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Towards quantitative MRI Driving online adaptive MRgRT for lung tumors
I Moretti1, M Nardini2, C Mazzarella2
1Università Cattolica del Sacro Cuore, Roma, Italy.
Summary
Online adaptive radiotherapy using MRI-Linacs shows feasibility and improves lung cancer treatment. Quantitative MRI shows promise for predicting toxicity and assessing response, though further research is needed.
Area of Science:
- Radiotherapy and Medical Imaging
- Oncology and Radiation Oncology
Background:
- Respiratory motion and anatomical variability challenge lung cancer radiotherapy precision.
- Magnetic Resonance Image-guided Radiotherapy (MRgRT) with hybrid MR-Linac systems offers enhanced soft-tissue visualization and online adaptive radiotherapy (online MRgART).
Purpose of the Study:
- To review current evidence on online MRgART for lung cancer.
- To examine the emerging roles of quantitative MRI (qMRI) in this context.
Main Methods:
- A systematic PubMed search from January 2020 to September 2025 identified 19 relevant studies.
- Three studies specifically focused on the application of qMRI in MR-Linac treatments.
Main Results:
- Online MRgART demonstrated workflow feasibility, frequent adaptations, improved target coverage, and OARs sparing.
- Encouraging local control with low toxicity was observed.
- Quantitative MRI (DWI, ventilation/perfusion mapping) showed feasibility for treatment adaptation, toxicity prediction, and response assessment.
Conclusions:
- Current qMRI integration in lung online MRgART is limited but expected to grow significantly.
- This review provides a state-of-the-art snapshot and highlights the nascent evidence for qMRI.
- Future directions include AI integration and multi-center trials to validate qMRI biomarkers and clinical benefits.
