☆ 4.6 Article

Prediction of the Molecular Subtype of IDH Mutation Combined with MGMT Promoter Methylation in Gliomas via Radiomics Based on Preoperative MRI

CANCERS (2023)

Related references

Note: Only part of the references are listed.

Article Oncology

Distribution and favorable prognostic implication of genomic EGFR alterations in IDH-wildtype glioblastoma

Nayuta Higa et al.

Summary: The study evaluated the mutation profile of the EGFR gene in IDH-wildtype GBMs and found that EGFR alterations are good prognostic markers of overall survival. Also, rare EGFR variants with longitudinal and temporal transformations of EGFRvIII were identified.

CANCER MEDICINE (2023)

Add to Collection

Article Computer Science, Interdisciplinary Applications

A Fully Automated Multimodal MRI-Based Multi-Task Learning for Glioma Segmentation and IDH Genotyping

Jianhong Cheng et al.

Summary: Accurate prediction of isocitrate dehydrogenase (IDH) mutation and glioma segmentation is crucial for computer-aided diagnosis using preoperative multimodal magnetic resonance imaging (MRI). Existing methods often address these tasks separately and overlook the correlation between them. Furthermore, the limited availability of IDH mutation data hampers modeling. In this paper, we propose a fully automated multimodal MRI-based multi-task learning framework that simultaneously performs glioma segmentation and IDH genotyping. Our framework combines a hybrid CNN-Transformer encoder with a multi-scale classifier to extract shared spatial and global information for segmentation and genotyping. A multi-task learning loss is designed to balance the two tasks, while an uncertainty-aware pseudo-label selection method improves the accuracy of IDH genotyping with semi-supervised learning. Experimental results on a multi-institutional public dataset demonstrate the promising performance of our proposed method compared to single-task learning and existing state-of-the-art methods. The availability of unlabeled data further enhances the performance of glioma segmentation and IDH genotyping. The source codes of our framework are publicly available.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2022)

Add to Collection

Article Oncology

Therapy for Diffuse Astrocytic and Oligodendroglial Tumors in Adults: ASCO-SNO Guideline

Nimish A. Mohile et al.

Summary: This article provides guidance on the therapy for diffuse astrocytic and oligodendroglial tumors in adults. The recommendations are based on a systematic literature review and offer specific treatment options for different tumor grades, with reasonable alternatives. The article also provides treatment suggestions for specific patient populations.

JOURNAL OF CLINICAL ONCOLOGY (2022)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Radiomics Profiling Identifies the Incremental Value of MRI Features beyond Key Molecular Biomarkers for the Risk Stratification of High-Grade Gliomas

Guoqiang Yang et al.

Summary: This study aimed to identify the incremental value of magnetic resonance imaging (MRI) features for risk stratification in patients with high-grade gliomas (HGGs). Radiomic features were extracted and a prognostic model was established, showing that the model can effectively differentiate risk subgroups. These MRI features have incremental value in providing preoperative basis for personalized diagnosis and treatment decision-making.

CONTRAST MEDIA & MOLECULAR IMAGING (2022)

Add to Collection

Review Clinical Neurology

Clinical implications of the 2021 edition of the WHO classification of central nervous system tumours

Craig Horbinski et al.

Summary: The fifth edition of the WHO classification of CNS tumours, published in 2021, incorporates major changes in the classification system. This new edition includes more molecular alterations in tumor diagnosis and reorganizes the classification of gliomas and ependymomas. Several new tumor entities, especially pediatric tumors, are added to the 2021 classification. This significant revision will have a major impact on the diagnosis and treatment of CNS tumors.

NATURE REVIEWS NEUROLOGY (2022)

Add to Collection

Review Oncology

World Health Organization 2021 Classification of Central Nervous System Tumors and Implications for Therapy for Adult-Type Gliomas A Review

Tamar R. Berger et al.

Summary: The 2021 World Health Organization central nervous system tumor classification is a major advance toward improving the diagnosis of brain tumors, providing more accurate guidance on prognosis and therapy selection, and facilitating the development of more effective treatments through enrollment of homogeneous patient populations in clinical trials.

JAMA ONCOLOGY (2022)

Add to Collection

Article Oncology

Imaging Glioblastoma Metabolism by Using Hyperpolarized [1-13C]Pyruvate Demonstrates Heterogeneity in Lactate Labeling: A Proof of Principle Study

Fulvio Zaccagna et al.

Summary: This study used hyperpolarized C-13 MRI to evaluate glioblastoma metabolism and found variations in lactate labeling within and between tumors, while bicarbonate labeling was consistently lower in the surrounding normal brain parenchyma.

RADIOLOGY-IMAGING CANCER (2022)

Add to Collection

Review Oncology

World Health Organization 2021 Classification of Central Nervous System Tumors and Implications for Therapy for Adult-Type Gliomas A Review

Tamar R. Berger et al.

