Undergraduates present on behalf of Insigneo at the British Conference of Undergraduate Research 2018

Undergraduates present on behalf of Insigneo at the British Conference of Undergraduate Research 2018

Two undergraduates, Abhinav Paul Kongari from the Department of Mechanical Engineering and Bioengineering student, Michael Woodward, presented on behalf of Insigneo at the British Conference of Undergraduate Research 2018 (BCUR) on Thursday 12 April 2018 at The University of Sheffield.

Dr Reilly, Insigneo Director of Training said: “Congratulations to Abhinav and Michael. It is exciting to see projects based at Insigneo being presented at this prestigious national conference of Undergraduate Research and highlights the importance of the ‘research-led teaching’ provided by Insigneo academic staff.”

Abhinav and Michael’s presentations were well received, commenting on the event Michael said: “I really enjoyed the experience and I think the conference and the range of research areas shown have been brilliant.”

The British Conference of Undergraduate Research promotes undergraduate research in all disciplines. The Conference meets annually every Spring in a different British university.

Photos:

Abstracts:

Abhinav Paul Kongari
MRI Based Subject-Specific Definition of Muscle Properties to Improve the Accuracy of Musculoskeletal Models of Human Gait

Subject-specific musculoskeletal (MSK) models are built and driven using medical data of individuals in order to run biomechanical simulations of movement. They yield unique estimates of kinematics and kinetics parameters related to human locomotion and can represent a powerful tool that can be used to support clinical decision-making in neuro-musculoskeletal diseases. The development of software to automatically segment 3D geometries of anatomical structures opens a window to improve the accuracy of MSK models. These algorithms allow to extract shape of body tissues and organs, by identifying their boundaries on the medical images. The aim of this research is to apply such a automated segmentation technique to Magnetic Resonance Imaging (MRI) to quantify the volume and geometry of muscle tissue in a repeatable and reliable way. Three subjects (Age: 68y(+/-5y), Height: 160.2cm(+/-3.3cm), Mass: 71.9kg(+/-7.5kg)) were enrolled and semi-automatic segmentation software (Mimics 20.0, Materialise, Belgium) was used to segment muscle tissue from MRI. A manually defined template mask was made according to muscle-fat boundaries which was matched against population based atlases to obtain muscle volumes of 17 upper leg muscles, which were compared against the literature. This procedure was repeated by varying input parameters i.e. sample percentage and atlas filtering threshold in order to assess the sensitivity of the methodology. This will be quantified in terms of mean and standard deviation of muscle volumes. As a next step, maximal isometric forces will be calculated according to Fmax = k*(V/l) where Fmax is maximal isometric force, k is specific tension, V is muscle volume and l is fibre length. These forces will be used to personalise a previously developed MSK model to run a biomechanical analysis of gait, with the aim to obtain a more accurate estimation of joint-contact forces during functional tasks.

Michael Woodward
Patient-Specific Multi-Scale Biomechanical Models for the Prediction of the Risk of Hip Fracture in Osteoporotic Women

It is estimated that over 600,000 women in Europe alone suffer hip fractures each year. In the vast majority of these cases the defining risk factor is osteoporosis, which has a particularly higher incidence in post-menopausal women. Clinical tools exist to assess the risk of fracture such as the Sheffield-developed Fracture Risk Assessment Tool (FRAX). These tools are not without shortcomings however and are often generalised, as quantification of the impact of each factor is difficult to assess for specific patients. Patient-specific musculoskeletal models are at the forefront of future medical technologies and could offer a new, highly specified, assessment of fracture risk. These models are virtual representations of a patient’s musculoskeletal geometry and can be used in combination with gait analysis data for various in silico studies and simulations. The aim of this study is to investigate this application of musculoskeletal modelling and contribute to the development and validation of the models. Using MRI and CT imaging, 3D models can be produced of a patient’s musculoskeletal geometry. Using Inverse Dynamic techniques, muscle and joint forces can be calculated from gait data. These forces and moments form the inputs to finite element modelling, again on the patient’s specific anatomy, providing an in-depth assessment of how these loads are distributed on the bone. The work is conducted through the MultiSim project, funded by the EPSRC (the Engineering and Physical Sciences Research Council). The study is ongoing, with a modelling pipeline currently being tested for six patients which can then be applied to the entire cohort of twenty patients. The results of this analysis will give a unique insight into the forces experienced during everyday motor tasks which could contribute to a hip fracture and create a platform for studies into the effects of osteoporosis on the mechanical response of bone.