Background: The stomach is a hollow organ of the gastrointestinal tract, on which bariatric surgery (BS) is performed for the treatment of obesity. Even though BS is the most effective treatment for severe obesity, drawbacks and complications are still present because the intervention design is largely based on the surgeon’s expertise and intraoperative decisions. Bioengineering methods can be exploited to develop computational tools for more rational presurgical design and planning of the intervention. Methods: A computational mechanical model of the stomach was developed, considering the actual complexity of the biological structure, as the nonhomogeneous and multilayered configuration of the gastric wall. Mechanical behavior was characterized by means of an anisotropic visco-hyperelastic constitutive formulation of fiber-reinforced conformation, nonlinear elastic response, and time-dependent behavior, which assume the typical features of gastric wall mechanics. Model applications allowed for an analysis of the influence of BS techniques on stomach mechanical functionality through different computational analyses. Results: Computational results showed that laparoscopic sleeve gastrectomy and endoscopic sleeve gastroplasty drastically alter stomach capacity and stiffness, while laparoscopic adjustable gastric banding modestly affects stomach stiffness and capacity. Moreover, the mean elongation strain values, which are correlated to the mechanical stimulation of gastric receptors, were elevated in laparoscopic adjustable gastric banding compared to other procedures. Conclusions: The investigation of stomach mechanical response through computational models provides information on different topics such as stomach capacity and stiffness and the mechanical stimulation of gastric receptors, which interact with the brain to control satiety. These data can provide reliable support to surgeons in the presurgical decision-making process.

Biomechanical Investigation of the Stomach Following Different Bariatric Surgery Approaches

Ilaria Toniolo;Chiara Giulia Fontanella
;
Mirto Foletto;Emanuele Luigi Carniel
2020

Abstract

Background: The stomach is a hollow organ of the gastrointestinal tract, on which bariatric surgery (BS) is performed for the treatment of obesity. Even though BS is the most effective treatment for severe obesity, drawbacks and complications are still present because the intervention design is largely based on the surgeon’s expertise and intraoperative decisions. Bioengineering methods can be exploited to develop computational tools for more rational presurgical design and planning of the intervention. Methods: A computational mechanical model of the stomach was developed, considering the actual complexity of the biological structure, as the nonhomogeneous and multilayered configuration of the gastric wall. Mechanical behavior was characterized by means of an anisotropic visco-hyperelastic constitutive formulation of fiber-reinforced conformation, nonlinear elastic response, and time-dependent behavior, which assume the typical features of gastric wall mechanics. Model applications allowed for an analysis of the influence of BS techniques on stomach mechanical functionality through different computational analyses. Results: Computational results showed that laparoscopic sleeve gastrectomy and endoscopic sleeve gastroplasty drastically alter stomach capacity and stiffness, while laparoscopic adjustable gastric banding modestly affects stomach stiffness and capacity. Moreover, the mean elongation strain values, which are correlated to the mechanical stimulation of gastric receptors, were elevated in laparoscopic adjustable gastric banding compared to other procedures. Conclusions: The investigation of stomach mechanical response through computational models provides information on different topics such as stomach capacity and stiffness and the mechanical stimulation of gastric receptors, which interact with the brain to control satiety. These data can provide reliable support to surgeons in the presurgical decision-making process.
2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3362366
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