Automatic surgical phase recognition-based skill assessment in laparoscopic distal gastrectomy using multicenter videos

Nakamura K, Katai H, Mizusawa J, Yoshikawa T, Ando M, Terashima M, et al. A phase III study of laparoscopy-assisted versus open distal gastrectomy with nodal dissection for clinical stage IA/IB gastric cancer (JCOG0912). Jpn J Clin Oncol. 2013;43:324–7.

Article  PubMed  Google Scholar 

Katai H, Mizusawa J, Katayama H, Takagi M, Yoshikawa T, Fukagawa T, et al. Short-term surgical outcomes from a phase III study of laparoscopy-assisted versus open distal gastrectomy with nodal dissection for clinical stage IA/IB gastric cancer: Japan clinical oncology group study JCOG0912. Gastric Cancer. 2017;20:699–708.

Article  PubMed  Google Scholar 

Kim HH, Han SU, Kim MC, Kim W, Lee HJ, Ryu SW, et al. Effect of laparoscopic distal gastrectomy vs open distal gastrectomy on long-term survival among patients with stage i gastric cancer: The KLASS-01 randomized clinical trial. JAMA Oncol. 2019;5:506–13.

Article  PubMed  PubMed Central  Google Scholar 

Inaki N, Etoh T, Ohyama T, Uchiyama K, Katada N, Koeda K, et al. A multi-institutional, prospective, phase II feasibility study of laparoscopy-assisted distal gastrectomy with D2 lymph node dissection for locally advanced gastric cancer (JLSSG0901). World J Surg. 2015;39:2734–41.

Article  PubMed  Google Scholar 

Etoh T, Ohyama T, Sakuramoto S, Tsuji T, Lee SW, Yoshida K, et al. Five-year survival outcomes of laparoscopy-assisted vs open distal gastrectomy for advanced gastric cancer: the JLSSG0901 randomized clinical trial. JAMA Surg. 2023;158:445–54.

Article  PubMed  Google Scholar 

Kumamoto T, Kurahashi Y, Niwa H, Nakanishi Y, Ozawa R, Okumura K, et al. Laparoscopic suprapancreatic lymph node dissection using a systematic mesogastric excision concept for gastric cancer. Ann Surg Oncol. 2020;27:529–31.

Article  PubMed  Google Scholar 

Shibasaki S, Suda K, Nakauchi M, Nakamura T, Kadoya S, Kikuchi K, et al. Outermost layer-oriented medial approach for infrapyloric nodal dissection in laparoscopic distal gastrectomy. Surg Endosc. 2018;32:2137–48.

Article  PubMed  Google Scholar 

Wenguang W, Xuefeng W, Zhiping Z, Xiangsong W, Jianwei W, Songgang L, et al. Three-step method for lymphadenectomy in gastric cancer surgery: a single institution experience of 120 patients. J Am Coll Surg. 2011;212:200–8.

Article  PubMed  Google Scholar 

Birkmeyer JD, Finks JF, O’Reilly A, Oerline M, Carlin AM, Nunn AR, et al. Surgical skill and complication rates after bariatric surgery. N Engl J Med. 2013;369:1434–42.

Article  CAS  PubMed  Google Scholar 

Martin JA, Regehr G, Reznick R, MacRae H, Murnaghan J, Hutchison C, et al. Objective structured assessment of technical skill (OSATS) for surgical residents. Br J Surg. 1997;84:273–8.

CAS  PubMed  Google Scholar 

Vassiliou MC, Feldman LS, Andrew CG, Bergman S, Leffondré K, Stanbridge D, et al. A global assessment tool for evaluation of intraoperative laparoscopic skills. Am J Surg. 2005;190:107–13.

Article  PubMed  Google Scholar 

Kinoshita T, Komatsu M. Artificial intelligence in surgery and its potential for gastric cancer. J Gastric Cancer. 2023;23:400–9.

