Repeatability and reproducibility of MRI-derived radiomics on a 0.35 T MR-Linac using a tissue-mimicking phantom

Magnetic resonance-guided radiotherapy provides real-time soft-tissue-based targeting during dose delivery. Beyond image guidance, magnetic resonance linear accelerator (MR-Linac) systems offer new opportunities for developing magnetic resonance imaging (MRI)-derived radiomics biomarkers. However, the reproducibility of these biomarkers in a low-field MR-Linac environment remains unclear.

This study evaluated the repeatability and reproducibility of MRI-derived radiomic features acquired on a 0.35 T MR-Linac using a tissue-mimicking phantom containing multiple tissue-equivalent materials. Fifty balanced steady-state free precession acquisitions were performed over 10 sessions, enabling both intra- and inter-session analyses. Forty-eight preprocessing pipelines combining normalization, discretization, and bias-field correction were assessed using the coefficient of variation and intraclass correlation coefficient for 68 radiomic features across 12 defined regions of interest.

The combination of N4 bias correction and z-score normalization yielded the highest overall stability, with several first-order (e.g. Entropy, Mean) and texture-based (e.g. glcm_DifferenceEntropy and glrlm_ShortRunEmphasis) features showing a coefficient of variation <5% and/or an intraclass correlation coefficient (2,1) > 0.85 across phantom materials. Stability varied with phantom composition, with higher reproducibility in homogeneous PVP-40 and water inserts compared to fat or fibroglandular compartments. Comparison with previous 0.35 T MR-Linac studies identified a consistent subset of robust features, supporting their potential as standardized MRI-derived radiomic biomarkers.

These findings demonstrated the critical role of preprocessing and tissue composition in feature reproducibility and highlighted the importance of tissue-mimicking phantoms for validating MR-Linac-based quantitative imaging pipelines.