Optimization of anastomotic technique and gastric conduit perfusion with hyperspectral imaging and machine learning in an experimental model for minimally invasive esophagectomy

F Nickel; A Studier-Fischer; B Özdemir; J Odenthal; L R Müller; S Knoedler; K F Kowalewski; I Camplisson; M M Allers; M Dietrich; K Schmidt; G A Salg; H G Kenngott; A T Billeter; I Gockel; C Sagiv; O E Hadar; J Gildenblat; L Ayala; S Seidlitz; L Maier-Hein; B P Müller-Stich

doi:10.1016/j.ejso.2023.04.007

Optimization of anastomotic technique and gastric conduit perfusion with hyperspectral imaging and machine learning in an experimental model for minimally invasive esophagectomy

Eur J Surg Oncol. 2023 Apr 18:S0748-7983(23)00444-4. doi: 10.1016/j.ejso.2023.04.007. Online ahead of print.

Authors

F Nickel¹, A Studier-Fischer², B Özdemir³, J Odenthal³, L R Müller⁴, S Knoedler³, K F Kowalewski⁵, I Camplisson⁶, M M Allers³, M Dietrich⁷, K Schmidt⁸, G A Salg³, H G Kenngott³, A T Billeter³, I Gockel⁹, C Sagiv¹⁰, O E Hadar¹⁰, J Gildenblat¹⁰, L Ayala¹¹, S Seidlitz¹², L Maier-Hein¹³, B P Müller-Stich¹⁴

Affiliations

¹ Department of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany; HIDSS4Health - Helmholtz Information and Data Science School for Health, Heidelberg and Karlsruhe, Germany.
² Department of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany; School of Medicine, Heidelberg University, Heidelberg, Germany.
³ Department of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany.
⁴ HIDSS4Health - Helmholtz Information and Data Science School for Health, Heidelberg and Karlsruhe, Germany; Division of Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany.
⁵ Department of Urology, Medical Faculty of Mannheim at the University of Heidelberg, Mannheim, Germany.
⁶ Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, USA.
⁷ Department of Anaesthesiology, Heidelberg University Hospital, Heidelberg, Germany.
⁸ Department of Anaesthesiology and Intensive Care Medicine, Essen University Hospital, Essen, Germany.
⁹ Department of Visceral, Transplantation, Thoracic and Vascular Surgery, Leipzig University Hospital, Leipzig, Germany.
¹⁰ DeePathology Ltd., Ra'anana, Israel.
¹¹ HIDSS4Health - Helmholtz Information and Data Science School for Health, Heidelberg and Karlsruhe, Germany; Division of Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany; Medical Faculty, Heidelberg University, Heidelberg, Germany.
¹² HIDSS4Health - Helmholtz Information and Data Science School for Health, Heidelberg and Karlsruhe, Germany; Division of Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany.
¹³ HIDSS4Health - Helmholtz Information and Data Science School for Health, Heidelberg and Karlsruhe, Germany; Division of Computer Assisted Medical Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Mathematics and Computer Science, Heidelberg University, Heidelberg, Germany; Medical Faculty, Heidelberg University, Heidelberg, Germany.
¹⁴ Department of General, Visceral, and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany; HIDSS4Health - Helmholtz Information and Data Science School for Health, Heidelberg and Karlsruhe, Germany. Electronic address: beat.mueller@clarunis.ch.

PMID: 37105869
DOI: 10.1016/j.ejso.2023.04.007

Abstract

Introduction: Esophagectomy is the mainstay of esophageal cancer treatment, but anastomotic insufficiency related morbidity and mortality remain challenging for patient outcome. Therefore, the objective of this work was to optimize anastomotic technique and gastric conduit perfusion with hyperspectral imaging (HSI) for total minimally invasive esophagectomy (MIE) with linear stapled anastomosis.

Material and methods: A live porcine model (n = 58) for MIE was used with gastric conduit formation and simulation of linear stapled side-to-side esophagogastrostomy. Four main experimental groups differed in stapling length (3 vs. 6 cm) and simulation of anastomotic position on the conduit (cranial vs. caudal). Tissue oxygenation around the anastomotic simulation site was evaluated using HSI and was validated with histopathology.

Results: The tissue oxygenation (ΔStO₂) after the anastomotic simulation remained constant only for the short stapler in caudal position (-0.4 ± 4.4%, n.s.) while it was impaired markedly in the other groups (short-cranial: -15.6 ± 11.5%, p = 0.0002; long-cranial: -20.4 ± 7.6%, p = 0.0126; long-caudal: -16.1 ± 9.4%, p < 0.0001). Tissue samples from avascular stomach as measured by HSI showed correspondent eosinophilic pre-necrotic changes in 35.7 ± 9.7% of the surface area.

Conclusion: Tissue oxygenation at the site of anastomotic simulation of the gastric conduit during MIE is influenced by stapling technique. Optimal oxygenation was achieved with a short stapler (3 cm) and sufficient distance of the simulated anastomosis to the cranial end of the gastric conduit. HSI tissue deoxygenation corresponded to histopathologic necrotic tissue changes. The experimental model with HSI and ML allow for systematic optimization of gastric conduit perfusion and anastomotic technique while clinical translation will have to be proven.

Keywords: Gastric conduit; Hyperspectral imaging; Linear stapled anastomosis; Minimally invasive esophagectomy; Porcine model; Simulation; Tissue perfusion.