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Computational and Mathematical Modeling of Medical Images: Advanced Methods and Applications in Translational Myology and Surgical Planning

PhD Thesis defence - Kyle Edmunds

  • 7.6.2017, 11:00 - 13:00

Computational and Mathematical Modeling of Medical Images: Advanced Methods and Applications in Translational Myology and Surgical Planning

Kyle Edmunds  7 June 2017, 11.00 am, room V102

Sigurður I. Erlingsson, head of the SSE research council
Thesis Committee:

Paolo Gargiulo, Supervisor and Associate Professor Reykjavík University, Reykjavík, Iceland
Þórður Helgason, Associate Professor Reykjavík University, Reykjavík, Iceland
Hannes Petersen, Head of the Dept. of Anatomy and Professor University of Iceland, Reykjavík, Iceland
Sigurður Brynjólfsson, Professor University of Iceland, Reykjavík, Iceland
Thesis Examiner:

Antonio Fratini, Lecturer and Biomedical Engineering Program Coordinator Aston University, Birmingham, United Kingdom


The growing field of translational myology continually seeks to define and promote the generalizability of muscle research to clinical practice via optimizing the transition of a wide variety of investigative muscle assessment modalities. There are distinct challenges in all facets of this research, but understanding the physiological importance of mobility currently presents a strategic priority. The severe physiological consequences from the loss of mobility are experienced by all of us: whether induced by normative ambulatory challenges as we age or as sequela of lower extremity pathology. Indeed, a growing wealth of literature clearly implicates mobility loss with a plethora of comorbidities, leading to an increasingly deleterious quality of life and ultimately resulting in early mortality. The loss of mobility is concomitantly evidenced by the progressive of skeletal muscle size and quality – phenomena which altogether define muscle degeneration. Nonetheless, complete etiological definitions and methodological comparisons for the precise, non-invasive quantification of muscle degeneration remains disparately described in literature.

This thesis focuses on the development, application, and assessment of novel methods in computational and mathematical modeling of medical images to quantify muscle degeneration and optimize our understanding of two mobility-restorative procedures: Functional Electrical Stimulation and Total Hip Arthroplasty. Additional impacts of these methods are further explored in defining multimodal metrics for mobility analysis, characterizing the utility of 3D printing for surgical planning, modeling craniofacial electromyography, and computing pre-surgical periprosthetic fracture risk. Results from these investigations altogether present the efficacies and limitations of available image processing modalities, and introduce novel methodologies, such as nonlinear trimodal regression analysis of radiodensitometric distributions and computational interference fitting for periprosthetic femoral fracture analysis. Such analyses and perspectives are herein presented in both a theoretical and practical context. Standardizing computational modeling methodologies for medical image assessment in these contexts would allow for the generalizability of such research to the indication of respective compensatory targets for clinical intervention. 

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