Abstract
Background
Visualization of key anatomical landmarks is required during surgical Trans Abdominal Pre Peritoneal repair (TAPP) of inguinal hernia. The Critical View of the MyoPectineal Orifice (CVMPO) was proposed to ensure correct dissection. An artificial intelligence (AI) system that automatically validates the presence of key and marks during the procedure is a critical step towards automatic dissection quality assessment and video-based competency evaluation. The aim of this study was to develop an AI system that automatically recognizes the TAPP key CVMPO landmarks in hernia repair videos.
Methods
Surgical videos of 160 TAPP procedures were used in this single-center study. A deep neural network-based object detector was developed to automatically recognize the pubic symphysis, direct hernia orifice, Cooper’s ligament, the iliac vein, triangle of Doom, deep inguinal ring, and iliopsoas muscle. The system was trained using 130 videos, annotated and verified by two board-certified surgeons. Performance was evaluated in 30 videos of new patients excluded from the training data.
Results
Performance was validated in 2 ways: first, single-image validation where the AI model detected landmarks in a single laparoscopic image (mean average precision (MAP) of 51.2%). The second validation is video evaluation where the model detected landmarks throughout the myopectineal orifice visual inspection phase (mean accuracy and F-score of 77.1 and 75.4% respectively). Annotation objectivity was assessed between 2 surgeons in video evaluation, showing a high agreement of 88.3%.
Conclusion
This study establishes the first AI-based automated recognition of critical structures in TAPP surgical videos, and a major step towards automatic CVMPO validation with AI. Strong performance was achieved in the video evaluation. The high inter-rater agreement confirms annotation quality and task objectivity.
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Acknowledgements
We wish to thank all surgical department staff for their collaboration in the preparation of this manuscript and IRCAD France’s audiovisual team for their technical assistance.
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Dr. Yuko Kitagawa received lecture fees from CHUGAI PHARMACEUTICAL CO., LTD., TAIHO PHARMACEUTICAL CO., LTD., ASAHI KASEI PHARMA CORPORATION, Otsuka Pharmaceutical Factory Inc., SHIONOGI & CO., LTD., Nippon Covidien Inc., ONO PHARMACEUTICAL CO., LTD., Bristol-Myers Squibb K.K. Dr. Yuko Kitagawa was supported by grants from CHUGAI PHARMACEUTICAL CO., LTD., TAIHO PHARMACEUTICAL CO., LTD., Yakult Honsha Co. Ltd., AsahiKASEI Co., Ltd., Otsuka Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co., Ltd., ONO PHARMACEUTICAL CO., LTD., TSUMURA & CO., Kyouwa Hakkou Kirin Co., Ltd., DAINIPPON SUMITOMO PHARMA Co., Ltd., EA Pharma Co., Ltd., Astellas Pharma Inc., Toyama Chemical Co., Ltd., MEDICON INC., KAKEN PHARMACEUTICAL CO. LTD., Eisai Co., Ltd., Otsuka Pharmaceutical Factory Inc., TEIJIN PHARMA LIMITED, NIHON PHARMACEUTICAL CO., LTD., and Nippon Covidien Inc. Dr. Yuko Kitagawa held an endowed chair provided by CHUGAI PHARMACEUTICAL CO., LTD., and TAIHO PHARMACEUTICAL CO., LTD., outside the submitted work. Drs. Masashi Takeuchi1, Toby Collins, Clement Lipps, Mathieu Haller, Josiane Uwineza, Nariaki Okamoto, Richard Nkusi, Jacques Marescaux, Hirofumi Kawakubo, Cristians Gonzalez, Didier Mutter, Silvana Perretta, Alexandre Hostettler, and Bernard Dallemagne have no conflicts of interest or financial ties to disclose.
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Takeuchi, M., Collins, T., Lipps, C. et al. Towards automatic verification of the critical view of the myopectineal orifice with artificial intelligence. Surg Endosc 37, 4525–4534 (2023). https://doi.org/10.1007/s00464-023-09934-7
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DOI: https://doi.org/10.1007/s00464-023-09934-7