Award details

A new framework for computational biomechanical models and 3Rs in musculoskeletal research.

ReferenceBB/R016380/1
Principal Investigator / Supervisor Professor Michael Fagan
Co-Investigators /
Co-Supervisors
Dr Peter Watson
Institution University of Hull
DepartmentMechanical Engineering
Funding typeResearch
Value (£) 347,835
StatusCurrent
TypeResearch Grant
Start date 01/01/2019
End date 31/05/2023
Duration53 months

Abstract

This project has two primary goals: (1) to quantify the experimental input data required for musculoskeletal computer models to deliver accurate biomechanical predictions, and (2) provide quantitative data on the current and future potential of computer simulation approaches as an alternative to animal experimentation in basic science, clinical/veterinary and industrial projects involving biomechanics. To achieve this we will use mastication in rabbits as our model system because it is experimentally tractable and will generate data relevant to basic biological science fields and the health and welfare of rabbits. We will collect a wealth of anatomical, in vivo and in vitro experimental data on the rabbit masticatory system. Biplanar x-ray videography will be synchronized with strain gauges, muscle EMG and sonomicrometry and a bite force transducer to simultaneously record 3D motions, muscle dynamics, bone strains and bite forces during feeding. In vitro physiology experiments will quantify muscle mechanics and key contractile properties. Key anatomical variables from the same rabbits will be quantified using dissection, medical imaging and nanoindentation. Initially this data will be used to test hypotheses relating functional adaptations to processing different food types and to understand how tissue level properties translate to overall skull function. But most importantly this data will allow us to build, drive and validate the most comprehensive musculoskeletal computer models produced to-date. Our initial models will thus provide a best-case scenario for simulation accuracy. We will then incrementally reduce or average-out the resolution of input data given to the model and observe the effects on accuracy. This will tell us how individual input parameters affect accuracy and help the musculoskeletal research community identify which parameters do not need to be measured through experimentation in real animals to achieve specific thresholds of accuracy.

Summary

This project has two overarching goals: (1) to investigate the type and amount of experimental input data required for musculoskeletal computer models to deliver accurate predictions, and (2) in doing so provide quantitative data on the current and future potential of models to contribute to the reduction, replacement and refinement (3Rs) of animal experiments in scientific research. To do this we will develop and validate new computational biomechanical models using mastication in rabbits as our case study. Validating computer models requires a large amount of experimental data about rabbit anatomy and feeding mechanics (e.g. muscle and bite forces). This data does not exist for rabbits, or indeed any other experimental animal. Therefore a systematic anatomical and biomechanical investigation of rabbit feeding is required in which all the primary determinants of feeding mechanics are measured from a cohort of rabbits. Computational models constructed from medical imaging data of those same rabbits can then be directly and immediately used to improve and validate computer simulations. Only in this way can models be truly validated and their potential for achieving 3Rs in future studies be demonstrated. Our specific objectives are therefore to collect: anatomical and image data on bone and muscle morphology in rabbits; in vivo data on bone motion and muscle physiology as they eat various food types; and combine these data to build and validate new computer models of rabbit feeding biomechanics. Rabbits have been chosen because they are widely used in a variety of research areas. They are the first-choice experimental animal for dental implant design and bone (re)growth studies because of their size, easy handling and relative similarities to humans in terms of bone composition, healing and anatomy. These experiments, like many in musculoskeletal research, are highly invasive, causing pain and distress to the animals before they are euthanized. A digital model hasthe potential to completely replace (or maximally reduce) the use of animals in musculoskeletal research and/or medical device design. The anatomy and behaviour of a digital model can be altered and re-tested without limitation and without any harm or distress to a real animal. This can also allow, for example: a model analysis to be extended to a different strain/breed of the same species (or a similar species) by digital modification of the anatomy/behaviour; elements of anatomy to be modified in multiple ways (e.g. removal of teeth/bone) to examine the consequences of different surgical approaches; and for implant devices to be digitally inserted into the models, and their impact on performance examined, all without the need for any harmful experimentation on real animals. But improving biomechanical models will not only reduce animal use in research, but has the potential to improve modelling of human biomechanics. Currently models are used widely to study healthy biomechanics (e.g. sports performance), ageing (e.g. sacropenia) and related diseases (e.g. knee osteoarithitis), dental procedures (e.g. orthodontic treatment) and injury (e.g. hip fracture). In these human studies they are used to estimate or predict parameters that cannot be measured directly in people, thus their accuracy is inherently difficult to assess. Thus there is clear need for the type of study we propose here. In the first instance we will generate the most comprehensive biomechanical models produced to-date using our exhaustive and state-of-the-art experimental dataset. This will provide a best-case scenario for model accuracy. We will then incrementally reduce the resolution of input data given to the model and observe the effects on accuracy. This will tell us how individual input parameters effect accuracy and help the musculoskeletal research community identify which parameters do not need to be measured through experimentation in real animals to achieve the necessary accuracy.

