Quantifying longitudinal changes in tumor habitats during radiotherapy via multiparametric MRI in a murine glioma model: Preliminary results

Motivation: Spatial and temporal changes in the tumor microenvironment significantly impact treatment efficacy. An MRI protocol designed to monitor tumor heterogeneity throughout radiotherapy could be a valuable tool for enhancing treatment insights and outcomes. Goal(s): We aim to implement a quantitative MRI protocol to identify and quantify tumor heterogeneity over the course of radiation therapy in a preclinical model. Approach: We implemented a multi-parametric, quantitative MRI protocol during radiation therapy in preclinical glioma models. Four experimental schedules and one control schedule were tested. Results: Our MRI protocol effectively captured significant differences in tumor composition in response to variations in the radiotherapy schedule. Impact: Spatial and temporal changes in the tumor microenvironment impact treatment efficacy. Our multi parametric, quantitative MRI protocol effectively captured shifts in tumor composition during radiotherapy, offering valuable insights to improve outcomes.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/1937
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Quantifying longitudinal changes in tumor habitats during radiotherapy via multiparametric MRI in a murine glioma model: Preliminary results

Thomas E. Yankeelov, Ayesha Das, David A. Hormuth, Jack Virostko
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Radiomics and Machine Learning in Medical Imaging
article

Quantifying longitudinal changes in tumor habitats during radiotherapy via multiparametric MRI in a murine glioma model: Preliminary results

Thomas E. Yankeelov, Ayesha Das, David A. Hormuth, Jack Virostko
article en

Abstract

Motivation: Spatial and temporal changes in the tumor microenvironment significantly impact treatment efficacy. An MRI protocol designed to monitor tumor heterogeneity throughout radiotherapy could be a valuable tool for enhancing treatment insights and outcomes. Goal(s): We aim to implement a quantitative MRI protocol to identify and quantify tumor heterogeneity over the course of radiation therapy in a preclinical model. Approach: We implemented a multi-parametric, quantitative MRI protocol during radiation therapy in preclinical glioma models. Four experimental schedules and one control schedule were tested. Results: Our MRI protocol effectively captured significant differences in tumor composition in response to variations in the radiotherapy schedule. Impact: Spatial and temporal changes in the tumor microenvironment impact treatment efficacy. Our multi parametric, quantitative MRI protocol effectively captured shifts in tumor composition during radiotherapy, offering valuable insights to improve outcomes.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 65%
Radiomics and Machine Learning in Medical Imaging
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