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A new platform for laparoscopic training: initial evaluation of the ex-vivo live multivisceral training device

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Abstract

Background

Various training models have been developed for laparoscopic training. Inanimate models including cadavers, ex-vivo simulator, and virtual reality (VR), are less realistic and often fail to display specific events such as bleeding, bile leakage, etc. Animal models provide more realistic experience, but constraints like cost involved, anesthetic requirement, and ethical approval have limited its application. We have designed a new training ex-vivo simulator—Smagister to address these issues.

Methods

The Smagister consists of a normothermic machine perfusion platform, multivisceral organ of porcine abdominal cavity (liver, gallbladder, pancreas, stomach, intestine, kidney, uterus, bladders, etc.), high-definition display, and software system. Blood gas analysis and number of peristalsis per hour were recorded. A questionnaire was used to subjectively assess vitality of the organ cluster every hour. Three laparoscopic procedures including cholecystectomy (LC), enterotomy closure (LEC) and hepatectomy (LLR) were performed on Smagister, with demonstration of specific events for each procedure. Six experts compared the procedures with actual surgery in terms of feasibility to complete procedures and demonstration of complications.

Results

The fluctuation of perfusate glucose (6.1–8.2 mmol/L) and lactate (5.82–6.55 mmol/L) suggested metabolic function of the multivisceral organs. The mean number of peristalsis was 2.2/min. The simulated surgical view and anatomic structures closely resembled actual surgery during continuous perfusion (3.5 ± 1.0, 3.8 ± 0.8, respectively). The evaluation scores of haptic feedbacks were 3.8 ± 0.8, resembling live tissue handling. LC, LEC, and LLR were performed well on the Smagister, with clear display of the specific events. All six experts considered Smagister as a suitable training modality for both basic and advanced laparoscopic surgery.

Conclusion

The amalgamation of live animal model and ex-vivo simulation in Smagister centralizes the virtue of both modalities, expands the training field, and provides high-fidelity laparoscopic training for both novice and senior surgeons.

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Acknowledgements

The authors thank the experts for participating in the trial and the staff in Singularity Medicine company for their assistance with setting up the Smagister simulator.

Funding

This study was supported by the National Natural Science Foundation of China (81970564, 81471583 and 81570587), the Guangdong Provincial Key Laboratory Construction Projection on Organ Donation and Transplant Immunology (2013A061401007 and 2017B030314018), Guangdong Provincial Natural Science Funds for Major Basic Science Culture Project (2015A030308010), Guangdong Provincial Natural Science Funds for Distinguished Young Scholars (2015A030306025), Special Support Program for Training High Level Talents in Guangdong Province (2015TQ01R168) and Science and Technology Program of Guangzhou (201704020150).

Author information

Author notes

  1. Xiaobo Wang, Kunsong Zhang, and Wenjie Hu have contributed equally to this work co-first authors.

Authors and Affiliations

  1. Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, People’s Republic of China

    Xiaobo Wang, Zhiyong Guo, Qiang Zhao & Xiaoshun He

  2. Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, 510080, People’s Republic of China

    Xiaobo Wang, Zhiyong Guo, Qiang Zhao & Xiaoshun He

  3. Guangdong Provincial International Cooperation Base of Science and Technology, Guangzhou, 510080, People’s Republic of China

    Xiaobo Wang, Zhiyong Guo, Qiang Zhao & Xiaoshun He

  4. Department of Hepatobiliary Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People’s Republic of China

    Kunsong Zhang, Wenjie Hu & Ming Kuang

  5. Faculty of Medicine, University of Glasgow, Glasgow, Scotland, UK

    Serene Teo

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  1. Xiaobo Wang
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Correspondence to Qiang Zhao or Xiaoshun He.

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Disclosures

Xiaobo Wang, Kunsong Zhang, Wenjie Hu, Ming Kuang, Serene Teo, Zhiyong Guo, Qiang Zhao and Xiaoshun He have no conflicts of interest or financial ties to disclose.

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Wang, X., Zhang, K., Hu, W. et al. A new platform for laparoscopic training: initial evaluation of the ex-vivo live multivisceral training device. Surg Endosc 35, 374–382 (2021). https://doi.org/10.1007/s00464-020-07411-z

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