Date of Award
5-2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Bioengineering
Committee Chair/Advisor
Hai Yao, PhD
Committee Member
Martine LaBerge, PhD
Committee Member
Michael J. Kern, PhD
Committee Member
Melinda Harman, PhD
Committee Member
Tong Ye, PhD
Abstract
Clarifying multifactorial musculoskeletal disorder etiologies supports risk analysis and development of targeted prevention and treatment modalities. Deep learning enables comprehensive risk factor identification through systematic analysis of disease datasets but does not provide sufficient context for mechanistic understanding, limiting clinical applicability for etiological investigations. Conversely, multiscale biomechanical modeling can evaluate mechanistic etiology within the relevant biomechanical and physiological context. We propose a hybrid approach combining 3D explainable deep learning and multiscale biomechanical modeling; we applied this approach to investigate temporomandibular joint (TMJ) disorder etiology by systematically identifying risk factors and elucidating mechanistic relationships between risk factors and TMJ biomechanics and mechanobiology. Our 3D convolutional neural network recognized TMJ disorder patients through subject-specific morphological features in condylar, ramus, and chin. Driven by deep learning model outputs, biomechanical modeling revealed that small mandibular size and flat condylar shape were associated with increased TMJ disorder risk through increased joint force, decreased tissue nutrient availability and cell ATP production, and increased TMJ disc strain energy density. Combining explainable deep learning and multiscale biomechanical modeling addresses the “mechanism unknown” limitation undermining translational confidence in clinical application of deep learning and identified TMJ disorder morphological risk factors never identified with single factor study hypothesis drive approach.
Recommended Citation
Sun, Shuchun, "Identifying Temporomandibular Disorder Morphological Risk Factors via Explainable Deep Learning and Multiscale Biomechanical Modeling" (2024). All Dissertations. 3593.
https://open.clemson.edu/all_dissertations/3593
Author ORCID Identifier
0000-0002-7985-2745
Included in
Artificial Intelligence and Robotics Commons, Biomechanics and Biotransport Commons, Oral and Maxillofacial Surgery Commons