Date of Award
Daniel Felix Ritchie School of Engineering and Computer Science, Computer Science
Peter Laz, Ph.D.
Humerus, Modeling, Principle component analysis, Shape, Statistical shape modeling, Statistical
The fit of the humeral prosthesis to the intramedullary canal and the replication of the anatomic humeral head center are important factors in Total Shoulder Arthroplasty (TSA). The objective of this thesis was to develop a Statistical Shape Model (SSM) of the cortical and cancellous bone regions of the proximal humerus, and to assess potential shape differences with gender and ethnicity, with a goal of informing implant design. An SSM was used and Principal Component Analysis (PCA) was applied to data that represented both the cancellous and cortical humeral bone of 63 healthy subjects and cadavers. Anatomical measurements and PC scores were analyzed by gender and ethnicity. Scaling accounted for 75% of the variation in the training set. Differences between males and females were primarily in size. Ethnicity differences were observed in the relationship between medial and posterior offset. Differences in ethnicity and/or gender were observed in the relationship between posterior offset and the head inclination angle. These are differences that should be considered when designing implants for a global population or subpopulation.
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Paul B. Sade Sr.
Received from ProQuest
Sade, Paul B. Sr., "Statistical Shape Modeling to Quantify Variation in the Proximal Humeral Anatomy" (2017). Electronic Theses and Dissertations. 1289.
Biomedical Engineering, Mechanical Engineering, Engineering