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Abstract #1678

Establishing a Quantitative MRI-Guided Adaptive Radiotherapy Program in Radiation Oncology

Jie Deng1, Yan Dai1, Yen-peng Liao1, Junjie Wu1, Christopher Kabat1, Jill De Vis1, Weiguo Lu1, Yulong Yan1, Bin Cai1, Mu-Han Lin1, and Andrew Godley 1
1University of Texas Southwestern Medical Center, Dallas, TX, United States

Synopsis

Keywords: Quantitative Imaging, Quantitative Imaging, quality assurance, T1 Mapping, T2 Mapping, ADC, Cellularity

Motivation: Anatomy-based adaptive radiotherapy (ART) is limited in underestimating tumor extent, unable to identify radio-resistant subregion and early treatment responses. Functional adaptation integrating biological insights throughout the MRI-guided radiation therapy (MRgRT) workflow will help achieve optimal plan adaptation.

Goal(s): Clinical implementation of integrating DWI and DCE into the MRgRT workflow from MR simulation to treatment on MR-LINAC systems.

Approach: Quantitative MRI (qMRI) protocol optimization and quality assurance, post-processing and image analysis via a script in the TPS API to provide biological information of intratumoral heterogeneity, and online adaptation with guidance of DWI.

Results: We established a qMRI-guided ART framework in radiation oncology department.

Impact: Our project accelerates the integration of qMRI-based biomarkers into clinical workflows involving MRI simulation and MR-LINAC treatment, establishing a framework for MR-guided Biology ART in clinical settings to achieve personalized radiotherapy.

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Keywords