Quantitative magnetic resonance imaging for accurate delineation of radiotherapy: a narrative review

Quantitative magnetic resonance imaging (qMRI) can provide quantifiable biological information, such as tissue relaxation times, diffusion coefficients, and perfusion parameters, thereby enabling accurate characterization of tumor heterogeneity, hypoxic status, and microenvironmental features. It holds unique clinical value in the precise delineation of radiotherapy targets. This review aims to systematically evaluate the research progress and clinical application prospects of qMRI in the biological definition of radiotherapy target volumes and to explore its potential in driving the paradigm shift from geometry-guided to biology-guided radiotherapy.

This narrative review systematically searched seven databases up to January 2026. Eligible English full-text human studies focusing on qMRI and biology-guided radiotherapy target delineation were included.

qMRI enables the acquisition of quantitative parameters, including apparent diffusion coefficient (ADC) values, relaxation times, and perfusion metrics, which accurately reflect tumor cellularity, microvascular perfusion, and metabolic status. It demonstrates unique value in identifying tumor infiltration boundaries, delineating internal subtargets, assessing tumor hypoxia, and predicting early radiotherapy response. Currently, this technique has shown significant advantages in target delineation for tumors of the brain, head and neck, prostate, and other sites. However, key challenges remain regarding standardization of data acquisition, parameter reproducibility, multicenter validation, and deep integration with radiotherapy treatment planning systems.

qMRI is driving a critical paradigm shift in radiotherapy from geometry-guided to biology-guided approaches, providing a powerful tool for individualized target delineation and dose "three-dimensional sculpting" based on tumor biology. Future efforts should focus on multi-parameter combined validation, establishing standardized systems covering acquisition, calibration, and post-processing, conducting large-scale prospective clinical trials to generate high-level evidence, and deeply integrating artificial intelligence to mine radiomics features and develop robust predictive models. Through technical optimization, clinical validation, and multidisciplinary collaboration, qMRI is expected to serve as an indispensable biological "eye" in precision radiotherapy systems, laying a solid foundation for individualized, adaptive radiotherapy (ART) and improved oncological outcomes.