Summary: The fifth edition of the Classification of Tumors of the Central Nervous System published by the World Health Organization in 2021 represents a significant improvement in the classification of brain tumors, incorporating molecular pathogenesis and histopathology to provide more accurate guidance on prognosis and therapy. This revision, particularly for gliomas, separates adult and pediatric tumors based on molecular differences and prognosis, consolidates adult-type diffuse gliomas into 3 types, and emphasizes the importance of IDH mutation status in tumor classification.

JAMA ONCOLOGY (2022)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Automated machine learning to predict the co-occurrence of isocitrate dehydrogenase mutations and O6-methylguanine-DNA methyltransferase promoter methylation in patients with gliomas

Simin Zhang et al.

Summary: The study aimed to predict the co-occurrence of IDHmut and MGMTmet in gliomas using radiomics features from MRI, and found that high discriminatory accuracy was achieved with the use of automated machine learning methods.

JOURNAL OF MAGNETIC RESONANCE IMAGING (2021)

Add to Collection

Article Oncology

Low MGMT digital expression is associated with a better outcome of IDH1 wildtype glioblastomas treated with temozolomide

Isabella Gomes et al.

Summary: The study found that MGMTp methylation was closely associated with TMZ treatment response, MGMT expression was negatively correlated with MGMTp methylation, and low MGMT expression was significantly associated with better patient survival.

JOURNAL OF NEURO-ONCOLOGY (2021)

Add to Collection

Article Oncology

CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2014-2018

Quinn T. Ostrom et al.

Summary: The report from CBTRUS provides the most up-to-date population-based data on primary brain tumors in the United States, including incidence rates, mortality rates, and survival rates for both malignant and non-malignant tumors.

NEURO-ONCOLOGY (2021)

Add to Collection

Review Clinical Neurology

Machine Learning for the Prediction of Molecular Markers in Glioma on Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis

Anne Jian et al.

Summary: Machine learning models show good performance in predicting molecular subtyping of gliomas, especially for predicting IDH mutation, MGMT methylation, and 1p/19q codeletion with high accuracy. Data augmentation and MRI sequence type are weakly associated with heterogeneity.

NEUROSURGERY (2021)

Add to Collection

Article Clinical Neurology

TERT promoter mutation status is necessary and sufficient to diagnose IDH-wildtype diffuse astrocytic glioma with molecular features of glioblastoma

Kenji Fujimoto et al.

Summary: This study found that in IDH-wildtype lower grade gliomas, the pTERT mutation is a significant predictor of poor prognosis, while both EGFR amplification and PDGFRA gain also play important roles in prognosis.

ACTA NEUROPATHOLOGICA (2021)

Add to Collection

Review Oncology

The 2021 WHO Classification of Tumors of the Central Nervous System: a summary

David N. Louis et al.

Summary: The fifth edition of the WHO Classification of Tumors of the Central Nervous System integrates molecular diagnostics into CNS tumor classification, introduces different approaches to tumor nomenclature and grading, and emphasizes the importance of integrated diagnoses and layered reports.

NEURO-ONCOLOGY (2021)

Add to Collection

Article Oncology

Predictive value of MGMT promoter methylation on the survival of TMZ treated IDH-mutant glioblastoma

Ruichao Chai et al.

Summary: The study investigated the role of MGMT promoter methylation in IDH-mutant glioblastoma, finding it to have predictive value with a cutoff value higher than that for IDH-wildtype glioblastoma.

CANCER BIOLOGY & MEDICINE (2021)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Predicting Isocitrate Dehydrogenase (IDH) Mutation Status in Gliomas Using Multiparameter MRI Radiomics Features

Hong Peng et al.

Summary: The study aimed to establish a model for classifying IDH status in gliomas based on multiparametric MRI, and found that radiomics features can identify IDH genotypes in gliomas.

JOURNAL OF MAGNETIC RESONANCE IMAGING (2021)

Add to Collection

Article Oncology

被撤回的出版物: A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas (Retracted article. See vol. 25, pg. 1197, 2023)

Chandan Ganesh Bangalore Yogananda et al.

NEURO-ONCOLOGY (2020)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Diffusion- and perfusion-weighted MRI radiomics model may predict isocitrate dehydrogenase (IDH) mutation and tumor aggressiveness in diffuse lower grade glioma

Minjae Kim et al.

EUROPEAN RADIOLOGY (2020)

Add to Collection

Review Oncology

IDH mutation in glioma: molecular mechanisms and potential therapeutic targets

Sue Han et al.

BRITISH JOURNAL OF CANCER (2020)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Machine and deep learning methods for radiomics

Michele Avanzo et al.

MEDICAL PHYSICS (2020)

Add to Collection

Review Radiology, Nuclear Medicine & Medical Imaging

A review of original articles published in the emerging field of radiomics

Jiangdian Song et al.

EUROPEAN JOURNAL OF RADIOLOGY (2020)

Add to Collection

Review Radiology, Nuclear Medicine & Medical Imaging

Radiomics in medical imaging-how-to guide and critical reflection

Janita E. van Timmeren et al.

