{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T03:46:36Z","timestamp":1791863196914,"version":"4.3.4"},"reference-count":30,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:00:00Z","timestamp":1777420800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T00:00:00Z","timestamp":1777420800000},"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":["Journal of Surgical Oncology"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Sentinel lymph node biopsy (SLNB) is standard for staging high\u2010risk melanoma, but current mapping provides limited spatial guidance. This pilot study assessed whether augmented reality (AR) projected 3D models can improve sentinel node localization compared with the gamma probe.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this prospective study, 10 melanoma patients undergoing SLNB at Sheba Medical Center had preoperative sentinel lymphoscintigraphy using SPECT\/CT imaging segmented to generate patient\u2010specific 3D models. Models were projected onto the patient via an AR headset before incision. Localization accuracy was measured as the deviation (mm) between AR3D\u2010identified and gamma probe\u2013identified sentinel lymph node positions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Ten patients were enrolled in this pilot study. The median age was 71 years (range 30\u201377). Primary tumor sites included upper limb (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20095), trunk (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20093), Lower Limb (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20091), and Head and Neck (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20091). The median Breslow thickness was 1.1\u2009mm (range 0.8\u201324\u2009mm), with ulceration in 2 cases. Model generation was successful in all patients, with each model projected onto the patient using the AR headset and evaluated by the surgeon prior to incision. The median deviation between AR3D model and the gamma probe localization was 12\u2009mm (range 0\u201340\u2009mm), with 43% of cases \u2264\u200910\u2009mm. No AR\u2010related complications occurred.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>AR\u2010based 3D modelling was feasible and safe for SLNB localization in melanoma. Although accuracy varied, in nearly half of the cases, AR3D model was within 10\u2009mm of the gamma probe detection. These preliminary results supported further refinement of the technique and evaluation in larger, multicenter trials.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jso.70282","type":"journal-article","created":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T04:44:01Z","timestamp":1777524241000},"page":"178-184","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Augmented Reality Based 3D Modelling for Sentinel Lymph Node Localization in Cutaneous Melanoma: A Pilot Study"],"prefix":"10.1002","volume":"134","author":[{"given":"Qais","family":"Adawi","sequence":"first","affiliation":[{"name":"Division of Surgery, Surgical Oncology Unit, Sheba Medical Center Affiliated with Tel Aviv University Ramat\u2010Gan Israel"},{"name":"The Surgical Innovation Laboratory, ARC Innovation Center Sheba Medical Center Ramat\u2010Gan 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