Cited by 0Medical Imaging and AnalysisHip disorders and treatmentsMedical Image Segmentation Techniques

A novel semi-automatic hip morphology assessment tool is more accurate than manual radiographic evaluations

Open access
Khayyeri, Hanifeh, Väänänen, Sami P., Flivik, Gunnar, Jurvelin, Jukka S., Dahlberg, Leif, Isaksson, Hanna·2020·Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization

Abstract

Radiological and pathological characteristics of hip osteoarthritis (OA) is joint-space loss due to degradation of articular cartilage. However, patients with early-stage OA do not yet show any radiological signs, which leaves them without diagnosis and treatment. This study evaluates the potential of a novel tool to identify pre-radiographic OA changes based on hip bone morphology. Two statistical appearance models for femur and pelvis were used to estimate the 3Dmorphology of the hip bones based on planar radiographs from patients. Well-known hip geometrical parameters (n = 22) were computed from patient CT scans (truth), 3D reconstructions (new method) and radiographs (calculated manually). The methods were compared by measuring relative error to truth. The new method was significantly more accurate in calculating hip geometrical parameters than the manual 2D calculations. The proposed approach could also capture rotational parameters like cross-over sign and anterior wall sign (100% correct predictions). The method can successfully reconstruct 3D hip shapes and densities for patients that have not yet developed severe osteoarthritis, and provided higher precision than manual estimations. Thus, it may be used to calculate morphological parameters that are predictors of OA and can become a powerful tool in human hip OA research and diagnostics.

Integrity signals

Registry

Crossref · 10.1080/21681163.2019.1578266

Cites

30 of 30 references verified0 citation errors · 0 not checkable

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Research works printed but not linked: 2

  1. Behiels G, 1999, Miccai’99, Proc, 1679, 128
  2. Yoshida K, 2010, Scot Med J, 55, 48

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Authors
Khayyeri, H., Väänänen, S. P., Flivik, G., Jurvelin, J. S., Dahlberg, L., & Isaksson, H.
Affiliations
  • Lund University (SE)
  • University of Eastern Finland (FI)
Corresponding author
Isaksson, Hanna
Venue
Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
Published
2019-02-22
Volume
8
Issue
1
Pages
76-86
ISSN
  • 2168-1163 (ISSN-L)
  • 2168-1171
OpenAlex
W2917309488
Cited by
0
References
30
FWCI
0.00
Type
journal article
Language
en
Open access
Locations
  • Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization (publishedVersion, cc-by-nc-nd)
  • Lund University Publications (Lund University) (submittedVersion)
Funders
  • Crafoordska Stiftelsen (20120752, 20140780)
  • Reumatikerförbundet (R-528331, R-635441, 003/17)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Medical Imaging and Analysis
  • Health Sciences › Medicine › Surgery › Hip disorders and treatments
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
Keywords
hip osteoarthritis, statistical shape models, articular cartilage degeneration, early osteoarthritis diagnosis

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