{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T13:45:21Z","timestamp":1792071921879,"version":"4.4.0"},"reference-count":56,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T00:00:00Z","timestamp":1787788800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T00:00:00Z","timestamp":1787788800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Accurate motion estimation remains a key challenge in adaptive radiotherapy (ART). Voxel\u2010wise accuracy is required, as registration errors can compromise the treatment quality. Locally constrained image registration is a promising technique to further improve ART treatment, but relies heavily on quick and accurate delineations of the local areas used to constrain. In online clinical scenarios, these delineations are often available on pre\u2010treatment image volumes, but not on the online data due to accuracy and time\u00a0constraints.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>We developed a deformable image registration (DIR) framework that integrates inverse consistency with local biomechanical constraints, enabling tissue\u2010specific motion modeling using contours from only a single image volume. This approach enforces tissue\u2010specific constraints on the inverse deformation field and propagates them to the forward deformation through inverse consistency optimization, yielding anatomically plausible motion estimates for ART\u00a0workflows.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The proposed framework was evaluated in three scenarios relevant to ART: abdominal CT\u2010CT and multi\u2010modality CT\u2010MR registration with incompressibility constraints on the liver and kidneys, as well as thoracic CT\u2010CT registration with local rigidity constraints on the ribs and vertebrae. We also investigated the robustness of the framework to image degradation by evaluating motion estimates under added Gaussian noise and artificially induced streaking artifacts. Performance was compared to a baseline DIR model and an unconstrained inverse\u2010consistent model. Accuracy and anatomical consistency were assessed using landmark alignment, contour overlap, and physics\u2010based motion\u00a0analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We demonstrate that local biomechanical constraints imposed on the inverse deformation field are successfully propagated to the forward motion field through inverse consistency optimization. The proposed framework improves the biomechanical plausibility of the resulting deformation fields at a small cost of landmark\u2010based accuracy, and maintaining comparable results in terms of contour\u2010based evaluation. The method is applicable to both mono\u2010 and multimodality registration and is more robust to noise and artifacts that appear from image acquisition and\u00a0reconstruction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The proposed framework uses inverse consistency to propagate local constraints between motion fields. This work demonstrates the use of local biomechanical constraints for DIR in several use\u2010cases for ART. This methodology requires delineations of local tissue on only one of the image volumes. This approach can become beneficial for applications where voxel\u2010wise accuracy and anatomical consistency are required, but quick and accurate delineations of new anatomies are unavailable, such as online\u00a0ART.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70645","type":"journal-article","created":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T13:38:04Z","timestamp":1787837884000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Inverse\u2010consistent deformable image registration to propagate biomechanical constraints for online adaptive radiotherapy"],"prefix":"10.1002","volume":"53","author":[{"given":"T. J. 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