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Numerical simulation of a thermodynamically consistent four-species tumor growth model

International journal for numerical methods in biomedical engineering, 2012-01, Vol.28 (1), p.3-24

2012

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

Bulletin of mathematical biology, 2015-05, Vol.77 (5), p.846-856

2015

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A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET

Journal of the Royal Society interface, 2015-02, Vol.12 (103)

2015

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From cells to tissue: How cell scale heterogeneity impacts glioblastoma growth and treatment response

PLoS computational biology, 2020-02, Vol.16 (2), p.e1007672-e1007672

2020

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Improved model prediction of glioma growth utilizing tissue-specific boundary effects

Mathematical biosciences, 2019-06, Vol.312, p.59-66

2019

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Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures

Nature communications, 2023-09, Vol.14 (1), p.6066-6066, Article 6066

2023

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Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma

Scientific reports, 2021-02, Vol.11 (1), p.3932-3932, Article 3932

2021

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Image-based metric of invasiveness predicts response to adjuvant temozolomide for primary glioblastoma

PloS one, 2020-03, Vol.15 (3), p.e0230492

2020

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Goal-oriented error estimation for Cahn-Hilliard models of binary phase transition

Numerical methods for partial differential equations, 2011-01, Vol.27 (1), p.160-196

2011

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Identifying the spatial and temporal dynamics of molecularly-distinct glioblastoma sub-populations

Mathematical biosciences and engineering : MBE, 2020-07, Vol.17 (5), p.4905-4941

2020

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Analysis of glioblastoma tumor coverage by oncolytic virus-loaded neural stem cells using MRI-based tracking and histological reconstruction

Cancer gene therapy, 2015-01, Vol.22 (1), p.55-61

2015

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Imaging of intratumoral heterogeneity in high-grade glioma

Cancer letters, 2020-05, Vol.477, p.97-106

2020

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PM-06 IMPROVED ANATOMICAL MODEL PREDICTION OF GLIOMA GROWTH UTILIZING TISSUE-SPECIFIC BOUNDARY EFFECTS

Neuro-oncology (Charlottesville, Va.), 2014-11, Vol.16 (suppl 5), p.v170-v170

2014

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PM-04 IN SILICO ANALYSIS OF AVAglio AND RTOG 0825 PHASE III CLINICAL TRIALS SUGGESTS SIGNATURES OF PATIENTS TO RECEIVE BENEFIT FROM COMBINED BEVACIZUMAB AND RADIATION THERAPIES

Neuro-oncology (Charlottesville, Va.), 2014-11, Vol.16 (suppl 5), p.v169-v169

2014

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RT-29 CONDUCTING VIRTUAL CLINICAL TRIALS TO EVALUATE HYPOFRACTIONATED RADIOTHERAPY FOR NEWLY DIAGNOSED GLIOBLASTOMA

Neuro-oncology (Charlottesville, Va.), 2014-11, Vol.16 (suppl 5), p.v194-v194

2014

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Response to "Tumor cells in search for glutamate: an alternative explanation for increased invasiveness of IDH1 mutant gliomas"

Neuro-oncology (Charlottesville, Va.), 2014-12, Vol.16 (12), p.1670-1671

2014

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Knowledge-Infused Global-Local Data Fusion for Spatial Predictive Modeling in Precision Medicine

IEEE transactions on automation science and engineering, 2022-07, Vol.19 (3), p.1-13

2022

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

Scientific reports, 2019-07, Vol.9 (1), p.10063-9, Article 10063

2019

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NIMG-85. EVALUATING THE PERFORMANCE OF A DEEP LEARNING GLIOMA SEGMENTATION MODEL USING COMBINED PRE- AND POST-TREATMENT MRI TRAINING DATA

Neuro-oncology (Charlottesville, Va.), 2023-11, Vol.25 (Supplement_5), p.v205-v205

2023

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NIMG-72. QUANTIFYING INTRA-TUMOR MULTI-GENE HETEROGENEITY OF GBM FROM MRI USING A DATA-INCLUSIVE MACHINE LEARNING ALGORITHM

Neuro-oncology (Charlottesville, Va.), 2021-11, Vol.23 (Supplement_6), p.vi145-vi146

2021

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ME-09 DYNAMIC EVIDENCE OF TUMOR INDUCED MICROGLIA ACTIVATION AT THE INFILTRATIVE MARGINS OF GLIOMA

Neuro-oncology (Charlottesville, Va.), 2014-11, Vol.16 (suppl 5), p.v121-v121

2014

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Numerical simulation of a thermodynamically consistent four-species tumor growth model

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

A patient-specific computational model of hypoxia-modulated radiation resistance in glioblastoma using 18F-FMISO-PET

From cells to tissue: How cell scale heterogeneity impacts glioblastoma growth and treatment response

Improved model prediction of glioma growth utilizing tissue-specific boundary effects

Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm

Image-localized biopsy mapping of brain tumor heterogeneity: A single-center study protocol

Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures

Uncertainty quantification in the radiogenomics modeling of EGFR amplification in glioblastoma

Image-based metric of invasiveness predicts response to adjuvant temozolomide for primary glioblastoma

Sex-specific impact of patterns of imageable tumor growth on survival of primary glioblastoma patients

Goal-oriented error estimation for Cahn-Hilliard models of binary phase transition

Identifying the spatial and temporal dynamics of molecularly-distinct glioblastoma sub-populations

Analysis of glioblastoma tumor coverage by oncolytic virus-loaded neural stem cells using MRI-based tracking and histological reconstruction

Imaging of intratumoral heterogeneity in high-grade glioma

PM-06 IMPROVED ANATOMICAL MODEL PREDICTION OF GLIOMA GROWTH UTILIZING TISSUE-SPECIFIC BOUNDARY EFFECTS

PM-04 IN SILICO ANALYSIS OF AVAglio AND RTOG 0825 PHASE III CLINICAL TRIALS SUGGESTS SIGNATURES OF PATIENTS TO RECEIVE BENEFIT FROM COMBINED BEVACIZUMAB AND RADIATION THERAPIES

RT-29 CONDUCTING VIRTUAL CLINICAL TRIALS TO EVALUATE HYPOFRACTIONATED RADIOTHERAPY FOR NEWLY DIAGNOSED GLIOBLASTOMA

Response to "Tumor cells in search for glutamate: an alternative explanation for increased invasiveness of IDH1 mutant gliomas"

Knowledge-Infused Global-Local Data Fusion for Spatial Predictive Modeling in Precision Medicine

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

NIMG-85. EVALUATING THE PERFORMANCE OF A DEEP LEARNING GLIOMA SEGMENTATION MODEL USING COMBINED PRE- AND POST-TREATMENT MRI TRAINING DATA

NIMG-72. QUANTIFYING INTRA-TUMOR MULTI-GENE HETEROGENEITY OF GBM FROM MRI USING A DATA-INCLUSIVE MACHINE LEARNING ALGORITHM

The 2019 mathematical oncology roadmap

ME-09 DYNAMIC EVIDENCE OF TUMOR INDUCED MICROGLIA ACTIVATION AT THE INFILTRATIVE MARGINS OF GLIOMA

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