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Isocitrate Dehydrogenase

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A machine learning analysis of a "normal-like" IDH-WT diffuse glioma transcriptomic subgroup associated with prolonged survival reveals novel immune and neurotransmitter-related actionable targets.

BMC medicine
BACKGROUND: Classification of primary central nervous system tumors according to the World Health Organization guidelines follows the integration of histologic interpretation with molecular information and aims at providing the most precise prognosis...

Noninvasive Determination of and 1p19q Status of Lower-grade Gliomas Using MRI Radiomics: A Systematic Review.

AJNR. American journal of neuroradiology
BACKGROUND: Determination of () status and, if -mutant, assessing 1p19q codeletion are an important component of diagnosis of World Health Organization grades II/III or lower-grade gliomas. This has led to research into noninvasively correlating ima...

Qualitative and Quantitative MRI Analysis in IDH1 Genotype Prediction of Lower-Grade Gliomas: A Machine Learning Approach.

BioMed research international
PURPOSE: Preoperative prediction of isocitrate dehydrogenase 1 (IDH1) mutation in lower-grade gliomas (LGGs) is crucial for clinical decision-making. This study aimed to examine the predictive value of a machine learning approach using qualitative an...

Differentiating IDH status in human gliomas using machine learning and multiparametric MR/PET.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: The purpose of this study was to develop a voxel-wise clustering method of multiparametric magnetic resonance imaging (MRI) and 3,4-dihydroxy-6-[F]-fluoro-L-phenylalanine (FDOPA) positron emission tomography (PET) images using an unsuperv...

Generative adversarial network for glioblastoma ensures morphologic variations and improves diagnostic model for isocitrate dehydrogenase mutant type.

Scientific reports
Generative adversarial network (GAN) creates synthetic images to increase data quantity, but whether GAN ensures meaningful morphologic variations is still unknown. We investigated whether GAN-based synthetic images provide sufficient morphologic var...

neoDL: a novel neoantigen intrinsic feature-based deep learning model identifies IDH wild-type glioblastomas with the longest survival.

BMC bioinformatics
BACKGROUND: Neoantigen based personalized immune therapies achieve promising results in melanoma and lung cancer, but few neoantigen based models perform well in IDH wild-type GBM, and the association between neoantigen intrinsic features and prognos...

Machine learning modeling of genome-wide copy number alteration signatures reliably predicts IDH mutational status in adult diffuse glioma.

Acta neuropathologica communications
Knowledge of 1p/19q-codeletion and IDH1/2 mutational status is necessary to interpret any investigational study of diffuse gliomas in the modern era. While DNA sequencing is the gold standard for determining IDH mutational status, genome-wide methyla...

Improving the noninvasive classification of glioma genetic subtype with deep learning and diffusion-weighted imaging.

Neuro-oncology
BACKGROUND: Diagnostic classification of diffuse gliomas now requires an assessment of molecular features, often including IDH-mutation and 1p19q-codeletion status. Because genetic testing requires an invasive process, an alternative noninvasive appr...