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Computational evaluation of laparoscopic sleeve gastrectomy.
Ilaria Toniolo1,2, Chiara Giulia Fontanella3,4, Michel Gagner5
1Department of Industrial Engineering, University of Padova, Via Venezia, 1, Padova, Italy. ilaria.toniolo.1@phd.unipd.it.
Updates in Surgery
|April 5, 2021
Summary
Computational models of sleeve gastrectomy (LSG) reveal how bougie size impacts stomach volume and wall stress. Larger bougie sizes increase volume and stress, particularly in the antrum and mucosa, offering insights for surgical design optimization.
Area of Science:
- Bioengineering and Medical Device Design
- Gastroenterology and Bariatric Surgery
Background:
- Laparoscopic sleeve gastrectomy (LSG) is a common bariatric procedure with a low complication rate.
- Suboptimal weight loss or weight regain after LSG indicates potential for surgical design improvement.
- A bioengineering approach can help refine LSG techniques to minimize complications.
Purpose of the Study:
- To develop computational models of the sleeved stomach based on varying bougie sizes (27-54 Fr).
- To analyze endoluminal pressure, basal volume, and gastric wall elongation under different intragastric pressures.
- To quantify the impact of LSG design on mechanoreceptors influencing satiety.
Main Methods:
- Development of computational LSG models using a range of bougie sizes.
- Calculation of endoluminal pressure and basal volume at varying intragastric pressures (up to 22.5 mmHg).
- Assessment of gastric wall elongation strain distribution across different regions and layers.
Main Results:
- Basal stomach volume significantly increased with larger bougie sizes; the 54 Fr model showed a 6-fold greater volume than the 27 Fr model at 22.5 mmHg.
- Elongation strain in the gastric wall demonstrated an increasing trend with larger bougie sizes.
- The antrum and mucosa were identified as the most stressed regions/layers, respectively, with increasing pressure.
Conclusions:
- Computational modeling and bioengineering offer quantitative insights into LSG design parameters.
- These methods can help predict and improve surgical outcomes by identifying critical design aspects.
- Advanced computational tools may facilitate the development of novel, less invasive bariatric procedures.