Article  PubMed  PubMed Central  Google Scholar 

Garrow CR, Kowalewski KF, Li L, Wagner M, Schmidt MW, Engelhardt S, et al. Machine learning for surgical phase recognition: a systematic review. Ann Surg. 2021;273:684–93.

Article  PubMed  Google Scholar 

Yamazaki Y, Kanaji S, Matsuda T, Oshikiri T, Nakamura T, Suzuki S, et al. Automated surgical instrument detection from laparoscopic gastrectomy video images using an open source convolutional neural network platform. J Am Coll Surg. 2020;230:725-32.e1.

Article  PubMed  Google Scholar 

Sasaki S, Kitaguchi D, Takenaka S, Nakajima K, Sasaki K, Ogane T, et al. Machine learning-based automatic evaluation of tissue handling skills in laparoscopic colorectal surgery: a retrospective experimental study. Ann Surg. 2023;278:e250–5.

Article  PubMed  Google Scholar 

Pernek I, Ferscha A. A survey of context recognition in surgery. Med Biol Eng Comput. 2017;55:1719–34.

Article  PubMed  Google Scholar 

Jin Y, Dou Q, Chen H, Yu L, Qin J, Fu CW, et al. SV-RCNet: Workflow recognition from surgical videos using recurrent convolutional network. IEEE Trans Med Imaging. 2018;37:1114–26.

Article  PubMed  Google Scholar 

Lalys F, Jannin P. Surgical process modelling: a review. Int J Comput Assist Radiol Surg. 2014;9:495–511.

Article  PubMed  Google Scholar 

Franke S, Rockstroh M, Hofer M, Neumuth T. The intelligent OR: design and validation of a context-aware surgical working environment. Int J Comput Assist Radiol Surg. 2018;13:1301–8.

Article  PubMed  Google Scholar 

Kitaguchi D, Takeshita N, Matsuzaki H, Igaki T, Hasegawa H, Ito M. Development and validation of a 3-dimensional convolutional neural network for automatic surgical skill assessment based on spatiotemporal video analysis. JAMA Netw Open. 2021;4: e2120786.

Article  PubMed  PubMed Central  Google Scholar 

Takeuchi M, Kawakubo H, Tsuji T, Maeda Y, Matsuda S, Fukuda K, et al. Evaluation of surgical complexity by automated surgical process recognition in robotic distal gastrectomy using artificial intelligence. Surg Endosc. 2023;37:4517–24.

Article  PubMed  PubMed Central  Google Scholar 

Brierley JGM, Wittekind C. TNM classification of malignant tumours. 8th ed. Oxford: Wiley Blackwell; 2017.

Google Scholar 

Japanese classification of gastric carcinoma: 3rd English edition. Gastric Cancer. 2011; 14: 101–12.

Japanese gastric cancer treatment guidelines 2018 (5th edition). Gastric Cancer. 2021; 24: 1–21

Akagi T, Endo H, Inomata M, Yamamoto H, Mori T, Kojima K, et al. Clinical impact of endoscopic surgical skill qualification system (ESSQS) by Japan society for endoscopic Surgery (JSES) for laparoscopic distal gastrectomy and low anterior resection based on the national clinical database (NCD) registry. Ann Gastroenterol Surg. 2020;4:721–34.

Article  PubMed  PubMed Central  Google Scholar 

Shibasaki S, Suda K, Nakauchi M, Nakamura K, Tanaka T, Kikuchi K, et al. Impact of the endoscopic surgical skill qualification system on the safety of laparoscopic gastrectomy for gastric cancer. Surg Endosc. 2021;35:6089–100.

Article  PubMed  Google Scholar 

Ichikawa N, Homma S, Funakoshi T, Ohshima T, Hirose K, Yamada K, et al. Impact of technically qualified surgeons on laparoscopic colorectal resection outcomes: results of a propensity score-matching analysis. BJS Open. 2020;4:486–98.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Tan M, Le QV (2020) EfficientNet: rethinking model scaling for convolutional neural networks. arXiv 11

Igaki T, Kitaguchi D, Matsuzaki H, Nakajima K, Kojima S, Hasegawa H, et al. Automatic surgical skill assessment system based on concordance of standardized surgical field development using artificial intelligence. JAMA Surg. 2023;158: e231131.

