Material Parameter Identification and Inverse Problems in Soft Tissue Biomechanics

October 16, 2017 — October 20, 2017

Coordinators:

  • Sam Evans (Cardiff University, Cardiff, Great Britain)
  • Stéphane Avril (Université de Lyon, Lyon, France)

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This advanced school follows the very successful and popular school CISM C1511 that took place at Udine from 2015, Oct 12 to Oct 16. It gathered six of the best worldwide specialists in hybrid experimental – computational methods applied to soft tissues, to teach focused and highly original courses in this area. Forty delegates registered to this course. They all appreciated learning skills in this multidisciplinary environment. Repeating this summer school will continue addressing this clear need within the biomedical engineering research community.
There are many fields in medicine and in biomedical engineering where accurate measurements of local soft tissue properties are needed. In general it is difficult to measure the mechanical properties of these materials directly and some kind of inverse approach is needed, where an experiment has to be simulated and the material parameters are adjusted until the model matches the experiment.
Several open questions are raised by inverse approaches in soft tissue biomechanics:
– Experimental measurements on biological tissues present many practical and theoretical difficulties. Experimental and numerical errors also increase the uncertainty, as do inadequate constitutive models.
– An inverse problem requires a computational model that can be solved repeatedly with different material parameters. This requires a model that can be solved quickly and reliably; these are not attributes one usually associates with computational models of biological tissues.
– Biological tissue mechanical behaviour exhibits special characteristics that may affect the mechanical response and disturb material identification, such as visco-elasticity, multi-scale properties, variability of properties and remodelling. Tissues often develop regionally varying stiffness, strength and anisotropy. Important challenges in soft tissue mechanics are now to develop and implement hybrid experimental – computational methods to quantify regional variations in properties in situ.
– Once the necessary experimental data and computational models are in place, it is essential to implement an appropriate optimisation strategy to adjust the material parameters to give the best match with the experimental results, and to consider issues of uniqueness of the identified parameters.
– the question of uniqueness can be tackled by increasing the quantity of experimental data. To this purpose, tracking the full-field deformation of tissues using optical measurements or medical imaging techniques becomes quite commonplace but these novel measurement approaches have only been recently applied to material identification of biological tissues and they still have to be well calibrated and validated for them.
– It has also been identified that in certain situations useful patient-specific results can be obtained without precise knowledge of patient-specific properties of tissues. This situation arises for instance in image-guided surgery and modelling and analysis of thin-walled biological organs.
Learning skills in this multidisciplinary environment is challenging, and rarely addressed to a sufficient level within classical degree programs. The advanced school will gather the best worldwide specialists in hybrid experimental – computational methods applied to soft tissues, to teach a focused and highly original course in this area. The course is addressed to doctoral students and postdoctoral researchers in mechanical and biomedical engineering, materials science, biophysics and applied mathematics, academic and industrial researchers and practicing engineers. Attendees should have an engineering background with reasonable knowledge of mathematics; the necessary biology will be taught from scratch.
In addition to the theoretical background taught at the C1511 CISM school in 2015, it is planned for this new course to have hands-on sessions for a better practice of material parameter identification and inverse problems in soft tissue biomechanics.

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