeneous group and should be molecularly stratified for risk, and these alterations occurred in a mutually exclusive fashion.

TL;DR: A new deep learning-based OS prediction method for GBM patients, which can derive tumor genotype-related features from pre-operative multimodal magnetic resonance imaging (MRI) brain data and feed them to OS prediction, achieves the highest OS prediction accuracy compared to other state-of-the-art methods.

TL;DR: A new model of the squeeze-and-excitation block DenseNet with weighted cross-entropy (named SD-Net_WCE) is developed for the glioma classification task, which is capable of solving multiple classification tasks and can satisfactorily able to classifyglioma subtypes.

TL;DR: Survival analysis revealed that TERTp mutation, H3F3A mutation, and ATRX loss were significantly associated with poor PFS, and it was shown that these molecular biomarkers can be used to stratify PLGGs into low- (KIAA1549-BRAF fusion or MYB amplification), intermediate-I, intermediate-II, and high-risk groups with distinct PFS.

TL;DR: It is demonstrated that not all 1p/19q intact oligodendroglial tumors are astrocytic and co-evaluation of IDH and TERTp mutation could potentially serve as an adjunct for diagnosing 1p/.