ArticlePhysics and imaging in radiation oncology2025
The bone rigidity error as a simple, quantitative, and interpretable metric for patient-specific validation of deformable image registration.
Article in Physics and imaging in radiation oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Local rigidity constraints for deformable image registration in CBCT-guided radiotherapy.Medical physics · 2025Article
- Imaging, automation and workflow challenges for online adaptive proton therapy.Physics and imaging in radiation oncology · 2025Article
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3 authors.
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Abstract
Background and Purpose: Despite its potential, deformable image registration (DIR) is underutilized clinically, especially in time-sensitive cases, due to a lack of comprehensive metrics for assessing solution quality. Here, we propose a metric of physical plausibility, the bone rigidity error (BRE), that penalizes non-rigid transformations within individual bones, based on the assumption that bones do not deform. Materials and Methods: The BRE is calculated by segmenting bones individually and isolating the vectors of a deformable vector field within each bone. A rigid registration is least-square fitted to these vectors, and the BRE is calculated as the average deviation of these vectors from the fitted rigid registration. A lower BRE indicates better rigidity preservation. We evaluated the BRE for 6 DIR algorithms on 32 patients with 137 computed tomography (CT)-to-CT registrations across relevant anatomical sites. Results: The BRE varied widely between DIR algorithms, up to a factor of 3 on average for inhale-to-exhale thoracic CT registration. Despite large BRE differences between anatomical sites within each algorithm, some algorithms consistently outperformed others. Notably, a low BRE was not correlated with poorer image similarity, and the BRE was only weakly correlated to target registration error. Furthermore, we proposed bone-specific inspection thresholds for patient-specific validation. BRE calculation required less than 5.5 s. Conclusions: The BRE is an automatic, interpretable, fast, and easy-to-implement metric to assist validation of DIR algorithms, which show widely varying performance. It provides a useful complementary metric for patient-specific validation, especially in time-sensitive applications.
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