Quantitative Assessment of Geometric Distortions in MRI-Linac Sequences for Enhanced Radiotherapy Planning

Motivation: Geometric distortion in MRI-Linac sequences remains insufficiently characterized, impacting the precision of radiotherapy treatment planning. This study aims to quantify such distortions in EPI, TSE, and SPLICE sequences. Goal(s): The goal of this study is to quantitatively assess and compare geometric distortion across three common MRI-Linac sequences using deformable image registration and DICE score analysis. Approach: An in vivo study employed patient T2 and DWI B0 scans. Deformable image registration was conducted using ADMIRE and Elekta-based software, generating deformation vector fields. A Python algorithm calculated RMS values. Results: The sequences exhibited distinct DSC scores and RMS distortions, revealing registration effectiveness and sequence-dependent variability. Impact: These findings set the stage for future research on minimizing distortions in MRI-Linac sequences. The developed Python algorithm could be adapted for real-time monitoring, advancing the precision and safety of MRI-guided radiotherapy.