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Research Papers: Variability/Uncertainty in D3

Modeling the Variability of Glenoid Geometry in Intact and Osteoarthritic Shoulders

[+] Author and Article Information
Charlotte M. de Vries

Department of Mechanical Engineering,
The Pennsylvania State University Erie,
Erie, PA 16510
e-mail: devries@psu.edu

Matthew B. Parkinson

Engineering Design Program,
Department of Mechanical Engineering,
The Pennsylvania State University,
University Park, PA 16802
e-mail: parkinson@psu.edu

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received January 27, 2017; final manuscript received July 19, 2017; published online October 2, 2017. Assoc. Editor: Charlie C. L. Wang.

J. Mech. Des 139(11), 111410 (Oct 02, 2017) (8 pages) Paper No: MD-17-1066; doi: 10.1115/1.4037408 History: Received January 27, 2017; Revised July 19, 2017

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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Figures

Grahic Jump Location
Fig. 1

The lateral and dorsal views of a healthy left scapula labeled with the parts described in this report. A directional compass is listed at the bottom right of each view. This image was created in osirix using the CT scan of a patient.

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Fig. 2

The osirix 3D volume rendering of a CT scan of a patient, with the bone CT scan presets. The scapula is not isolated, but is seen with the humerus, clavicle, and rib cage. The humerus and scapula are labeled, along with the glenoid and humeral head at the joint.

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Fig. 3

Overview of the method used to create the glenoid models and validate them. This paper discusses the four tasks completed using the processed CT scans: quantify geometry, meshless representation, quantify variability, and synthesize new glenoids. A description of each task can be found in Sec. 3.

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Fig. 4

To determine the orientation of the glenoid relative to the scapula, a sphere is fit to the concave face of the glenoid

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Fig. 5

The process to validate the each glenoid used to represent base glenoid mesh

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Fig. 6

The glenoid and vault created using the mean version of the data. All other shoulders are used by adding linear combinations of the PCs.

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Fig. 7

The curvature, version, and inclination of the synthesized shoulders created by varying PC 1 and PC 2: (a) curvature, (b) version, and (c) inclination

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Fig. 8

A visualization of the transformed glenoids created by varying PC 1 and PC 2. The darker shading represents the PC score density of the intact population. The lighter shading in the bottom right corner represents the PC score density of osteoarthritic shoulders.

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