Development of an ontology for laparoscopic transabdominal adrenalectomy via a comprehensive modified Delphi survey and its validation on a multicentric pilot data set for surgical training and future video analysis with machine learning algorithms

作者：Barbara Seeliger, Sofia Di Lorenzo, Pier Francesco Alesina, Laurent Brunaud, Costanza Chiapponi, Carmela De Crea, Gianluca Donatini, Maurizio Iacobone, Özer Makay, Radu Mihai, Martina T. Mogl, Didier Mutter, Nicolas Padoy, Fausto Palazzo, Óscar Vidal, Francesco Pennestrì, Jacques Marescaux, Michel Vix, Marco Raffaelli · 发表于：British journal of surgery · 年份：2024 · DOI：10.1093/bjs/znae148 · 被引用次数：8 · 研究领域：Adrenal and Paraganglionic Tumors、Cardiac, Anesthesia and Surgical Outcomes、Health and Medical Research Impacts

Lay Summary Surgical technique is essential to ensure safe minimally invasive adrenalectomy. Due to the relative rarity of adrenal surgery, it is challenging to ensure adequate exposure in surgical training. Surgical video analysis supports auto-evaluation, expert assessment and could be a target for automatization. The developed ontology was validated by a European expert consensus and is applicable across the surgical techniques encountered in all participating centres, with an exemplary demonstration in bi-centric recordings. Standardization of adrenalectomy video analysis may foster surgical training and enable machine learning training for automated safety alerts.