{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T09:40:48Z","timestamp":1792402848830,"version":"4.4.0"},"reference-count":23,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T00:00:00Z","timestamp":1790121600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["23K24282"],"award-info":[{"award-number":["23K24282"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J Applied Clin Med Phys"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Deformable image registration (DIR) is essential for thoracic four\u2010dimensional computed tomography (4D\u2010CT)\u2010based radiotherapy applications. Recently, deep learning\u2010based DIR methods such as VoxelMorph have been proposed; however, their performance relative to clinically used DIR algorithms remains unclear.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study aimed to evaluate the DIR accuracy of VoxelMorph for thoracic 4D\u2010CT and to compare it with conventional clinical and research\u2010oriented DIR methods.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>Thoracic 4D\u2010CT data from 64 lung cancer patients were retrospectively analyzed. End\u2010inhalation and end\u2010exhalation phase images were used for DIR. VoxelMorph was trained using 50 cases, with 4 for validation and 10 for testing. DIR performance on the test dataset was compared with Demons (SimpleITK), modified Demons (Eclipse), and ANACONDA (RayStation). Accuracy was evaluated by mean absolute error (MAE) of CT values computed within the body region, whereas Dice similarity coefficient (DSC) and 95th percentile of Hausdorff distance (HD95) were evaluated within the lung label.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The median MAE decreased from 67.56 HU before DIR to 52.32 HU with modified Demons, 37.39 HU with Demons, 36.18 HU with ANACONDA, and 36.83 HU with VoxelMorph. The median DSC increased from 0.91 to 0.95 for modified Demons, 0.97 for Demons and ANACONDA, and 0.98 for VoxelMorph. The median HD95 was 3.0\u00a0mm for modified Demons, 3.1\u00a0mm for Demons, 2.0\u00a0mm for ANACONDA, and 2.5\u00a0mm for VoxelMorph. Overall, VoxelMorph demonstrated competitive accuracy, significantly outperforming modified Demons (adjusted\n                      <jats:italic>p\u00a0&lt;<\/jats:italic>\n                      \u00a00.05), while showing smaller inter\u2010case variability and markedly reduced processing time.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>VoxelMorph demonstrated DIR performance comparable to that of clinically used algorithms for thoracic 4D\u2010CT, with high overlap accuracy, relatively low inter\u2010case variability and shorter processing times under the evaluated implementation conditions. These findings suggest its potential as research\u2010oriented DIR framework, although further validation under standardized conditions is required before routine clinical implementation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/acm2.70816","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T10:14:34Z","timestamp":1790158474000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Comparative evaluation of VoxelMorpand conventional deformable image registration algorithms for thoracic 4D\u2010CT in radiotherapy"],"prefix":"10.1002","volume":"27","author":[{"given":"Mizuha","family":"Sakai","sequence":"first","affiliation":[{"name":"Department of Advanced Medical Physics Graduate School of Medicine Kyoto University  Kyoto Kyoto Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Megumi","family":"Nakao","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering and Intelligence Graduate School of Medicine Kyoto University  Kyoto Kyoto Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hideaki","family":"Hirashima","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Image\u2010Applied Therapy Graduate School of Medicine Kyoto University  Kyoto Kyoto Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Masahiro","family":"Yoneyama","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Image\u2010Applied Therapy Graduate School of Medicine Kyoto University  Kyoto Kyoto Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Noriko","family":"Kishi","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Image\u2010Applied Therapy Graduate School of Medicine Kyoto University  Kyoto Kyoto Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takashi","family":"Mizowaki","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology and Image\u2010Applied Therapy Graduate School of Medicine Kyoto University  Kyoto Kyoto Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mitsuhiro","family":"Nakamura","sequence":"additional","affiliation":[{"name":"Department of Advanced Medical Physics Graduate School of Medicine Kyoto University  Kyoto Kyoto Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,9,23]]},"reference":[{"key":"e_1_2_13_2_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4769427"},{"key":"e_1_2_13_3_1","doi-asserted-by":"publisher","DOI":"10.01002\/mp.12256"},{"key":"e_1_2_13_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jirobp.2016.02.058"},{"key":"e_1_2_13_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2024.103385"},{"key":"e_1_2_13_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2020.106767"},{"key":"e_1_2_13_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2897538"},{"key":"e_1_2_13_8_1","doi-asserted-by":"crossref","unstructured":"KanamuroM HirashimaH NakamuraM NakaoM Diffusion model\u2010based displacement field generation for 4D\u2010CT chest image generation.International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).2025:1\u20106. doi:10.1109\/EMBC58623.2025.11254765","DOI":"10.1109\/EMBC58623.2025.11254765"},{"key":"e_1_2_13_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/\/j.compbiomed.2023.107434"},{"key":"e_1_2_13_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/acm2.13392"},{"key":"e_1_2_13_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TRPMS.2024.3430827"},{"key":"e_1_2_13_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.70387"},{"key":"e_1_2_13_13_1","doi-asserted-by":"publisher","DOI":"10.1088\/1361\u20106560\/ab79c4"},{"key":"e_1_2_13_14_1","unstructured":"JaderbergM SimonyanK ZissermanA KavukcuogluK Spatial Transformer Networks. Advance in Neural Information Processing Systems.2015;2017\u20102025. doi:10.4855\/arXiv.1506.02025"},{"key":"e_1_2_13_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/s1361\u20108415(98)80022\u20104"},{"key":"e_1_2_13_16_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031\u20109155\/50\/12\/011"},{"key":"e_1_2_13_17_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4894702"},{"key":"e_1_2_13_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tipsro.2024.100295"},{"key":"e_1_2_13_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2019.2951024"},{"key":"e_1_2_13_20_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.14065"},{"key":"e_1_2_13_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102615"},{"key":"e_1_2_13_22_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467\u2010026\u201072508\u20103"},{"key":"e_1_2_13_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40314\u2010026\u201003773\u20107"},{"key":"e_1_2_13_24_1","doi-asserted-by":"publisher","DOI":"10.1088\/0031\u20109155\/54\/7\/001"}],"container-title":["Journal of Applied Clinical Medical Physics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/acm2.70816","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/acm2.70816","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/acm2.70816","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T08:53:57Z","timestamp":1792400037000},"score":1,"resource":{"primary":{"URL":"https:\/\/aapm.onlinelibrary.wiley.com\/doi\/10.1002\/acm2.70816"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,23]]},"references-count":23,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2026,10]]}},"alternative-id":["10.1002\/acm2.70816"],"URL":"https:\/\/doi.org\/10.1002\/acm2.70816","archive":["Portico"],"relation":{},"ISSN":["1526-9914","1526-9914"],"issn-type":[{"value":"1526-9914","type":"print"},{"value":"1526-9914","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,23]]},"assertion":[{"value":"2026-05-10","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-09-08","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-09-23","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70816"}}