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Exploring inter-subject anatomic variability using a population of patient-specific femurs and a statistical shape and intensity model

Exploring inter-subject anatomic variability using a population of patient-specific femurs and a statistical shape and intensity model
Exploring inter-subject anatomic variability using a population of patient-specific femurs and a statistical shape and intensity model
This paper is motivated by the need to accurately and efficiently measure key periosteal and endosteal parameters of the femur, known to critically influence hip biomechanics following arthroplasty. The proposed approach uses statistical shape and intensity models (SSIMs) to represent the variability across a wide range of patients, in terms of femoral shape and bone density. The approach feasibility is demonstrated by using a training dataset of computer tomography scans from British subjects aged 25-106 years (75 male and 34 female). For each gender, a thousand new virtual femur geometries were generated using a subset of principal components required to capture 95% of the variance in both female and male training datasets. Significant differences were found in basic anatomic parameters between females and males: anteversion, CCD angle, femur and neck lengths, head offsets and radius, cortical thickness, densities in both Gruen and neck zones. The measured anteversion for female subjects was found to be twice as high as that for male subjects: 13 ± 6.4° vs. 6.3 ± 7.8° using the training datasets compared to 12.96 ± 6.68 vs. 5.83 ± 9.2 using the thousand virtual femurs. No significant differences were found in canal flare indexes. The proposed methodology is a valuable tool for automatically generating a large specific population of femurs, targeting specific patients, supporting implant design and femoral reconstructive surgery.
CT-scan, segmentation, finite element mesh, principal component analysis, statistical shape and intensity modelling Femur anatomy, implant design, reconstructive surgery
1350-4533
995-1007
Bah, Mamadou
b5cd0f47-016f-485c-8293-5f6bf8a7ef1a
Shi, Junfen
395fe40b-665e-453f-b917-38538fb5adac
Browne, Martin
6578cc37-7bd6-43b9-ae5c-77ccb7726397
Suchier, Yanneck
862eb630-1f4f-4a9e-a6cf-d940e900e94b
Lefebvre, Fabien
0b1b7c88-54d7-4c65-8d39-0c567f8928f3
Young, Philippe
251d84a2-cb36-4271-8d0a-2d6fcfa58c0f
King, Leonard
7442bd3c-ed4c-46aa-9d9b-1898a113c740
Dunlop, Doug G.
531e164e-1d31-4e37-bed3-08b1587442b7
Heller, Markus O.
3da19d2a-f34d-4ff1-8a34-9b5a7e695829
Bah, Mamadou
b5cd0f47-016f-485c-8293-5f6bf8a7ef1a
Shi, Junfen
395fe40b-665e-453f-b917-38538fb5adac
Browne, Martin
6578cc37-7bd6-43b9-ae5c-77ccb7726397
Suchier, Yanneck
862eb630-1f4f-4a9e-a6cf-d940e900e94b
Lefebvre, Fabien
0b1b7c88-54d7-4c65-8d39-0c567f8928f3
Young, Philippe
251d84a2-cb36-4271-8d0a-2d6fcfa58c0f
King, Leonard
7442bd3c-ed4c-46aa-9d9b-1898a113c740
Dunlop, Doug G.
531e164e-1d31-4e37-bed3-08b1587442b7
Heller, Markus O.
3da19d2a-f34d-4ff1-8a34-9b5a7e695829

Bah, Mamadou, Shi, Junfen, Browne, Martin, Suchier, Yanneck, Lefebvre, Fabien, Young, Philippe, King, Leonard, Dunlop, Doug G. and Heller, Markus O. (2015) Exploring inter-subject anatomic variability using a population of patient-specific femurs and a statistical shape and intensity model. Medical Engineering & Physics, 37 (10), 995-1007. (doi:10.1016/j.medengphy.2015.08.004). (PMID:26363532)

Record type: Article

Abstract

This paper is motivated by the need to accurately and efficiently measure key periosteal and endosteal parameters of the femur, known to critically influence hip biomechanics following arthroplasty. The proposed approach uses statistical shape and intensity models (SSIMs) to represent the variability across a wide range of patients, in terms of femoral shape and bone density. The approach feasibility is demonstrated by using a training dataset of computer tomography scans from British subjects aged 25-106 years (75 male and 34 female). For each gender, a thousand new virtual femur geometries were generated using a subset of principal components required to capture 95% of the variance in both female and male training datasets. Significant differences were found in basic anatomic parameters between females and males: anteversion, CCD angle, femur and neck lengths, head offsets and radius, cortical thickness, densities in both Gruen and neck zones. The measured anteversion for female subjects was found to be twice as high as that for male subjects: 13 ± 6.4° vs. 6.3 ± 7.8° using the training datasets compared to 12.96 ± 6.68 vs. 5.83 ± 9.2 using the thousand virtual femurs. No significant differences were found in canal flare indexes. The proposed methodology is a valuable tool for automatically generating a large specific population of femurs, targeting specific patients, supporting implant design and femoral reconstructive surgery.

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More information

Accepted/In Press date: 3 August 2015
e-pub ahead of print date: 9 September 2015
Keywords: CT-scan, segmentation, finite element mesh, principal component analysis, statistical shape and intensity modelling Femur anatomy, implant design, reconstructive surgery
Organisations: Bioengineering Group, Institute for Life Sciences

Identifiers

Local EPrints ID: 381765
URI: https://eprints.soton.ac.uk/id/eprint/381765
ISSN: 1350-4533
PURE UUID: bfcfe351-a243-40dc-b8e8-a7dcb7e6bc0d
ORCID for Martin Browne: ORCID iD orcid.org/0000-0001-5184-050X
ORCID for Markus O. Heller: ORCID iD orcid.org/0000-0002-7879-1135

Catalogue record

Date deposited: 13 Oct 2015 11:26
Last modified: 06 Jun 2018 13:03

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