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Updated: Jun 19, 2026

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In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
Published on: July 2, 2021
A comparative study between corresponding structural geometric variables using 2 commonly implemented hip structural
Benjamin C C Khoo1, Scott G Wilson, Graeme K Worth
1Department of Medical Technology and Physics, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia.
Summary
Hip structural analysis (HSA) shows differences between research (r-HSA) and clinical (c-HSA) versions. Linear transformations are provided to reconcile these bone geometry measurement variations.
Area of Science:
- Orthopedics and Bone Health
- Medical Imaging Analysis
- Biomechanical Engineering
Background:
- Hip structural analysis (HSA) has been utilized for two decades in research to link bone geometry with fragility.
- Hologic Inc. introduced a modified version, clinical HSA (c-HSA), in 2007 for their DXA scanners, transitioning HSA into clinical practice.
Purpose of the Study:
- To compare the outcomes of research-HSA (r-HSA) and clinical-HSA (c-HSA) implementations.
- To assess the agreement and identify discrepancies in bone structural geometric measurements between the two HSA versions.
Main Methods:
- Dual-energy X-ray absorptiometry (DXA) scans from 191 females were analyzed using both r-HSA and c-HSA.
- Bland-Altman plots were employed to evaluate the agreement between measurements from the narrow-neck (NN) region of the hip.
Main Results:
- Significant differences (p < 0.001) were observed in NN areal bone mineral density, cross-sectional area, moment of inertia, and section modulus between r-HSA and c-HSA.
- r-HSA generally yielded higher values for these parameters compared to c-HSA, except for NN subperiosteal width.
- High linear correlations (r(2) > 0.81) were found for most NN structural geometric outcomes, though neck shaft angle showed weaker correlation (r(2) > 0.47).
Conclusions:
- While significant differences exist between r-HSA and c-HSA bone geometry measurements, strong correlations suggest comparability.
- The study provides essential linear transformation parameters to convert r-HSA data to c-HSA equivalents, facilitating data integration and clinical application.
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