TY - JOUR
T1 - Modeling the Variability of Glenoid Geometry in Intact and Osteoarthritic Shoulders
AU - Vries, Charlotte M.De
AU - Parkinson, Matthew B.
N1 - Funding Information:
• National Science Foundation (Award No. 0729386).
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/11/1
Y1 - 2017/11/1
N2 - The objective of this research is to model the geometric variability of the glenoid of the scapula. The glenoid is the "socket" component of the "ball and socket" connection of the shoulder joint. The model must capture the observed variability with sufficient resolution such that it informs both operative and design decisions. Creating the model required the application of existing mathematical and statistical modeling approaches, including geometric fitting, radial basis functions (RBFs), and principal component analysis (PCA). The landmark identification process represented the glenoid in a new manner. This work was validated against existing approaches and computed tomography (CT) scans from 42 patients. Information on the range of shoulder geometries can assist with preoperative planning as well as implant design for total shoulder arthroplasty (TSA). PCA was used to quantify the variability of shape across landmarks used to represent the glenoid shape. These landmark locations could be used to generate full surface meshes of existing glenoids or new glenoid models synthesized by changing principal components (PC). The process of creation of these shoulder geometries may be useful for the study of other joints. The models created will help surgeons and engineers to understand the effects of osteoarthritis on bone geometry, as well as the range of variability present in healthy shoulders.
AB - The objective of this research is to model the geometric variability of the glenoid of the scapula. The glenoid is the "socket" component of the "ball and socket" connection of the shoulder joint. The model must capture the observed variability with sufficient resolution such that it informs both operative and design decisions. Creating the model required the application of existing mathematical and statistical modeling approaches, including geometric fitting, radial basis functions (RBFs), and principal component analysis (PCA). The landmark identification process represented the glenoid in a new manner. This work was validated against existing approaches and computed tomography (CT) scans from 42 patients. Information on the range of shoulder geometries can assist with preoperative planning as well as implant design for total shoulder arthroplasty (TSA). PCA was used to quantify the variability of shape across landmarks used to represent the glenoid shape. These landmark locations could be used to generate full surface meshes of existing glenoids or new glenoid models synthesized by changing principal components (PC). The process of creation of these shoulder geometries may be useful for the study of other joints. The models created will help surgeons and engineers to understand the effects of osteoarthritis on bone geometry, as well as the range of variability present in healthy shoulders.
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U2 - 10.1115/1.4037408
DO - 10.1115/1.4037408
M3 - Article
AN - SCOPUS:85030450627
VL - 139
JO - Journal of Mechanical Design - Transactions of the ASME
JF - Journal of Mechanical Design - Transactions of the ASME
SN - 1050-0472
IS - 11
M1 - 111410
ER -