{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T12:25:06Z","timestamp":1790771106243,"version":"4.1.0"},"reference-count":31,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2023,7,17]],"date-time":"2023-07-17T00:00:00Z","timestamp":1689552000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001665","name":"Agence Nationale de la Recherche","doi-asserted-by":"publisher","award":["ANR\u201011\u2010LABX\u20100004"],"award-info":[{"award-number":["ANR\u201011\u2010LABX\u20100004"]}],"id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003100","name":"F\u00e9d\u00e9ration Fran\u00e7aise de Cardiologie","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003100","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":[[2024,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Cardiac radioablation (CR) is an innovative treatment to ablate cardiac arrythmia sources by radiation therapy. CR target delineation is a challenging task requiring the exploitation of highly different imaging modalities, including cardiac electro\u2010anatomical mapping (EAM).<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>In this work, a data integration process is proposed to alleviate the tediousness of CR target delineation by generating a fused representation of the heart, including all the information of interest resulting from the analysis and registration of electro\u2010anatomical data, PET scan and planning computed tomography (CT) scan. The proposed process was evaluated by cardiologists during delineation\u00a0trials.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>The data processing pipeline was composed of the following steps. The cardiac structures of interest were segmented from cardiac CT scans using a deep learning method. The EAM data was registered to the cardiac CT scan using a point cloud based registration method. The PET scan was registered using rigid image registration. The EAM and PET information, as well as the myocardium thickness, were projected on the surface of the 3D mesh of the left ventricle. The target was identified by delineating a path on this surface that was further projected to the thickness of the myocardium to create the target volume. This process was evaluated by comparison with a standard slice\u2010by\u2010slice delineation with mental EAM registration. Four cardiologists delineated targets for three patients using both methods. The variability of target volumes, and the ease of use of the proposed method, were\u00a0evaluated.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>All cardiologists reported being more confident and efficient using the proposed method. The inter\u2010clinician variability in delineated target volume was systematically lower with the proposed method (average dice score of 0.62 vs. 0.32 with a classical method). Delineation times were also\u00a0improved.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>A data integration process was proposed and evaluated to fuse images of interest for CR target delineation. It effectively reduces the tediousness of CR target delineation, while improving inter\u2010clinician agreement on target volumes. This study is still to be confirmed by including more clinicians and patient data to the\u00a0experiments.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.16613","type":"journal-article","created":{"date-parts":[[2023,7,17]],"date-time":"2023-07-17T08:10:30Z","timestamp":1689581430000},"page":"292-305","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Multimodal fusion workflow for target delineation in cardiac radioablation of ventricular tachycardia"],"prefix":"10.1002","volume":"51","author":[{"given":"Louis","family":"Rigal","sequence":"first","affiliation":[{"name":"Univ Rennes, CHU Rennes, CLCC Eug\u00e8ne Marquis, Inserm, LTSI \u2013 UMR 1099 Rennes France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karim","family":"Benali","sequence":"additional","affiliation":[{"name":"Univ Rennes, CHU Rennes, CLCC Eug\u00e8ne Marquis, Inserm, LTSI \u2013 UMR 1099 Rennes France"},{"name":"Department of Cardiology Saint\u2010Etienne University Hospital Saint\u2010Priest\u2010En\u2010Jarez France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valentin","family":"Barr\u00e9","sequence":"additional","affiliation":[{"name":"Department of Cardiology Rennes University Hospital Rennes France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mathilde","family":"Bougault","sequence":"additional","affiliation":[{"name":"Department of Cardiology Rennes University Hospital Rennes France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julien","family":"Bellec","sequence":"additional","affiliation":[{"name":"Department of Cardiology Rennes University Hospital Rennes France"},{"name":"Medical Physics Department CLCC Eug\u00e8ne Marquis Rennes France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Renaud De","family":"Crevoisier","sequence":"additional","affiliation":[{"name":"Univ Rennes, CHU Rennes, CLCC Eug\u00e8ne Marquis, Inserm, LTSI \u2013 UMR 1099 Rennes France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rapha\u00ebl","family":"Martins","sequence":"additional","affiliation":[{"name":"Univ Rennes, CHU Rennes, CLCC Eug\u00e8ne Marquis, Inserm, LTSI \u2013 UMR 1099 Rennes France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antoine","family":"Simon","sequence":"additional","affiliation":[{"name":"Univ Rennes, CHU Rennes, CLCC Eug\u00e8ne Marquis, Inserm, LTSI \u2013 UMR 1099 Rennes France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,7,17]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1613773"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.118.038261"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCEP.122.010955"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1093\/europace\/euac238"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1540\u20108167.2009.01563.x"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.hrthm.2020.03.013"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmir.2021.09.007"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2020.10.036"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCEP.112.000191"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1111\/jce.13441"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.hrthm.2019.06.012"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2021.01.028"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1111\/jce.14660"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.prro.2020.04.006"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2021.07.424"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.hrcr.2022.09.008"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.phro.2022.12.003"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.adro.2023.101272"},{"key":"e_1_2_8_20_1","doi-asserted-by":"crossref","unstructured":"RonnebergerO FischerP BroxT.U\u2010Net: convolutional networks for biomedical image segmentation. 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