Faculty Collaboration Database

Evaluation and mitigation of deformable image registration uncertainties for MRI-guided adaptive radiotherapy. J Appl Clin Med Phys 2024 Jun;25(6):e14358

Date

04/18/2024

Pubmed ID

38634799

Pubmed Central ID

PMC11163488

DOI

10.1002/acm2.14358

Scopus ID

2-s2.0-85190946901 (requires institutional sign-in at Scopus site)   2 Citations

Abstract

PURPOSE: We 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 METHODS: Three 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.

RESULTS: For 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.

CONCLUSIONS: Among 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.

Author List

Zhong H, Kainz KK, Paulson ES

Authors

Kristofer Kainz PhD Associate Professor in the Radiation Oncology department at Medical College of Wisconsin
Eric Paulson PhD Chief, Professor in the Radiation Oncology department at Medical College of Wisconsin
Hualiang Zhong PhD Associate Professor in the Radiation Oncology department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Abdominal Neoplasms
Algorithms
Humans
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Radiotherapy Dosage
Radiotherapy Planning, Computer-Assisted
Radiotherapy, Image-Guided
Radiotherapy, Intensity-Modulated
Software
Uncertainty