Abstract
Background
In digestive tract surgery, dissection of an avascular space consisting of loose connective tissue (LCT) appearing by countertraction improves oncological outcomes and reduces complications.1,2,3 Kumazu et al.4 described a deep learning approach that automatically segments LCT to help surgeons.4 During left colorectal surgery, lumbar splanchnic, hypogastric, and pelvic visceral nerve injuries cause sexual dysfunction and/or urinary issues.5 As nerve preservation is critical for functional preservation, the AI model Kumazu reported is named Eureka (Anaut Inc., Tokyo, Japan) and was developed to separate nerves automatically. The educative efficacy of intraoperative nerve visualization has been described.6 Artificial intelligence (AI) assisted navigation is expected to aid in the anatomical recognition of nerves and the safe dissection layers surrounding nerves in the future.
Methods
We used Eureka as an educational tool for surgeons’ training during laparoscopic colorectal surgery. The laparoscopic system used was Olympus VISERA ELITE3 (Tokyo, Japan).
Results
Total mesorectal excision (TME) was safely performed with nerve preservation. No postoperative complications occurred. Automatic segmentation and highlighting of LCT in the dissected layers, lumbar splanchnic, hypogastric, and pelvic visceral nerves (S3, S4), were performed in real time.
Conclusions
In colorectal cancer surgery, the nerves are vital anatomical structures serving as landmarks for dissection. Lumbar splanchnic, hypogastric, and pelvic visceral nerve injuries (S3, S4) cause sexual dysfunction or urinary disorders.5 Nerve preservation is important for functional preservation. AI-assisted navigation methods are noninvasive, user-friendly, and expected to improve in accuracy in the future. They have the potential to develop nerve-guided TME.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Heald RJ, Santiago I, Pares O, Carvalho C, Figueiredo N. The perfect total mesorectal excision obviates the need for anything else in the management of most rectal cancers. Clin Colon Rectal Surg. 201730: 324–332.
Di Buono G, Buscemi S, Cocorullo G, et al. Feasibility and safety of laparoscopic complete mesocolic excision (CME) for right-sided colon cancer: short-term outcomes. A randomized clinical study. Ann Surg. 2021274: 57–62.
Shinohara H, Haruta S, Ohkura Y, Udagawa H, Sakai Y. Tracing dissectable layers of mesenteries overcomes embryologic restrictions when performing infrapyloric lymphadenectomy in laparoscopic gastric cancer surgery. J Am Coll Surg. 2015220:e81–e87.
Kumazu Y, Kobayashi N, Kitamura N, et al. Automated segmentation by deep learning of loose connective tissue fibers to define safe dissection planes in robot-assisted gastrectomy. Sci Rep 202111: 21198.
Zhai ZC, Zhang WG, Gu J. Pelvic autonomic nerve preservation in rectal cancer: anatomical concept and clinical significance. Zhonghua Wei Chang Wai Ke Za Zhi. 202326: 68–74. Chinese.
Ryu. S, Goto K, Kitagawa T, et al. Real-time artificial intelligence navigation-assisted anatomical recognition for laparoscopic colorectal surgery. J Gastrointest Surg. 2023. https://doi.org/10.1007/s11605-023-05819-1.
Acknowledgments
The authors would like to thank the operating room staff of the Kawaguchi Municipal Medical Center. The authors would also like to thank Ms. Keika Iijima for her assistance with the colorectal cancer database. Finally, the authors would like to express special thanks to Nao Kobayashi, Yuta Kumazu, Sakiko Tamatani, and Kyohei Fukata (Anaut Inc.).
Funding
This work was supported by JSPS KAKENHI grant no. 22K16524.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ethical approval
This study was approved by the Research Ethics Committee of the Kawaguchi Municipal Medical Center (approval no.: 2022-27).
Disclosure
None
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Supplementary file1 (MP4 104081 KB)
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Ryu, S., Goto, K., Imaizumi, Y. et al. Laparoscopic Colorectal Surgery with Anatomical Recognition with Artificial Intelligence Assistance for Nerves and Dissection Layers. Ann Surg Oncol 31, 1690–1691 (2024). https://doi.org/10.1245/s10434-023-14633-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1245/s10434-023-14633-7