OBJECTIVE(S): To develop and assess AI algorithms to identify operative steps in laparoscopic sleeve gastrectomy (LSG). BACKGROUND: Computer vision, a form of artificial intelligence (AI), allows for quantitative analysis of video by computers for identification of objects and patterns, such as in autonomous driving. METHODS: Intraoperative video from LSG from an academic institution was annotated by 2 fellowship-trained, board-certified bariatric surgeons. Videos were segmented into the following steps: 1) port placement, 2) liver retraction, 3) liver biopsy, 4) gastrocolic ligament dissection, 5) stapling of the stomach, 6) bagging specimen, and 7) final inspection of staple line. Deep neural networks were used to analyze videos. Accuracy of operative step identification by the AI was determined by comparing to surgeon annotations. RESULTS: Eighty-eight cases of LSG were analyzed. A random 70% sample of these clips was used to train the AI and 30% to test the AI's performance. Mean concordance correlation coefficient for human annotators was 0.862, suggesting excellent agreement. Mean (±SD) accuracy of the AI in identifying operative steps in the test set was 82% ± 4% with a maximum of 85.6%. CONCLUSIONS: AI can extract quantitative surgical data from video with 85.6% accuracy. This suggests operative video could be used as a quantitative data source for research in intraoperative clinical decision support, risk prediction, or outcomes studies.
OBJECTIVE(S): To develop and assess AI algorithms to identify operative steps in laparoscopic sleeve gastrectomy (LSG). BACKGROUND: Computer vision, a form of artificial intelligence (AI), allows for quantitative analysis of video by computers for identification of objects and patterns, such as in autonomous driving. METHODS: Intraoperative video from LSG from an academic institution was annotated by 2 fellowship-trained, board-certified bariatric surgeons. Videos were segmented into the following steps: 1) port placement, 2) liver retraction, 3) liver biopsy, 4) gastrocolic ligament dissection, 5) stapling of the stomach, 6) bagging specimen, and 7) final inspection of staple line. Deep neural networks were used to analyze videos. Accuracy of operative step identification by the AI was determined by comparing to surgeon annotations. RESULTS: Eighty-eight cases of LSG were analyzed. A random 70% sample of these clips was used to train the AI and 30% to test the AI's performance. Mean concordance correlation coefficient for human annotators was 0.862, suggesting excellent agreement. Mean (±SD) accuracy of the AI in identifying operative steps in the test set was 82% ± 4% with a maximum of 85.6%. CONCLUSIONS: AI can extract quantitative surgical data from video with 85.6% accuracy. This suggests operative video could be used as a quantitative data source for research in intraoperative clinical decision support, risk prediction, or outcomes studies.
Authors: M Wagner; A Schulze; S Bodenstedt; L Maier-Hein; S Speidel; F Nickel; F Berlth; B P Müller-Stich; Peter Grimminger Journal: Chirurg Date: 2022-01-24 Impact factor: 0.955
Authors: Dolores Müller; Raphael Stier; Jennifer Straatman; Benjamin Babic; Lars Schiffmann; Jennifer Eckhoff; Thomas Schmidt; Christiane Bruns; Hans F Fuchs Journal: Chirurgie (Heidelb) Date: 2022-06-03
Authors: Martin Wagner; Johanna M Brandenburg; Sebastian Bodenstedt; André Schulze; Alexander C Jenke; Antonia Stern; Marie T J Daum; Lars Mündermann; Fiona R Kolbinger; Nithya Bhasker; Gerd Schneider; Grit Krause-Jüttler; Hisham Alwanni; Fleur Fritz-Kebede; Oliver Burgert; Dirk Wilhelm; Johannes Fallert; Felix Nickel; Lena Maier-Hein; Martin Dugas; Marius Distler; Jürgen Weitz; Beat-Peter Müller-Stich; Stefanie Speidel Journal: Surg Endosc Date: 2022-09-28 Impact factor: 3.453
Authors: Tyler J Loftus; Amanda C Filiberto; Yanjun Li; Jeremy Balch; Allyson C Cook; Patrick J Tighe; Philip A Efron; Gilbert R Upchurch; Parisa Rashidi; Xiaolin Li; Azra Bihorac Journal: Surgery Date: 2020-06-13 Impact factor: 3.982
Authors: Alexander Urbanski; Benjamin Babic; Wolfgang Schröder; Lars Schiffmann; Dolores T Müller; Christiane J Bruns; Hans F Fuchs Journal: Chirurg Date: 2021-02 Impact factor: 0.955