Integration of machine learning and mechanistic models accurately predicts variation in cell density of glioblastoma using multiparametric MRI

COMP-05. EVALUATION OF A DEEP LEARNING ARCHITECTURE FOR MRI PREDICTION OF IDH, 1p19q AND TERT IN GLIOMA PATIENTS

(2018) Panagiotis Korfiatis et al.   NEURO-ONCOLOGY

Deep Learning based Radiomics (DLR) and its usage in noninvasive IDH1 prediction for low grade glioma

(2017) Zeju Li et al.   Scientific Reports

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

Radiogenomics to characterize regional genetic heterogeneity in glioblastoma

(2016) Leland S. Hu et al.   NEURO-ONCOLOGY

Radiomics: Images Are More than Pictures, They Are Data

(2016) Robert J. Gillies et al.   RADIOLOGY

Patient-Specific Mathematical Neuro-Oncology: Using a Simple Proliferation and Invasion Tumor Model to Inform Clinical Practice

(2015) Pamela R. Jackson et al.   BULLETIN OF MATHEMATICAL BIOLOGY

Immunotherapy response assessment in neuro-oncology: a report of the RANO working group

(2015) Hideho Okada et al.   LANCET ONCOLOGY

Evaluation of tumor-derived MRI-texture features for discrimination of molecular subtypes and prediction of 12-month survival status in glioblastoma

(2015) Dalu Yang et al.   MEDICAL PHYSICS

Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma

(2015) Leland S. Hu et al.   PLoS One

Invasion and proliferation kinetics in enhancing gliomas predict IDH1 mutation status

(2014) Anne L. Baldock et al.   NEURO-ONCOLOGY

Patient-Specific Metrics of Invasiveness Reveal Significant Prognostic Benefit of Resection in a Predictable Subset of Gliomas

(2014) Anne L. Baldock et al.   PLoS One

MRI-localized biopsies reveal subtype-specific differences in molecular and cellular composition at the margins of glioblastoma

(2014) B. J. Gill et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

5-ALA complete resections go beyond MR contrast enhancement: shift corrected volumetric analysis of the extent of resection in surgery for glioblastoma

(2013) Philippe Schucht et al.   ACTA NEUROCHIRURGICA

Response Classification Based on a Minimal Model of Glioblastoma Growth Is Prognostic for Clinical Outcomes and Distinguishes Progression from Pseudoprogression

(2013) M. L. Neal et al.   CANCER RESEARCH

Response to "Reply to [18F]-fluoro-ethyl-L-tyrosine PET: a valuable diagnostic tool in neuro-oncology, but not all that glitters is glioma" by Hutterer et al.

(2013) M. Hutterer et al.   NEURO-ONCOLOGY

Discriminating Survival Outcomes in Patients with Glioblastoma Using a Simulation-Based, Patient-Specific Response Metric

(2013) Maxwell Lewis Neal et al.   PLoS One

FET–PET for malignant glioma treatment planning

(2011) Maximilian Niyazi et al.   RADIOTHERAPY AND ONCOLOGY

Spatially quantifying microscopic tumor invasion and proliferation using a voxel-wise solution to a glioma growth model and serial diffusion MRI

(2010) Benjamin M. Ellingson et al.   MAGNETIC RESONANCE IN MEDICINE

Predicting the efficacy of radiotherapy in individual glioblastoma patientsin vivo:a mathematical modeling approach

(2010) R Rockne et al.   PHYSICS IN MEDICINE AND BIOLOGY

Glioblastoma Multiforme Regional Genetic and Cellular Expression Patterns: Influence on Anatomic and Physiologic MR Imaging

(2010) Ramon F. Barajas et al.   RADIOLOGY

Response Assessment in Neuro-Oncology

(2010) Eudocia C. Quant et al.   Current Oncology Reports

Association of F18-fluoro-ethyl-tyrosin uptake and 5-aminolevulinic acid-induced fluorescence in gliomas

(2009) Florian Stockhammer et al.   ACTA NEUROCHIRURGICA

Quantitative Metrics of Net Proliferation and Invasion Link Biological Aggressiveness Assessed by MRI with Hypoxia Assessed by FMISO-PET in Newly Diagnosed Glioblastomas

(2009) M. D. Szeto et al.   CANCER RESEARCH

Prognostic Significance of Growth Kinetics in Newly Diagnosed Glioblastomas Revealed by Combining Serial Imaging with a Novel Biomathematical Model

(2009) C. H. Wang et al.   CANCER RESEARCH

Correlation of F-18-fluoro-ethyl-tyrosin uptake with vascular and cell density in non-contrast-enhancing gliomas

(2008) Florian Stockhammer et al.   JOURNAL OF NEURO-ONCOLOGY