Abstract #2318

Wavelet-Based Time-Frequency Analysis of Radiation-Induced Vascular Changes in Brain Tumors Using Dynamic Contrast Enhanced MRI

Hassan Bagher-Ebadian^1,2,3,4, Stephen L. Brown^1,2,3, Mohammad M. Ghassemi⁵, Prabhu C. Acharya³, James R. Ewing^2,3,6, Indrin J. Chetty⁷, Farzan Siddiqui¹, Benjamin Movsas^1,2, and Kundan Thind^1,2,4

¹Radiation Oncology, Henry Ford Health, Detroit, MI, United States, ²Radiology, Michigan State University, East Lansing, MI, United States, ³Physics, Oakland University, Rochester, MI, United States, ⁴Oncology, Wayne State University, Detroit, MI, United States, ⁵Computer Science and Engineering, Michigan State University, East Lansing, MI, United States, ⁶Neurology, Henry Ford Health, Detroit, MI, United States, ⁷Cedars Sinai Medical Center, Los Angles, CA, United States

Synopsis

Keywords: Perfusion, Treatment Response, Dynamic Contrast Enhanced MRI, Wavelet Analysis, Nested Model Selection, Radiation Induced Effect, Signal Coherence, Signal Time-Frequency Analysis, Physiological Tissue Characterization

Motivation: To improve the assessment of radiation therapy impact on brain tumor and normal tissue vasculature using Dynamic-Contrast-Enhanced MRI and advanced time-frequency analysis techniques.

Goal(s): To use wavelet analysis to evaluate how radiation therapy alters contrast agent movement in brain tumors and normal tissues using DCE-MRI in a Nested-Model-Selection framework.

Approach: Animal models of brain tumor were studied pre- and post-radiation using DCE-MRI, with wavelet-based time-frequency analysis to characterize radiation-induced changes in contrast agent dynamics.

Results: Significant radiation-induced lead and lag times in contrast agent dynamics were observed, particularly in the tumor periphery and surrounding normal tissues, suggesting differing responses to radiation across regions.

Impact: This study presents a novel DCE-MRI-based approach using Nested-Model-Selection and wavelet analysis to identify radiation-induced changes in animal models of brain tumor and normal tissues, offering potential clinical applications in improving and optimizing radiation treatment planning for brain cancer patients.

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