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Related Experiment Video

Updated: Jul 28, 2025

Software-Assisted Quantitative Measurement of Osteoarthritic Subchondral Bone Thickness
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Automated Radiographic Measurements of Knee Osteoarthritis.

H Rayegan1,2, H C Nguyen3,4, H Weinans3,5

  • 1Orthopaedic-BioMechanics Research Group, University of Birjand, Birjand, Iran.

Cartilage
|June 2, 2023
PubMed
Summary

A new Orthopedic Digital Image Analysis (ODIA) software automatically measures knee osteoarthritis (OA) on radiographs. While some measurements showed variability, ODIA offers a reproducible method for large-scale OA research.

Keywords:
automationkneemeasurementsosteoarthritisradiological imaging

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Area of Science:

  • Orthopedics
  • Radiology
  • Medical Imaging Analysis

Background:

  • Manual measurement of knee osteoarthritis (OA) parameters from radiographs is time-consuming and can hinder large-cohort studies.
  • Automated and reproducible methods are crucial for advancing OA research and understanding disease progression.

Purpose of the Study:

  • To develop and evaluate the Orthopedic Digital Image Analysis (ODIA) software for automated quantitative measurements of knee OA parameters.
  • To compare the automated ODIA measurements with existing manual Knee Imaging Digital Analysis (KIDA) measurements.

Main Methods:

  • Utilized data from the prospective multicentre CHECK cohort study, including 1,743 knee radiographs.
  • Compared automated ODIA measurements (medial/lateral joint space width, minimal JSW, JLCA, eminence heights, subchondral bone intensities) against manual KIDA measurements.

Main Results:

  • Intraclass correlation coefficients (ICCs) for Joint Line Convergence Angle (JLCA) and minimal Joint Space Width (JSW) were poor (0.422 and 0.299, respectively).
  • Moderate to good ICCs (≥0.7) were observed for mean medial/lateral JSW, eminence height, and subchondral bone intensities.
  • Discrepancies between ODIA and KIDA were primarily noted in the lateral tibia plateau for JLCA and minimal JSW.

Conclusions:

  • The ODIA software provides automated and reproducible quantitative measurements of knee OA parameters from standard radiographs.
  • ODIA's high reproducibility makes it suitable for large epidemiological cohorts like CHECK and OAI for investigating structural OA progression.