Izabela Lubowiecka

Effective treatment of abdominal hernia with synthetic implants requires a prosthetic material biologically and mechanically compatible with the tissue. The mechanical compatibility is particularly important because the human abdominal wall is a complex multilayer structure and its properties may have individual characteristics that are not fully known. To address this issue, we propose a novel approach to optimal implant design for hernia repair by modifying locally the implant thickness to adapt it to the applied loads. Compatibility criteria are translated to an objective function that is to be minimized in the optimization procedure. The objective function is designed to equalize and minimize forces at the tissue‐implant interface and minimize implant deflection. This reduces vulnerability to failure without hindering functionality. The input data are taken from in vivo tests on human subjects performed using digital image correlation and applied to a computational model of the implant defined by means of the Finite Element Method. The results show that the material distribution varies across models with different properties in two perpendicular directions (i.e., orthotropy) and across individuals, suggesting the potential for patient‐specific design of the implant and a patient‐specific approach to hernia repair. This approach takes into account abdominal wall heterogeneity and anisotropy, which in practice may help to reduce the ventral hernia recurrence rate.

Despite being a common procedure, abdominal hernia treatments still require improvement due to the number of relapses and other postoperative issues. In silico testing can be employed to predict the behavior of the complex abdominal wall and implant systems. Here, uncertainty quantification and sensitivity analysis are required in order to optimize the parameters of hernia repair models. This paper concerns the modeling of an abdominal wall and implant using the finite element method. A Gasser‐Ogden‐Holzapfel (GOH) material model is used for the abdominal wall and an orthotropic material model for the implant. The parameters of the GOH model and the orientation of the implant are assumed to be uncertain. Regression‐based polynomial chaos expansion is used as a meta‐modeling method for uncertainty propagation and global sensitivity analysis. The maximum force in the connection between the implant and native tissue is considered as the quantity of interest. A failure risk criterion is also defined and presented. It has been found that the significance of the material parameters depends on the type of implant that is analyzed. Likewise, the risk of connection failure varies considerably depending on the implant used. Models with different types of implant produce very diverse results. Moreover, these differences also appear in the global sensitivity index and the risk of connection failure. This would indicate that specific implant designs and material properties are crucial to the success of hernia repair surgery.

The study refers to the application of a type of artificial neural network called the Self-Organising Map (SOM) for the identification of areas of the human abdominal wall that perform in a similar mechanical way. The research was based on data acquired during in vivo tests using the digital image correlation technique (DIC). The mechanical behaviour of the human abdominal wall was analysed during changing intra-abdominal pressure. SOM allowed us to study simultaneously three variables in four time steps. The variables referred to the principal strains and their directions. SOM classified into clusters all the abdominal surface data points that behaved similarly in accordance with the 12 variables. The analysis of the clusters provided a better insight into abdominal wall deformation and its evolution under pressure than when observing a single mechanical variable. The presented results may provide a better understanding of the mechanics of the living human abdominal wall. It might be particularly useful in the designing of surgical meshes for the treatment of abdominal hernias, which would be mechanically compatible with identified regions of the human anterior abdominal wall, and possibly open the way for patient-specific implants.

The article focuses on the oldest surviving I-type portico houses located in the Vistula Delta, which were built in the 17th and 18th centuries. The study describes the houses’ origins, structure, details of roof structures and technical condition, and it also includes numerical modelling of a roof truss and its mechanical analysis. Numerical models of the roof trusses are defined and analysed by means of the finite element method. Global sensitivity analysis with the use of the polynomial chaos expansion method is used to study the influence of uncertainties in material properties of wood, such as Young’s modulus and the friction coefficient, and also the beam cross-sectional height in the output of the numerical model of the structure. The outcomes show that the uncertainty of beam height exerts the dominating influence on the maximum deflection of the roof truss, hence accurate measurements of geometry are of great importance in the planning of conservation and renovation of such historic structures.