{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T15:29:58Z","timestamp":1788449398878,"version":"build-2803163510"},"reference-count":25,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T00:00:00Z","timestamp":1782777600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T00:00:00Z","timestamp":1782777600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100004562","name":"Minist\u00e8re de l'Enseignement sup\u00e9rieur et de la Recherche","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004562","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>While positioning errors during radiotherapy are increasingly well\u2010characterized and accounted for in the Planning Target Volume (PTV), little is known about the shape and volume changes of the breast in the course of radiotherapy. Yet they represent an unknown factor that may impact treatment effectiveness, highlighting the need to analyze inter\u2010fractional breast deformations to enable promising approaches such as patient\u2010specific adaptive irradiation\u00a0planning.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>In this study, we develop a geometric approach to analyze inter\u2010fractional breast deformation throughout the radiotherapy treatment, based on a dataset of 3D surface scans of patients' frontal torso acquired during radiotherapy\u00a0sessions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We used a handheld 3D range scanner to collect surface scans of 22 patients prior to, during, and after radiotherapy sessions following breast\u2010conserving surgery (lumpectomy). We begin by adapting functional map framework to compute inter\u2010 and intra\u2010patient nonrigid correspondences. To study shape changes during radiotherapy, we then perform both intrinsic and extrinsic analyses of the collected breast surface shapes, by leveraging the intra\u2010 and inter\u2010patient correspondences. These analysis provide complementary insights into how the breast changes over time: The intrinsic analysis evaluates deformation patterns directly on the shape manifolds, enabling the identification of regions exhibiting high conformal (bending) or area distortions (stretching). We also perform extrinsic analysis, where we align surface acquisitions of the treated breast with the CT\u2010derived skin surface to assess pointwise surface displacements and volume changes in the treated area, thereby producing quantitative measures such as displacement amplitudes (in mm) and relative volume changes (in percentage).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The qualitative shape collection analysis highlight deformations in the contra\u2010lateral breast and armpit areas, along with positioning shifts on the head or abdominal regions. On average, displacements within the treated breast exhibit amplitudes of 1\u20132 mm across sessions, with higher values observed at the time of the 25th irradiation session. Volume changes, inferred from surface variations, reached up to 10% over the course of treatment, with the majority of values ranging between 2% and 5%.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>A \u2010based geometric approach has been proposed for analyzing breast shape changes over the course of radiotherapy from surface data acquisitions. Based on a functional map framework, we develop a shape matching specialized for the breast data as well as a shape variability analysis within a unified space. Analysis across multiple patient datasets revealed a wide spectrum of breast changes despite a clinically acceptable quantitative average, demonstrating the power of our method to perform both quantitative and qualitative analysis of deformation patterns both on the individual and group level.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial Registration<\/jats:title>\n                    <jats:p>The clinical trial data used in this paper is registered under the ClinicalTrials.gov ID\u00a0NCT03801850.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70532","type":"journal-article","created":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T13:03:13Z","timestamp":1782824593000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Surface\u2010guided analysis of breast shape changes during postoperative radiotherapy by using a functional map framework"],"prefix":"10.1002","volume":"53","author":[{"given":"Pierre","family":"Galmiche","sequence":"first","affiliation":[{"name":"Laboiratoire ICube CNRS\u2013University of Strasbourg Strasbourg France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyewon","family":"Seo","sequence":"additional","affiliation":[{"name":"Laboiratoire ICube CNRS\u2013University of Strasbourg Strasbourg France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yvan","family":"Pin","sequence":"additional","affiliation":[{"name":"Institut Priv\u00e9 de Radioth\u00e9rapie de Metz (IPRM) Metz France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philippe","family":"Meyer","sequence":"additional","affiliation":[{"name":"Laboiratoire ICube CNRS\u2013University of Strasbourg Strasbourg France"},{"name":"Institut de Canc\u00e9rologie de Strasbourg Europe (ICANS) Strasbourg France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Georges","family":"No\u00ebl","sequence":"additional","affiliation":[{"name":"Laboiratoire ICube CNRS\u2013University of Strasbourg Strasbourg France"},{"name":"Institut de Canc\u00e9rologie de Strasbourg Europe (ICANS) Strasbourg France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michel","family":"De Mathelin","sequence":"additional","affiliation":[{"name":"Laboiratoire ICube CNRS\u2013University of Strasbourg Strasbourg France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,6,30]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.phro.2018.05.006"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejmp.2019.07.021"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2008.10.037"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1177\/030089161109700414"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.meddos.2011.11.008"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2006.04.042"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/mp.15532"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/acm2.12700"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12094-021-02617-6"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tipsro.2022.02.001"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejmp.2023.102566"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2185520.2185526"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3355089.3356524"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.14934"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.13123"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2601097.2601111"},{"key":"e_1_2_8_18_1","doi-asserted-by":"crossref","unstructured":"WangF HuangQ GuibasLJ.Image co\u2010segmentation via consistent functional maps. 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