Multiscale Modelling is made up of 5 of the Work Packages, including, WP1. Environment Modelling, WP2. Body Model, WP3. Organ Model, WP4. Tissue Modelling and WP5. Cell Model.Work Package 1. Environment Modelling
WP Leader: Professor Aleksandar Pavic
Main title: Medical Grade Outdoor Measurement of Human Body Dynamics.
Advancements in sensory technologies and evolution of ‘Big data’ handling techniques and infrastructure have created a unique opportunity for the healthcare sector to realise the notion of real-life data-driven diagnosis, prognosis and health monitoring to the fullest. Rapid adoption of ‘informed’ life-style by masses in recent years has proven the strong public desire for a paradigm shift in health care services towards more personal and ‘point-of-care’ forms.
- Estimation of spectrum of environmental boundary conditions for different activities of daily living (ADL)
- Musculoskeletal/neuromotor health monitoring
- Fall prediction and monitoring
- Seamless integration of wearable robots by developing ‘rich’ data-driven control technics
Work Package 2. Body Model
WP Leader: Dr Claudia Mazzà
The protocols for the gait analysis and MRI data have been defined in order to allow a full representation of gait that includes the details of the foot and ankle joints. The problem of developing a multisegment foot has also been dealt with. This model requires the ground reaction force (GRF) to be subdivided between the modelled foot segments. A sensitivity analysis to the number of segments to be included has been performed and an available retrospective dataset combining plantar pressure data and ground reaction forces is being analised to investigate the feasibility of using foot kinematics and morphology to predict the vertical loading that occurs in each of three foot segments during experimental walking trials.
WP2 is interacting with WP1 and WP6 for what concerns the possibility of estimating the ground reaction forces and the centre of pressure trajectory from wearable sensors. The interaction with WP6 will also concern the definition of a method that provides quantitative comparison between inverse-dynamic predicted activations and EMG measurements. The interaction with WP3 will be based on providing them with the estimate of a spectrum of possible boundary conditions. Last but not least, WP2 ahs substantially contributed to the definition of the clinical protocol to be used in the WP8 clinical study and will provide support in the data collection at whole body level.
Work Package 3. Organ Model
WP Leader: Professor Marco Viceconti
“Today we can to predict the strength of each bone of a given patient by simply taking a CT scan of the bone of interest”.
The Organ Model WP aims to develop modelling methods to predict changes in the musculoskeletal system at the organ scale. This typically involves the modelling of whole bones, but also of whole muscles, ligaments, etc. We mostly use finite element analysis as primary numerical method.
We started analysing the current methods for whole bone modelling. We used a retrospective cohort of 100 osteoporosis patients, half with a femoral neck fracture, provided by Prof Eastell. We found that changes in the quality of the FE mesh and of the anatomical reference system (used to define the musculo-articular forces acting on the femur), significantly improve the ability of the minimal physiological strength to discriminate fractured and non fractured patients.
As one of the main sources of error was found to be the CT scan, that was limited to the proximal femur, we developed a new CT scan plan that cover the entire femur, but present an effective radiation dose smaller than the current clinical protocol.
We are also working on modelling paediatric fractures in the long bones (femurs and tibia), and on the and on the modelling of skeletal muscles.
We will soon start to receive skeletal forces to be applied to our models from WP2, as these are predicted by the whole body models. From WP4 we would expect predictions of the evolution of the apparent density over time due to the progression of the disease (osteoporosis, metastasis, ostemalachia), or as an effect of the intervention.
Work Package 4. Tissue Modelling
WP Leader: Professor Damien Lacroix
The objective of this WP is to develop mechanoregulation models able to predict the tissue formation and resorption as a function of the mechanical loading. In particular bone topological discretization and bone remodelling algorithms used in combination with mechanoregulation models will be developed. Also a new constitutive model of muscles will be developed. These models will be integrated into the Organ Modelling WP3 and will make use of the outputs provided by the Cell Modelling WP5.
Volumetric Topological Analysis (VTA) is considered as a powerful complex geometry analysis scheme which provides important information about trabecular network architects and its contribution to whole musculoskeletal mechanical response. Two methodologies were applied in this study. In the first phase, an algorithm was developed in MATLAB to perform medial surface thinning on a trabecular microstructure. In the second phase, a separate MATLAB program was generated to perform digital topological analysis which aims to organise thinned trabecular bone network into separated plate and rod members. Therefore, by applying our VTA package on any trabecular microstructure, it is then possible to extract detailed information on structural topology, network formation and local anisotropy. This technique can also be used to obtain more knowledge on the effect of diseases, such as osteoporosis, over the bone microarchitecture.
The topological architecture developed in this WP will provide inputs in terms of anisotropic and stiffness properties of bone at the organ level (WP5).
Work Package 5. Cell Model
WP Leader: Professor Tim Skerry
The objective of this WP is to gain knowledge on the mechanoresponse of cells when subjected to mechanical loading and to integrate single cell level and population-based level experimental and numerical information into the tissue scale WP. In particular a dynamic single cell computational model simulating the cytoskeleton adaptation of cell to mechanical loading will be developed. Cell-cell interactions will then be studied by combining agent-based modeling technique with the single cell finite element model. This will provide a new approach to model cells individually or in a population. The output of this approach will enable to study in vitro processes that will inform on the tissue extracellular matrix formation.
The types of mechanical loading will be derived from the outputs provided in WP4. In addition some modelling at the single cell level and population-based level will be performed in order to integrate it with the tissue WP4.
On the other side the mechanotransduction of osteocyte cells will be studied experimentally by taking RNA sequence of cells in the skull and long bones to evaluate the effect of in vivo mechanical loading onto gene expression patterns. The outcome of these experimental mechanical stimulations on osteocytes transcriptomic response will likely contribute to the identification of mediators involved in the adaptive response of bone. Cell memory and site-specific response will also be studied by investigating the effect of mechanical loading in vitro on osteocyte cells extracted from the tibia and skull of different animals.