Article  PubMed  Google Scholar 

Kitaguchi D, Takeshita N, Matsuzaki H, Takano H, Owada Y, Enomoto T, et al. Real-time automatic surgical phase recognition in laparoscopic sigmoidectomy using the convolutional neural network-based deep learning approach. Surg Endosc. 2020;34:4924–31.

Article  PubMed  Google Scholar 

Kitaguchi D, Takeshita N, Matsuzaki H, Oda T, Watanabe M, Mori K, et al. Automated laparoscopic colorectal surgery workflow recognition using artificial intelligence: experimental research. Int J Surg. 2020;79:88–94.

Article  PubMed  Google Scholar 

Kitaguchi D, Takeshita N, Matsuzaki H, Hasegawa H, Igaki T, Oda T, et al. Deep learning-based automatic surgical step recognition in intraoperative videos for transanal total mesorectal excision. Surg Endosc. 2022;36:1143–51.

Article  PubMed  Google Scholar 

Hashimoto DA, Rosman G, Witkowski ER, Stafford C, Navarette-Welton AJ, Rattner DW, et al. Computer vision analysis of intraoperative video: automated recognition of operative steps in laparoscopic sleeve gastrectomy. Ann Surg. 2019;270:414–21.

Article  PubMed  Google Scholar 

Shinozuka K, Turuda S, Fujinaga A, Nakanuma H, Kawamura M, Matsunobu Y, et al. Artificial intelligence software available for medical devices: surgical phase recognition in laparoscopic cholecystectomy. Surg Endosc. 2022;36:7444–52.

Article  PubMed  PubMed Central  Google Scholar 

Cheng K, You J, Wu S, Chen Z, Zhou Z, Guan J, et al. Artificial intelligence-based automated laparoscopic cholecystectomy surgical phase recognition and analysis. Surg Endosc. 2022;36:3160–8.

Article  PubMed  Google Scholar 

Sasaki K, Ito M, Kobayashi S, Kitaguchi D, Matsuzaki H, Kudo M, et al. Automated surgical workflow identification by artificial intelligence in laparoscopic hepatectomy: Experimental research. Int J Surg. 2022;105: 106856.

Article  PubMed  Google Scholar 

Takeuchi M, Kawakubo H, Saito K, Maeda Y, Matsuda S, Fukuda K, et al. Automated surgical-phase recognition for robot-assisted minimally invasive esophagectomy using artificial intelligence. Ann Surg Oncol. 2022;29:6847–55.

Article  PubMed  Google Scholar 

Cao B, Xiao A, Shen J, Xie D, Gong J. An optimal surgical approach for suprapancreatic area dissection in laparoscopic D2 gastrectomy with complete mesogastric excision. J Gastrointest Surg. 2020;24:916–7.

Article  PubMed  Google Scholar 

Rindos NB, Wroble-Biglan M, Ecker A, Lee TT, Donnellan NM. Impact of video coaching on gynecologic resident laparoscopic suturing: a randomized controlled trial. J Minim Invasive Gynecol. 2017;24:426–31.

Article  PubMed  Google Scholar 

Soucisse ML, Boulva K, Sideris L, Drolet P, Morin M, Dubé P. Video coaching as an efficient teaching method for surgical residents-A randomized controlled trial. J Surg Educ. 2017;74:365–71.

Article  PubMed  Google Scholar 

Alameddine MB, Englesbe MJ, Waits SA. A video-based coaching intervention to improve surgical skill in fourth-year medical students. J Surg Educ. 2018;75:1475–9.

Article  PubMed 

留言 (0)

沒有登入
gif