ArticlePractical radiation oncology
Utility and validation of biomechanical deformable image registration in low-contrast images.
Article in Practical radiation oncology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Comparison of regional lung perfusion response on longitudinal MAA SPECT/CT in lung cancer patients treated with and without functional tissue-avoidance radiation therapy.The British journal of radiology · 2019Trial
- Inverse consistency error for validating deformable image registration: an explorative study on computational phantoms.Physics and imaging in radiation oncology · 2026Article
- Artificial intelligence-based automated segmentation and radiotherapy dose mapping for thoracic normal tissues.Physics and imaging in radiation oncology · 2024Article
- Review and recommendations on deformable image registration uncertainties for radiotherapy applications.Physics in medicine and biology · 2023Review
- Optimization of mesh generation for geometric accuracy, robustness, and efficiency of biomechanical-model-based deformable image registration.Medical physics · 2023Article
- Leveraging deep learning-based segmentation and contours-driven deformable registration for dose accumulation in abdominal structures.Frontiers in oncology · 2022Article
- Automatic liver tumor localization using deep learning-based liver boundary motion estimation and biomechanical modeling (DL-Bio).Medical physics · 2021Article
- The evaluation of a hybrid biomechanical deformable registration method on a multistage physical phantom with reproducible deformation.Radiation oncology (London, England) · 2018Article
- Implementing Radiation Dose-Volume Liver Response in Biomechanical Deformable Image Registration.International journal of radiation oncology, biology, physics · 2017Article
- Validation of biomechanical deformable image registration in the abdomen, thorax, and pelvis in a commercial radiotherapy treatment planning system.Medical physics · 2017Article
- Characterization of deformation and physical force in uniform low contrast anatomy and its impact on accuracy of deformable image registration.Medical physics · 2016Article
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5 authors.
Funding
Abstract
purposeThe application of a biomechanical deformable image registration algorithm has been demonstrated to overcome the potential limitations in the use of intensity-based algorithms on low-contrast images that lack prominent features. Because validation of deformable registration is particularly challenging on such images, the dose distribution predicted via a biomechanical algorithm was evaluated using the measured dose from a deformable dosimeter. METHODS AND MATERIALS: A biomechanical model-based image registration algorithm registered computed tomographic (CT) images of an elastic radiochromic dosimeter between its undeformed and deformed positions. The algorithm aligns the external boundaries of the dosimeter, created from CT contours, and the internal displacements are solved by modeling the physical material properties of the dosimeter. The dosimeter was planned and irradiated in its deformed position, and subsequently, the delivered dose was measured with optical CT in the undeformed position. The predicted dose distribution, created by applying the deformable registration displacement map to the planned distribution, was then compared with the measured optical CT distribution.
resultsCompared with the optical CT distribution, biomechanical image registration predicted the position and size of the deformed dose fields with mean errors of ≤1 mm (maximum, 3 mm). The accuracy did not differ between cross sections with a greater or lesser deformation magnitude despite the homogenous CT intensities throughout the dosimeter. The overall 3-dimensional voxel passing rate of the predicted distribution was γ3%/3mm = 91% compared with optical CT.
conclusionsBiomechanical registration accurately predicted the deformed dose distribution measured in a deformable dosimeter, whereas previously, evaluations of a commercial intensity-based algorithm demonstrated substantial errors. The addition of biomechanical algorithms to the collection of adaptive radiation therapy tools would be valuable for dose accumulation, particularly in feature-poor images such as cone beam CT and organs such as the liver.
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