Computed Tomography-based Finite Element Modelling (CT-FEM) integrates engineering, biology and medicine in computational biomechanics, making significant progress in digital health. This approach provides realistic geometries, which contribute to understanding and simulating the accurate mechanical behavior of various biological structures. CT-FEM enables precise prediction and intricate biomechanical analysis, including the examination of cell, tissue, and organ behavior under various loading circumstances. These insights provide valuable information for the development of medical devices, therapies, treatments, and interventions.

CT-FEM is one of the most promising tools used in biomechanics, but it also presents several challenges. One of the primary concerns is accurate modelling of the geometrical properties and the mechanical properties of biological tissues, which can vary significantly depending on the individual or situation. The complex hierarchical nature of biomechanical activity, from the cellular level to the entire organ, is another significant challenge that must be considered. To ensure that the models accurately represent the real-world behavior of biological tissues, they must be validated and verified against experimental data, while accounting for uncertainties in parameters and boundary conditions. The high computational cost of detailed simulations is yet another challenge that requires access to efficient algorithms and high-performance computing resources.

The proposed Research Topic seeks to address the current challenges and showcase the latest advancements in CT-FEM. It aims to promote collaboration among researchers from various fields and share novel methods, insights, and applications. By compiling a collection of cutting-edge original research and review articles, this topic will contribute to the development of more accurate, reliable, and clinically relevant CT-FEM studies.

Potential topics include but are not limited to the following:
• The effect of medical devices and tools on biological tissues;
• Personalized biomechanical simulations;
• CT-FEM and their real-world validation;
• Integration of experimental data and computational models;
• Medical decision-making with respect to CT-FEM;
• Multi-scale engineering modelling of tissue mechanics and interactions;
• Target based-multiple organ simulation;
• Characterization of mechanical properties of biological tissues using advanced imaging;
• Biomechanics of joint replacement and implants;
• Biomechanics of tumor growth and response to treatment;
• Biomechanical models for drug delivery;
• Biomechanics of soft tissues;
• Determination of the mechanical properties of biological tissues;
• Efficient algorithms for large-scale biomechanical simulations;
• Uncertainty quantification in computational biomechanics;
• Computational biomechanics in orthopedics and musculoskeletal disorders;
• Cardiovascular biomechanics and patient-specific simulations;
• Pulmonary biomechanics and patient-specific simulation;
• Fluid-structure interactions in biological systems;
• Simulation-based training and education in biomechanics;
• Translation of computational biomechanics research to clinical practice.

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Frontiers in Digital Health

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