Image-based personalization of computational models for predicting response of high-grade glioma to chemoradiation
DA Hormuth, KA Al Feghali, AM Elliott, TE Yankeelov… - Scientific reports, 2021 - nature.com
High-grade gliomas are an aggressive and invasive malignancy which are susceptible to
treatment resistance due to heterogeneity in intratumoral properties such as cell proliferation …
treatment resistance due to heterogeneity in intratumoral properties such as cell proliferation …
Predicting the efficacy of radiotherapy in individual glioblastoma patients in vivo: a mathematical modeling approach
R Rockne, JK Rockhill, M Mrugala… - Physics in Medicine …, 2010 - iopscience.iop.org
Glioblastoma multiforme (GBM) is the most malignant form of primary brain tumors known as
gliomas. They proliferate and invade extensively and yield short life expectancies despite …
gliomas. They proliferate and invade extensively and yield short life expectancies despite …
Applications of radiomics and radiogenomics in high-grade gliomas in the era of precision medicine
Simple Summary Radiomics and radiogenomics offer new insight into high-grade glioma
biology, as well as into glioma behavior in response to standard therapies. In this article, we …
biology, as well as into glioma behavior in response to standard therapies. In this article, we …
Personalized radiotherapy design for glioblastoma: integrating mathematical tumor models, multimodal scans, and Bayesian inference
Glioblastoma (GBM) is a highly invasive brain tumor, whose cells infiltrate surrounding
normal brain tissue beyond the lesion outlines visible in the current medical scans. These …
normal brain tissue beyond the lesion outlines visible in the current medical scans. These …
Discriminating survival outcomes in patients with glioblastoma using a simulation-based, patient-specific response metric
ML Neal, AD Trister, T Cloke, R Sodt, S Ahn… - PloS one, 2013 - journals.plos.org
Accurate clinical assessment of a patient's response to treatment for glioblastoma multiforme
(GBM), the most malignant type of primary brain tumor, is undermined by the wide patient-to …
(GBM), the most malignant type of primary brain tumor, is undermined by the wide patient-to …
Quantifying uncertainty and robustness in a biomathematical model–based patient-specific response metric for glioblastoma
A Hawkins-Daarud, SK Johnston… - JCO clinical cancer …, 2019 - ascopubs.org
Purpose Glioblastomas, lethal primary brain tumors, are known for their heterogeneity and
invasiveness. A growing body of literature has been developed demonstrating the clinical …
invasiveness. A growing body of literature has been developed demonstrating the clinical …
Machine learning-based radiomic evaluation of treatment response prediction in glioblastoma
AIM To investigate machine learning based models combining clinical, radiomic, and
molecular information to distinguish between early true progression (tPD) and …
molecular information to distinguish between early true progression (tPD) and …
Forecasting tumor and vasculature response dynamics to radiation therapy via image based mathematical modeling
Background Intra-and inter-tumoral heterogeneity in growth dynamics and vascularity
influence tumor response to radiation therapy. Quantitative imaging techniques capture …
influence tumor response to radiation therapy. Quantitative imaging techniques capture …
Quantitative multiparametric MRI assessment of glioma response to radiotherapy in a rat model
Background The inability of structural MRI to accurately measure tumor response to therapy
complicates care management for patients with gliomas. The purpose of this study was to …
complicates care management for patients with gliomas. The purpose of this study was to …
Radiomic profiling of glioblastoma: identifying an imaging predictor of patient survival with improved performance over established clinical and radiologic risk models
Purpose To evaluate whether radiomic feature–based magnetic resonance (MR) imaging
signatures allow prediction of survival and stratification of patients with newly diagnosed …
signatures allow prediction of survival and stratification of patients with newly diagnosed …
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