Evaluatie van de maturiteit van geengineerd skeletspierweefsel en microstructuurgebaseerde hyperelastische modellering van menselijke abdominale fascia

Tissue engineering offers a promising approach for regenerative medicine in the long term and requires both effective protocols for tissue culture and a precise understanding of tissue functions and properties. Based on the expertise of the Tissue Engineering Lab and the LaMcube laboratory hosting this research, we focus on skeletal muscle tissue engineering and on the mechanical modeling of human abdominal fascia. Engineered skeletal muscles currently display maturity and function well below that of native tissue, which hinders translation to clinical transplantation, as well as other applications such as drug screening and disease modeling. Therefore, enhancing artificial muscle growth and contractile potential is a central challenge in the field. In turn, this requires relevant and robust indicators for tracking muscle maturity. Our first objective aims to further improve and broaden access to such indicators for the evaluation of engineered skeletal muscle tissue. In parallel, we investigate the mechanical properties of human abdominal fascia. This tissue has a fibrous, multi-layered, and strongly oriented architecture, making its behavior highly anisotropic and non-linear. Accurate models of this tissue find application in multiple aspects of medical research, including childbirth simulations and surgical implant design. Yet, microstructural parameters of the tissue, which strongly influence its mechanical behavior, remain insufficiently used in many studies. To address this, our second objective is to propose a microstructure-based mechanical model of human abdominal fascia that accounts for microstructural properties quantified at the pixel scale. Building on state-of-the-art methods, this study first presents an AI-based solution for the automatic quantification of fusion index in muscle cell cultures, an indicator tracking the development of the muscle cells. This solution is released as an open-source Python module for broad use. To evaluate a complementary marker of muscle maturity, we describe an automated platform for the optical tracking of passive tension in engineered muscles over weeks of culture, which we use to rank culture conditions. We also introduce a general-purpose framework for driving complex experimental tests in an accessible way ('Crappy'), which ensures hardware synchronization and parallelization of experimental tasks. To process transparency images of human abdominal fascia acquired with Crappy, we propose a pipeline that extracts per-pixel fiber orientation and orientation dispersion, as well as other relevant indicators. Finally, we introduce a hyperelastic constitutive law for the modeling of human abdominal fascia, based on the orientation homogenization of the local stiffness tensor as modulated by microstructural parameters. This law is combined with experimental data and tissue images to perform pixel-wise analyses and yield material parameters of the fascia. This work advances methods for evaluating the maturity of engineered tissue constructs, and demonstrates the feasibility of quantifying microstructural properties and incorporating them into a mechanical model of human abdominal fascia at the pixel scale. Although these avenues of research are currently independent, they both contribute to the long-term objective of engineering functional tissue replacements for the abdominal wall.