ArticleMedical physics2017
Validation of biomechanical deformable image registration in the abdomen, thorax, and pelvis in a commercial radiotherapy treatment planning system.
Article in Medical physics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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30 citing papers in PubMed, 61 citations in OpenAlex.
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- Evaluation of hybrid DIR performance using controlling structures and points of interest in MR-guided adaptive radiotherapy for prostate cancer patients.Journal of applied clinical medical physics · 2026Article
- Local rigidity constraints for deformable image registration in CBCT-guided radiotherapy.Medical physics · 2025Article
- Real-Time Dose-Guided Radiation Therapy.International journal of radiation oncology, biology, physics · 2025Review
- Multi-contrast 4DMR via MR multitasking: Early clinical experience and implication for liver stereotactic body radiation therapy.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2025Article
- Tools and recommendations for commissioning and quality assurance of deformable image registration in radiotherapy.Physics and imaging in radiation oncology · 2024Review
- Ablative margin quantification using deformable versus rigid image registration in colorectal liver metastasis thermal ablation: a retrospective single-center study.European radiology · 2024Article
- Evaluation and mitigation of deformable image registration uncertainties for MRI-guided adaptive radiotherapy.Journal of applied clinical medical physics · 2024Article
- Evaluation of the availability of single-position treatment with a rotating gantry and the validity of deformable image registration dose assessment for pancreatic cancer carbon-ion radiotherapy.Journal of applied clinical medical physics · 2024Article
- Incidental Ring-hyperenhancing Liver Micronodules at CT Hepatic Arteriography-guided Percutaneous Thermal Ablation of Colorectal Liver Metastases.Radiology. Imaging cancer · 2024Article
- Review and recommendations on deformable image registration uncertainties for radiotherapy applications.Physics in medicine and biology · 2023Review
- Progressively refined deep joint registration segmentation (ProRSeg) of gastrointestinal organs at risk: Application to MRI and cone-beam CT.Medical physics · 2023Article
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- Ablative Margins of Colorectal Liver Metastases Using Deformable CT Image Registration and Autosegmentation.Radiology · 2023Article
- 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
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- Automatic liver tumor localization using deep learning-based liver boundary motion estimation and biomechanical modeling (DL-Bio).Medical physics · 2021Article
- A novel use of biomechanical model-based deformable image registration (DIR) for assessing colorectal liver metastases ablation outcomes.Medical physics · 2021Article
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Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
Abstract
purposeThe accuracy of deformable image registration tools can vary widely between imaging modalities and specific implementations of the same algorithms. A biomechanical model-based algorithm initially developed in-house at an academic institution was translated into a commercial radiotherapy treatment planning system and validated for multiple imaging modalities and anatomic sites.
methodsBiomechanical deformable registration (Morfeus) is a geometry-driven algorithm based on the finite element method. Boundary conditions are derived from the model-based segmentation of controlling structures in each image which establishes a point-to-point surface correspondence. For each controlling structure, material properties and fixed or sliding interfaces are assigned. The displacements of internal volumes for controlling structures and other structures implicitly deformed are solved with finite element analysis. Registration was performed for 74 patients with images (mean vector resolution) of thoracic and abdominal 4DCT (2.8 mm) and MR (5.3 mm), liver CT-MR (4.5 mm), and prostate MR (2.6 mm). Accuracy was quantified between deformed and actual target images using distance-to-agreement (DTA) for structure surfaces and the target registration error (TRE) for internal point landmarks.
resultsThe results of the commercial implementation were as follows. The mean DTA was ≤ 1.0 mm for controlling structures and 1.0-3.5 mm for implicitly deformed structures on average. TRE ranged from 2.0 mm on prostate MR to 5.1 mm on lung MR on average, within 0.1 mm or lower than the image voxel sizes. Accuracy was not overly sensitive to changes in the material properties or variability in structure segmentations, as changing these inputs affected DTA and TRE by ≤ 0.8 mm. Maximum DTA > 5 mm occurred for 88% of the structures evaluated although these were within the inherent segmentation uncertainty for 82% of structures. Differences in accuracy between the commercial and in-house research implementations were ≤ 0.5 mm for mean DTA and ≤ 0.7 mm for mean TRE.
conclusionsAccuracy of biomechanical deformable registration evaluated on a large cohort of images in the thorax, abdomen and prostate was similar to the image voxel resolution on average across multiple modalities. Validation of this treatment planning system implementation supports biomechanical deformable registration as a versatile clinical tool to enable accurate target delineation at planning and treatment adaptation.
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