{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T05:18:04Z","timestamp":1787807884366,"version":"build-2784847793"},"reference-count":32,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T00:00:00Z","timestamp":1783641600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T00:00:00Z","timestamp":1783641600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Robotics Computer Surgery"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>This single\u2010centre study aimed to implement and internally validate a deep learning pipeline based on a 3D SegResNet architecture for automatic segmentation of renal vascular structures from contrast\u2010enhanced CT images, enabling accurate three\u2010dimensional reconstructions to support surgical planning in robot\u2010assisted partial nephrectomy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Ninety\u2010seven CT scans from patients with renal masses treated between January 2019 and September 2025 were included, with 68 used for training and 29 held out as an independent test set, never seen by the model during training. Imaging data included arterial and portal phases, and manual segmentations served as the ground truth. A 3D SegResNet architecture was implemented with spatial normalisation, isotropic resampling, data augmentation and tailored pre\u2010 and post\u2010processing.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The model achieved mean DICE scores of 0.86 for renal arteries and 0.81 for renal veins, with HD95 of 6.4\u00a0\u00b1\u00a02.8\u00a0mm and ASSD of 0.58\u00a0\u00b1\u00a00.22\u00a0mm for arteries, and HD95 of 8.7\u00a0\u00b1\u00a03.5\u00a0mm and ASSD of 0.94\u00a0\u00b1\u00a00.41\u00a0mm for veins, demonstrating high concordance with manual segmentation and correctly identifying most vascular structures. Performance was lower for distal intraparenchymal branches and in cases with multiple renal arteries or veins.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Overall, this feasibility study supports the technical viability of automated, standardized and cost\u2010effective tools for surgical planning.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/rcs.70207","type":"journal-article","created":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T19:09:13Z","timestamp":1783710553000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Development of an Artificial Intelligence\u2013Driven Three\u2010Dimensional Reconstruction Model of Renal Vasculature for Surgical Planning in Robot\u2010Assisted Partial Nephrectomy"],"prefix":"10.1002","volume":"22","author":[{"given":"Davide","family":"Brusa","sequence":"first","affiliation":[{"name":"University of Verona Urology Unit AOUI Verona  Verona Italy"},{"name":"Urology Unit Santissima Trinit\u00e0 Hospital  Borgomanero Novara Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Riccardo","family":"Bertolo","sequence":"additional","affiliation":[{"name":"University of Verona Urology Unit AOUI Verona  Verona Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Ditonno","sequence":"additional","affiliation":[{"name":"University of Verona Urology Unit AOUI Verona  Verona Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Greta","family":"Pettenuzzo","sequence":"additional","affiliation":[{"name":"University of Verona Urology Unit AOUI Verona  Verona Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7805-4814","authenticated-orcid":false,"given":"Lorenzo Pierangelo","family":"Treccani","sequence":"additional","affiliation":[{"name":"University of Verona Urology Unit AOUI Verona  Verona Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandro","family":"Veccia","sequence":"additional","affiliation":[{"name":"University of Verona Urology Unit AOUI Verona  Verona Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Filippo","family":"Caudana","sequence":"additional","affiliation":[{"name":"University of Verona Urology Unit AOUI Verona  Verona Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Fontana","sequence":"additional","affiliation":[{"name":"Urology Unit Santissima Trinit\u00e0 Hospital  Borgomanero Novara Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria Angela","family":"Cerruto","sequence":"additional","affiliation":[{"name":"University of Verona Urology Unit AOUI Verona  Verona Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandro","family":"Antonelli","sequence":"additional","affiliation":[{"name":"University of Verona Urology Unit AOUI Verona  Verona Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,10]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2017.12.027"},{"key":"e_1_2_12_3_1","doi-asserted-by":"publisher","DOI":"10.1159\/000495618"},{"key":"e_1_2_12_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajur.2022.06.003"},{"key":"e_1_2_12_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.euros.2022.02.006"},{"key":"e_1_2_12_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.euo.2022.09.003"},{"key":"e_1_2_12_7_1","doi-asserted-by":"crossref","unstructured":"I. 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