Biomechanical stability of hernia-damaged abdominal walls

Abstract

AbstractHernia occurs when the peritoneum and/or internal organs penetrate through a defect in the abdominal wall. Implanting mesh fabrics is a common way to reinforce the repair of hernia-damaged tissues, despite the risks of infection and failure associated with them. However, there is neither consensus on the optimum mesh placement within the abdominal muscles complex nor on the minimum size of hernia defect that requires surgical correction. Here we show that the optimum position of the mesh depends on the hernia location; placing the mesh on the transversus abdominis muscles reduces the equivalent stresses in the damaged zone and represents the optimum reinforcement solution for incisional hernia. However, retrorectus reinforcement of the linea alba is more effective than preperitoneal, anterectus, and onlay implantations in the case of paraumbilical hernia. Using the principles of fracture mechanics, we found that the critical size of a hernia damage zone becomes severe at 4.1 cm in the rectus abdominis and at larger sizes (5.2–8.2 cm) in other anterior abdominal muscles. Furthermore, we found that the hernia defect size must reach 7.8 mm in the rectus abdominis before it influences the failure stress. In other anterior abdominal muscles, hernia starts to influence the failure stress at sizes ranging from 1.5 to 3.4 mm. Our results provide objective criteria to decide when a hernia damage zone becomes severe and requires repair. They demonstrate where mesh should be implanted for a mechanically stable reinforcement, depending on the type of hernia. We anticipate our contribution to be a starting point for sophisticated models of damage and fracture biomechanics. For example, the apparent fracture toughness is an important physical property that should be determined for patients living with different obesity levels. Furthermore, relevant mechanical properties of abdominal muscles at various ages and health conditions would be significant to generate patient specific results.