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    Modeling the Variability of Glenoid Geometry in Intact and Osteoarthritic Shoulders

    Source: Journal of Mechanical Design:;2017:;volume( 139 ):;issue: 011::page 111410
    Author:
    de Vries
    ,
    Charlotte M.;Parkinson
    ,
    Matthew B.
    DOI: 10.1115/1.4037408
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: 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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      Modeling the Variability of Glenoid Geometry in Intact and Osteoarthritic Shoulders

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    contributor authorde Vries
    contributor authorCharlotte M.;Parkinson
    contributor authorMatthew B.
    date accessioned2017-12-30T11:43:18Z
    date available2017-12-30T11:43:18Z
    date copyright10/2/2017 12:00:00 AM
    date issued2017
    identifier issn1050-0472
    identifier othermd_139_11_111410.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4242768
    description abstractThe 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.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleModeling the Variability of Glenoid Geometry in Intact and Osteoarthritic Shoulders
    typeJournal Paper
    journal volume139
    journal issue11
    journal titleJournal of Mechanical Design
    identifier doi10.1115/1.4037408
    journal fristpage111410
    journal lastpage111410-8
    treeJournal of Mechanical Design:;2017:;volume( 139 ):;issue: 011
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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