PADLOCK · Personalized forecasting of prostate cancer growth through advanced nonlinear biomechanical model supported by locally adaptive, locking-free isogeometric methods

Prostate cancer (PCa) is the second most diagnosed cancer and the fifth leading cause of cancer-related deaths among men worldwide in 2022. However, current clinical practice often remains inadequate with limited individualization, leading to overdiagnosis, overtreatment, and undertreatment. A spatiotemporal biomechanistic model informed by multiparametric magnetic resonance imaging offers a powerful tool to address these challenges. Isogeometric analysis (IGA) and local h-adaptivity further contribute to accurately represent the complex biostructures and capture tumor dynamics. Hence, this technology enables personalized forecasting of PCa growth following its first diagnosis, leading to improved clinical and therapeutic decision-making. However, the existing models of PCa growth present fundamental limitations in predictive accuracy and computational efficiency. In this project, we will address three issues underlying those limitations: a suboptimal adaptive scheme for IGA, susceptibility to numerical locking due to the near-incompressible mechanical behavior of biostructures, and the assumption of linear elasticity. Towards this end, this project will follow a multifaceted approach that includes the integration of truncated hierarchical B-splines to enhance the adaptive IGA scheme, the use of mixed formulations to circumvent the adverse effects of volumetric locking while modeling near-incompressible biological tissues, and the incorporation of geometric and material nonlinearities to improve the accuracy of displacement and stress fields. Through these transformative strategies, the proposed model will represent a substantial step forward in the development of clinically viable predictive digital twins for PCa growth. This project aligns closely with the objectives of the European Commission’s cancer mission and could positively impact individuals with PCa. My expertise in IGA, locking, and biomechanics, uniquely equips me to achieve the project's objectives.