Evaluation and mitigation of deformable image registration uncertainties for MRI‐guided adaptive radiotherapy

Abstract

AbstractPurposeWe evaluate the performance of a deformable image registration (DIR) software package in registering abdominal magnetic resonance images (MRIs) and then develop a mechanical modeling method to mitigate detected DIR uncertainties.Materials and MethodsThree evaluation metrics, namely mean displacement to agreement (MDA), DICE similarity coefficient (DSC), and standard deviation of Jacobian determinants (STD‐JD), are used to assess the multi‐modality (MM), contour‐consistency (CC), and image‐intensity (II)‐based DIR algorithms in the MIM software package, as well as an in‐house developed, contour matching‐based finite element method (CM‐FEM). Furthermore, we develop a hybrid FEM registration technique to modify the displacement vector field of each MIM registration. The MIM and FEM registrations were evaluated on MRIs obtained from 10 abdominal cancer patients. One‐tailed Wilcoxon‐Mann‐Whitney (WMW) tests were conducted to compare the MIM registrations with their FEM modifications.ResultsFor the registrations performed with the MIM‐CC, MIM‐MM, MIM‐II, and CM‐FEM algorithms, their average MDAs are 0.62 ± 0.27, 2.39 ± 1.30, 3.07 ± 2.42, 1.04 ± 0.72 mm, and average DSCs are 0.94 ± 0.03, 0.80 ± 0.12, 0.77 ± 0.15, 0.90 ± 0.11, respectively. The p‐values of the WMW tests between the MIM registrations and their FEM modifications are less than 0.0084 for STD‐JDs and greater than 0.87 for MDA and DSC.ConclusionsAmong the three MIM DIR algorithms, MIM‐CC shows the smallest errors in terms of MDA and DSC but exhibits significant Jacobian uncertainties in the interior regions of abdominal organs. The hybrid FEM technique effectively mitigates the Jacobian uncertainties in these regions.