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Automated radiographic hip morphology measurements: An open-access method.

F Boel1,2, S de Vos-Jakobs3, N S Riedstra1

  • 1Erasmus MC, Department of Orthopaedics and Sports Medicine, University Medical Center Rotterdam, Dr. Molewaterplein 40, 3015GD Rotterdam, the Netherlands.

Osteoarthritis Imaging
|September 6, 2024
PubMed
Summary
This summary is machine-generated.

A new automated method accurately measures hip morphology on DXA scans, offering reliable results comparable to or better than manual assessments for large studies.

Keywords:
DXAHipMorphologyRadiographyRadiology

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Area of Science:

  • Radiology
  • Orthopedics
  • Medical Imaging

Background:

  • Accurate radiographic measurements of hip morphology are crucial for diagnosing and managing hip conditions.
  • Dual-energy X-ray absorptiometry (DXA) images offer a potential source for these measurements, but manual analysis can be time-consuming and subjective.

Purpose of the Study:

  • To introduce a novel automated method for quantifying hip morphology from DXA images.
  • To evaluate the performance and reliability of this automated method against traditional manual assessments.

Main Methods:

  • An automated algorithm was developed to outline hip shape and calculate key morphological parameters (ADR, AI, AA, WCEA, EI, NSA, TI) on DXA scans.
  • Manual measurements were performed by two orthopedic surgeons on the same dataset (n=30).
  • Agreement and reliability were assessed using Bland-Altman plots and intraclass correlation coefficients (ICC).

Main Results:

  • The automated method successfully computed all targeted radiographic hip morphology measurements.
  • Intermethod reliability between automated and manual measurements ranged from 0.57 to 0.96.
  • The automated method's reliability was comparable to or exceeded manual interobserver reliability, with the exception of the acetabular index (AI).

Conclusions:

  • The developed open-access automated method provides a fast and reproducible means to measure hip morphology on DXA images.
  • This tool shows significant promise for applications in large population studies and routine clinical practice for radiographic hip morphology assessment.