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Abstract #1937

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

Ayesha Das1, David A Hormuth II1,2, Jack Virostko2,3,4, and Thomas Yankeelov1,2,4,5,6,7
1Biomedical Engineering, University of Texas at Austin, Austin, TX, United States, 2Oden Institute for Computational Science and Engineering, University of Texas at Austin, Austin, TX, United States, 3Diagnostic Medicine, Dell Medical School, Austin, TX, United States, 4Livestrong Cancer Institutes, Dell Medical School, Austin, TX, United States, 5Department of Diagnostic Medicine, Dell Medical School, Austin, TX, United States, 6Department of Oncology, Dell Medical School, Austin, TX, United States, 7Department of Imaging Physics, MD Anderson Cancer Center, Houston, TX, United States

Synopsis

Keywords: Preclinical Image Analysis, Radiotherapy, Analysis/Processing, cancer, quantitative imaging

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.

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