With the increasing prevalence of obesity worldwide, bariatric surgery is becoming increasingly common. However, the mechanic of the gastric wall related to bariatric surgery complications remains to be investigated. This study aims to understand mechanical behaviour of stomach by developing advanced material laws for gastric tissue incorporating microstructure. A multi-scale characterisation of the porcine stomach wall was performed in the fundus and corpus anatomical regions and in circumferential and longitudinal orientations The protocol included uniaxial tensile testing until damage, survival analysis to provide damage probability, comparison of phenomenological (Fung and Ogden order 1, 2 and 3) and structural (Holzapfel fibre-reinforced) computational models fitted to the experimental data, and quantitative analysis of elastin and collagen fibre structure from histological slides. All constitutive models fitted the experimental data well (r 2 > 0.988 and RSME<3.8 kPa). Longitudinal and circumferential elastic modulus in quasi linear phase were respectively 1.75 ± 1.2 MPa, 0.76 ± 0.35 MPa for fundus, and 2.30 ± 0.66 MPa, 1.36 ± 0.89 MPa for corpus, highlighting significant differences between orientations in fundus and corpus, with an overall softer fundus in the circumferential direction. Microstructure analysis illustrated collagen and elastin fibre orientation, dispersion and density. As microstructure appears to play an important role in stomach biomechanics, model incorporating fibre structure such as Holzapfel fibre-reinforced model, seem best suited to describe the material behaviour of the stomach wall. Future research should complement these findings with an expanded sample set in human models.
Keyphrases
- bariatric surgery
- white matter
- diabetic retinopathy
- weight loss
- oxidative stress
- obese patients
- electronic health record
- risk factors
- endothelial cells
- randomized controlled trial
- metabolic syndrome
- type diabetes
- multiple sclerosis
- big data
- high resolution
- body mass index
- wound healing
- physical activity
- data analysis
- deep learning