Modelo Digital Twin como Ferramenta para Melhorar a Abordagem Cirúrgica para Prolapso dos Órgãos Pélvicos

Despite significant clinical research, progress in reducing mesh-related complications (MRCs) post-surgeries has been sluggish, emphasizing the need for innovative tools to enhance biomechanical understanding and improve therapeutic interventions. The TREAT-POP aims to reduce postoperative MRCs, re-operation rates, and healthcare costs. It also aims to assist manufacturers in aligning with FDA recommendations[9] by utilizing biomechanical simulation for safer and more effective clinical procedures. Including biodegradable (BD) implants enhances the potential for personalized and effective treatment of pelvic organ prolapse (POP). TREAT-POP seeks to create advanced computational tools, like Digital Twin Model (DTM), for better pre-surgical planning. These models consider pelvic structures, implant properties, and geometry to realistically simulate the pelvic cavity before and after surgery. This technique enables personalized patient analysis and the design of customized therapies, including the use of BD implants. TREAT-POP aims to characterize the material properties of pelvic soft tissues using MRI and optimization algorithms, adapting a methodology previously used by our research group to estimate in vivo biomechanical properties of PFM and bladder tissue [22]. The project aims to ascertain the in vivo biomechanical properties of both passive and active pelvic structures, using nonlinear constitutive modeling. By employing a vaginal transducer to measure intravaginal pressure, the research seeks to map intra-abdominal pressure (IAP), quantifying stress and forces under various conditions. This effort contributes to a comprehensive database of biomechanical properties and IAP for patients with diverse characteristics. Biodegradable implants will be made using a 3D printing prototype called melt electrowriting (MEW). The microstructure's mechanical properties will be studied using scanning electron microscopy (SEM) during tensile testing. Neural Networks (NN) will be employed to analyze the multiscale features of these implants, playing a key role in predicting and modeling their overall structural behavior. In vitro degradation experiments will simulate in vivo conditions. Using uniaxial and biaxial loads in experiments will help estimate how surgical implants behave, which is vital for predicting potential instabilities. Tension analysis will validate computational models and introduce a new hyperelastic model for biodegradable implants, considering degradation time, water diffusion, and hydrolysis kinetics. The goal is to synchronize the implant's mechanical degradation with tissue regeneration time. Collaborating with internationally research groups and leveraging our Research Group's pelvic biomechanics expertise, TREAT-POP is built on a strong foundation. The project concentrates on patient-specific modeling, employing morphing techniques for pelvic structure adaptation, and adapting inverse finite element analysis to estimate the in vivo biomechanical properties of pelvic tissues. Additionally, subject-specific mesh implants produced through melt electrowriting (MEW) enrich the project’s scope. Ultimately, TREAT-POP seeks to redefine our understanding of predicting surgery outcomes, enhancing the quality of life for women undergoing POP surgeries, reduce recurrence rates, alleviate the financial impact on National Health Care Systems’ costs, and contribute to sustainable and efficient healthcare systems globally.