INSIGHTS INTO IMAGING (2020)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

A multi-sequence and habitat-based MRI radiomics signature for preoperative prediction of MGMT promoter methylation in astrocytomas with prognostic implication

Jingwei Wei et al.

EUROPEAN RADIOLOGY (2019)

Add to Collection

Review Oncology

Risk factors for childhood and adult primary brain tumors

Quinn T. Ostrom et al.

NEURO-ONCOLOGY (2019)

Add to Collection

Article Computer Science, Information Systems

Geometric SMOTE a geometrically enhanced drop-in replacement for SMOTE

Georgios Douzas et al.

INFORMATION SCIENCES (2019)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Fusion Radiomics Features from Conventional MRI Predict MGMT Promoter Methylation Status in Lower Grade Gliomas

Chendan Jiang et al.

EUROPEAN JOURNAL OF RADIOLOGY (2019)

Add to Collection

Article Computer Science, Information Systems

A Comprehensive Analysis of Synthetic Minority Oversampling Technique (SMOTE) for handling class imbalance

Dina Elreedy et al.

INFORMATION SCIENCES (2019)

Add to Collection

Review Medicine, Research & Experimental

The Applications of Radiomics in Precision Diagnosis and Treatment of Oncology: Opportunities and Challenges

Zhenyu Liu et al.

THERANOSTICS (2019)

Add to Collection

Review Oncology

Tumour heterogeneity and resistance to cancer therapies

Ibiayi Dagogo-Jack et al.

NATURE REVIEWS CLINICAL ONCOLOGY (2018)

Add to Collection

Article Radiology, Nuclear Medicine & Medical Imaging

Multiregional radiomics features from multiparametric MRI for prediction of MGMT methylation status in glioblastoma multiforme: A multicentre study

Zhi-Cheng Li et al.

EUROPEAN RADIOLOGY (2018)

Add to Collection

Article Computer Science, Artificial Intelligence

SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary

Alberto Fernandez et al.

JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH (2018)

Add to Collection

Article Multidisciplinary Sciences

Concordant association validates MGMT methylation and protein expression as favorable prognostic factors in glioma patients on alkylating chemotherapy (Temozolomide)

Arshad A. Pandith et al.

SCIENTIFIC REPORTS (2018)

Add to Collection

Review Oncology

Association of MGMT Promoter Methylation Status With Survival Outcomes in Patients With High-Risk Glioma Treated With Radiotherapy and Temozolomide An Analysis From the NRG Oncology/RTOG 0424 Trial

Erica H. Bell et al.

JAMA ONCOLOGY (2018)

Add to Collection

Article Oncology

CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2011-2015

Quinn T. Ostrom et al.

NEURO-ONCOLOGY (2018)

Add to Collection

Review Clinical Neurology

Glioma Subclassifications and Their Clinical Significance

Ricky Chen et al.

NEUROTHERAPEUTICS (2017)

Add to Collection

Article Medicine, General & Internal

Glioma Groups Based on 1p/19q, IDH, and TERT Promoter Mutations in Tumors

Jeanette E. Eckel-Passow et al.

NEW ENGLAND JOURNAL OF MEDICINE (2015)

Add to Collection

Review Clinical Neurology

MGMT testing-the challenges for biomarker-based glioma treatment

Wolfgang Wick et al.

NATURE REVIEWS NEUROLOGY (2014)

Add to Collection

Article Oncology

The combination of IDH1 mutations and MGMT methylation status predicts survival in glioblastoma better than either IDH1 or MGMT alone

Remco J. Molenaar et al.

NEURO-ONCOLOGY (2014)

Add to Collection

Article Clinical Neurology

ATRX loss refines the classification of anaplastic gliomas and identifies a subgroup of IDH mutant astrocytic tumors with better prognosis

Benedikt Wiestler et al.

ACTA NEUROPATHOLOGICA (2013)

Add to Collection

Article Oncology

IDH/MGMT-driven molecular classification of low-grade glioma is a strong predictor for long-term survival

Severina Leu et al.

NEURO-ONCOLOGY (2013)

Add to Collection

Article Clinical Neurology

Prognostic or predictive value of MGMT promoter methylation in gliomas depends on IDH1 mutation

Wolfgang Wick et al.

NEUROLOGY (2013)

Add to Collection

Article Clinical Neurology

Patients with IDH1 wild type anaplastic astrocytomas exhibit worse prognosis than IDH1-mutated glioblastomas, and IDH1 mutation status accounts for the unfavorable prognostic effect of higher age: implications for classification of gliomas

Christian Hartmann et al.

ACTA NEUROPATHOLOGICA (2010)

Add to Collection

Article Oncology

Diagnostic, treatment, and demographic factors influencing survival in population-based adult glioma patients in the San Francisco Bay area

M Wrensch et al.

NEURO-ONCOLOGY (2006)

Add to Collection

Article Oncology

Factors influencing survival in high-grade gliomas

JC Buckner

SEMINARS IN ONCOLOGY (2003)

Add to Collection

© Peeref 2019-2024. All rights reserved.