Integration of Radiomic and Multi-omic Analyses Predicts Survival of Newly Diagnosed IDH1 Wild-Type Glioblastoma

Radiomics in Glioblastoma: Current Status and Challenges Facing Clinical Implementation

(2019) Ahmad Chaddad et al.   Frontiers in Oncology

Prediction of survival with multi-scale radiomic analysis in glioblastoma patients

(2018) Ahmad Chaddad et al.   MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING

In vivo evaluation of EGFRvIII mutation in primary glioblastoma patients via complex multiparametric MRI signature

(2018) Hamed Akbari et al.   NEURO-ONCOLOGY

Radiomic MRI signature reveals three distinct subtypes of glioblastoma with different clinical and molecular characteristics, offering prognostic value beyond IDH1

(2018) Saima Rathore et al.   Scientific Reports

Novel Radiomic Features based on Joint Intensity Matrices for Predicting Glioblastoma Patient Survival Time

(2018) Ahmad Chaddad et al.   IEEE Journal of Biomedical and Health Informatics

Quantitative imaging biomarkers for risk stratification of patients with recurrent glioblastoma treated with bevacizumab

(2017) Patrick Grossmann et al.   NEURO-ONCOLOGY

Radiomic subtyping improves disease stratification beyond key molecular, clinical, and standard imaging characteristics in patients with glioblastoma

(2017) Philipp Kickingereder et al.   NEURO-ONCOLOGY

MRI features predict survival and molecular markers in diffuse lower-grade gliomas

(2017) Hao Zhou et al.   NEURO-ONCOLOGY

Predicting survival time of lung cancer patients using radiomic analysis

(2017) Ahmad Chaddad et al.   Oncotarget

Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features

(2017) Spyridon Bakas et al.   Scientific Data

Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age

(2017) Ahmad Chaddad et al.   Scientific Reports

Imaging-genomics reveals driving pathways of MRI derived volumetric tumor phenotype features in Glioblastoma

(2016) Patrick Grossmann et al.   BMC CANCER

A quantitative study of shape descriptors from glioblastoma multiforme phenotypes for predicting survival outcome

(2016) Ahmad Chaddad et al.   BRITISH JOURNAL OF RADIOLOGY

Large-scale Radiomic Profiling of Recurrent Glioblastoma Identifies an Imaging Predictor for Stratifying Anti-Angiogenic Treatment Response

(2016) P. Kickingereder et al.   CLINICAL CANCER RESEARCH

Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings

(2016) Prateek Prasanna et al.   EUROPEAN RADIOLOGY

Extracted magnetic resonance texture features discriminate between phenotypes and are associated with overall survival in glioblastoma multiforme patients

(2016) Ahmad Chaddad et al.   MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING

Advances in the molecular genetics of gliomas — implications for classification and therapy

(2016) Guido Reifenberger et al.   Nature Reviews Clinical Oncology

Multimodal MRI features predict isocitrate dehydrogenase genotype in high-grade gliomas

(2016) Biqi Zhang et al.   NEURO-ONCOLOGY

Somatic mutations associated with MRI-derived volumetric features in glioblastoma

(2015) David A. Gutman et al.   NEURORADIOLOGY

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

(2015) Jeanette E. Eckel-Passow et al.   NEW ENGLAND JOURNAL OF MEDICINE

Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas

(2015)   NEW ENGLAND JOURNAL OF MEDICINE

Comparison of radiation regimens in the treatment of Glioblastoma multiforme: results from a single institution

(2015) Melissa Azoulay et al.   Radiation Oncology

Glioblastoma: Imaging Genomic Mapping Reveals Sex-specific Oncogenic Associations of Cell Death

(2015) Rivka R. Colen et al.   RADIOLOGY

Machine Learning methods for Quantitative Radiomic Biomarkers

(2015) Chintan Parmar et al.   Scientific Reports

Random survival forests for competing risks

(2014) H. Ishwaran et al.   BIOSTATISTICS

Imaging genomic mapping of an invasive MRI phenotype predicts patient outcome and metabolic dysfunction: a TCGA glioma phenotype research group project

(2014) Rivka R Colen et al.   BMC Medical Genomics

Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal

(2013) J. Gao et al.   Science Signaling

Somatic Mutations of PIK3R1 Promote Gliomagenesis

(2012) Steven N. Quayle et al.   PLoS One

Isocitrate dehydrogenase mutations in gliomas

(2011) Changcun Guo et al.   CURRENT OPINION IN NEUROLOGY

Imaging parameters of high grade gliomas in relation to the MGMT promoter methylation status: the CT, diffusion tensor imaging, and perfusion MR imaging

(2011) Won-Jin Moon et al.   NEURORADIOLOGY

COMPUTATION OF MINKOWSKI MEASURES ON 2D AND 3D BINARY IMAGES

(2011) David Legland et al.   Image Analysis & Stereology

The prognostic IDH1 R132 mutation is associated with reduced NADP+-dependent IDH activity in glioblastoma

(2010) Fonnet E. Bleeker et al.   ACTA NEUROPATHOLOGICA

Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1

(2010) Roel G.W. Verhaak et al.   CANCER CELL

Classification of brain tumor type and grade using MRI texture and shape in a machine learning scheme

(2009) Evangelia I. Zacharaki et al.   MAGNETIC RESONANCE IN MEDICINE

An analysis of image texture, tumor location, and MGMT promoter methylation in glioblastoma using magnetic resonance imaging

(2009) Sylvia Drabycz et al.   NEUROIMAGE

Empirical characterization of random forest variable importance measures

(2007) Kellie J. Archer et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS