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Updated: Apr 15, 2026

Software-Assisted Quantitative Measurement of Osteoarthritic Subchondral Bone Thickness
Published on: March 18, 2022
Minimum joint space width demonstrates higher inter-and intra-observer reliability than Kellgren-Lawrence grading in
Monty S Khela1, Tiana Lee1, Kellen L Mulford1
1Orthopedic Surgery Artificial Intelligence Laboratory, Department of Orthopedic Surgery, Mayo Clinic, Rochester, Minnesota, USA.
Minimum joint space width (mJSW) measurement on knee radiographs shows higher reliability than Kellgren-Lawrence (KL) grading. Expertise, standardized views, and AI-assisted methods further improve accuracy for both assessments.
Area of Science:
- Radiology
- Orthopedics
- Medical Imaging Analysis
Background:
- Kellgren-Lawrence (KL) grading is a common method for assessing knee osteoarthritis severity.
- Assessing the reliability of radiographic interpretation is crucial for consistent clinical decision-making.
- Minimum joint space width (mJSW) offers a quantitative alternative for evaluating joint space narrowing.
Purpose of the Study:
- To systematically compare the inter- and intra-observer reliability of KL grading versus mJSW measurement on knee radiographs.
- To investigate factors influencing reliability, including rater type, radiographic view, and training.
Main Methods:
- Systematic review of studies reporting reliability for KL or mJSW on knee radiographs.
- Inclusion of data from PubMed/MEDLINE, Embase, Scopus, and Web of Science.
- Analysis of kappa (κ) and intraclass correlation coefficient (ICC) values, considering rater expertise, views, and atlas training.
Main Results:
- Twenty-four studies involving 10,394 radiographs were analyzed.
- mJSW demonstrated generally higher inter-observer reliability (mean ICC = 0.82) than KL grading (mean κ = 0.72).
- Expert raters and AI-assisted systems outperformed trainees; reliability improved with specific views and training.
Conclusions:
- Quantitative mJSW measurement generally exhibits superior reproducibility compared to KL grading for knee radiographs.
- Reliability is enhanced by rater expertise, standardized imaging protocols, structured training, and AI-assisted tools.
- mJSW should complement KL grading, especially with alignment measures, for improved consistency and clinical relevance in radiographic assessments.
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