We established a framework for integrating quantitative MRI and biomarkers in MR-guided therapy, indicating improved adaptation in radiation oncology.
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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Deng et al. (2025) studied this question.
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