Impact Summary

The main impacts of this research programme are on animal welfare, the general public, and the researchers employed on the grant, together with benefits to the academic community (see Academic Beneficiaries). APPLIED LINKS WITH THE POTENTIAL TO DELIVER ANIMAL WELFARE BENEFITS THROUGH THE 3Rs Publication and dissemination of computational models will benefit a very wide range of researchers, potentially leading to significant societal impact in terms of improved animal welfare. Through the development of the most robust, validated computer models ever constructed we will facilitate a step change in our understanding of model accuracy and usefulness, and in doing so provide a marker for future musculoskeletal research. Our models will demonstrate how precise (or how species-specific) input parameters have to be to achieve different thresholds of accuracy in terms of predicting an enormous range of muscle and bone parameters. This will directly guide other researchers utilising musculoskeletal models in a variety of contexts, ranging from basic biologists (e.g. functional anatomists, palaeontologists), to applied researchers (clinicians/veterinarians) interested in understanding healthy and "abnormal" biomechanics, through to bioengineers and roboticists developing medical devices and bioinspired robots. As a direct consequence of this we believe that our models will demonstrate that computer simulation approaches can contribute significantly to achieving the 3Rs in musculoskeletal research, and in surgical and implant design studies that require biomechanical analyses. Experimental studies of this type are highly invasive and typically cause significant pain and distress to the animals before they are euthanized. The approach we will take herein will mean that the potential for future benefits from 3Rs in this context will be broad. By demonstrating how individual anatomical and physiological parameters (e.g. muscle size, contraction behaviour) impact on model accuracy our data will indicate which variables need to be measured directly from cohorts or species of animal in the future and which do not, given the threshold of accuracy for specific model parameters required. In the future, the application of such models will allow some animal experiments to be replaced and in other cases refined and/or reduced as model simulations will allow research efforts involving animal research to be better designed. THE GENERAL PUBLIC Animal anatomy and functional morphology are topics that interest the general public, as testified by the continued success of natural history documentaries and recent documentaries like "Inside Nature's Giants." Medical imaging and computational models are powerful and flexible mediums through which to communicate our understanding of the links between anatomy, mechanics and ecology to the general public. Our work will have a positive impact in this respect and demonstrating technological advances and a wide variety of applications of biological research and will have an impact on the general public as a whole, but in particular school children. OTHER SPECIFIC IMPACTS The careers of the PDRAs will be developed considerably by involvement in a multi-disciplinary project that integrates physiology, biomechanics and modelling approaches. They will benefit from working closely with laboratories in different leading institutions. The research will also impact on the training of undergraduates carrying out research projects and postgraduates completing MSc/PhD's within our labs.
Committee Research Committee A (Animal disease, health and welfare)
Research TopicsAnimal Welfare, Systems Biology, The 3 Rs (Replacement, Reduction and Refinement of animals in research)
Research PriorityX – Research Priority information not available
Research Initiative X - not in an Initiative
Funding SchemeX – not Funded via a specific Funding Scheme
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