Literature DB >> 19045517

Development and validation of patient-specific finite element models of the hemipelvis generated from a sparse CT data set.

Vickie B Shim1, Rocco P Pitto, Robert M Streicher, Peter J Hunter, Iain A Anderson.   

Abstract

To produce a patient-specific finite element (FE) model of a bone such as the pelvis, a complete computer tomographic (CT) or magnetic resonance imaging (MRI) geometric data set is desirable. However, most patient data are limited to a specific region of interest such as the acetabulum. We have overcome this problem by providing a hybrid method that is capable of generating accurate FE models from sparse patient data sets. In this paper, we have validated our technique with mechanical experiments. Three cadaveric embalmed pelves were strain gauged and used in mechanical experiments. FE models were generated from the CT scans of the pelves. Material properties for cancellous bone were obtained from the CT scans and assigned to the FE mesh using a spatially varying field embedded inside the mesh while other materials used in the model were obtained from the literature. Although our FE meshes have large elements, the spatially varying field allowed them to have location dependent inhomogeneous material properties. For each pelvis, five different FE meshes with a varying number of patient CT slices (8-12) were generated to determine how many patient CT slices are needed for good accuracy. All five mesh types showed good agreement between the model and experimental strains. Meshes generated with incomplete data sets showed very similar stress distributions to those obtained from the FE mesh generated with complete data sets. Our modeling approach provides an important step in advancing the application of FE models from the research environment to the clinical setting.

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Year:  2008        PMID: 19045517     DOI: 10.1115/1.2960368

Source DB:  PubMed          Journal:  J Biomech Eng        ISSN: 0148-0731            Impact factor:   2.097


  5 in total

Review 1.  Current progress in patient-specific modeling.

Authors:  Maxwell Lewis Neal; Roy Kerckhoffs
Journal:  Brief Bioinform       Date:  2009-12-02       Impact factor: 11.622

2.  Statistical modeling to characterize relationships between knee anatomy and kinematics.

Authors:  Lowell M Smoger; Clare K Fitzpatrick; Chadd W Clary; Adam J Cyr; Lorin P Maletsky; Paul J Rullkoetter; Peter J Laz
Journal:  J Orthop Res       Date:  2015-06-23       Impact factor: 3.494

3.  Analyzing bone remodeling patterns after total hip arthroplasty using quantitative computed tomography and patient-specific 3D computational models.

Authors:  Shanika Arachchi; Rocco P Pitto; Iain A Anderson; Vickie B Shim
Journal:  Quant Imaging Med Surg       Date:  2015-08

4.  Validation of radiocarpal joint contact models based on images from a clinical MRI scanner.

Authors:  Joshua E Johnson; Terence E McIff; Phil Lee; E Bruce Toby; Kenneth J Fischer
Journal:  Comput Methods Biomech Biomed Engin       Date:  2012-05-25       Impact factor: 1.763

5.  Quantitative CT with finite element analysis: towards a predictive tool for bone remodelling around an uncemented tapered stem.

Authors:  Vickie B Shim; Rocco P Pitto; Iain A Anderson
Journal:  Int Orthop       Date:  2012-04-12       Impact factor: 3.075

  5 in total

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