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. 2023 Dec;14(4):413-423.
doi: 10.1177/19476035231166126. Epub 2023 Jun 2.

Automated Radiographic Measurements of Knee Osteoarthritis

H Rayegan  1   2 , H C Nguyen  3   4 , H Weinans  3   5 , W P Gielis  3 , S Y Ahmadi Brooghani  2 , R J H Custers  3 , N van Egmond  3 , C Lindner  6 , V Arbabi  1   2   3
Affiliations

Automated Radiographic Measurements of Knee Osteoarthritis

H Rayegan et al. Cartilage. 2023 Dec.

Abstract

Objective: Herewith, we report the development of Orthopedic Digital Image Analysis (ODIA) software that is developed to obtain quantitative measurements of knee osteoarthritis (OA) radiographs automatically. Manual segmentation and measurement of OA parameters currently hamper large-cohort analyses, and therefore, automated and reproducible methods are a valuable addition in OA research. This study aims to test the automated ODIA measurements and compare them with available manual Knee Imaging Digital Analysis (KIDA) measurements as comparison.

Design: This study included data from the CHECK (Cohort Hip and Cohort Knee) initiative, a prospective multicentre cohort study in the Netherlands with 1,002 participants. Knee radiographs obtained at baseline of the CHECK cohort were included and mean medial/lateral joint space width (JSW), minimal JSW, joint line convergence angle (JLCA), eminence heights, and subchondral bone intensities were compared between ODIA and KIDA.

Results: Of the potential 2,004 radiographs, 1,743 were included for analyses. Poor intraclass correlation coefficients (ICCs) were reported for the JLCA (0.422) and minimal JSW (0.299). The mean medial and lateral JSW, eminence height, and subchondral bone intensities reported a moderate to good ICC (0.7 or higher). Discrepancies in JLCA and minimal JSW between the 2 methods were mostly a problem in the lateral tibia plateau.

Conclusions: The current ODIA tool provides important measurements of OA parameters in an automated manner from standard radiographs of the knee. Given the automated and computerized methodology that has very high reproducibility, ODIA is suitable for large epidemiological cohorts with various follow-up time points to investigate structural progression, such as CHECK or the Osteoarthritis Initiative (OAI).

Keywords: automation; knee; measurements; osteoarthritis; radiological imaging.

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Conflict of interest statement

Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Measured parameters on knee radiographs, from left to right: Joint space width (JSW), joint line convergence angle (JLCA), eminence heights, and subchondral bone intensities.
Figure 2.
Figure 2.
The 99-points model automatically placed on knee radiograph using BoneFinder®., The points on the lateral tibia plateau were placed on the anticipated anterior edge.
Figure 3.
Figure 3.
The measurements as performed by the Orthopedic Digital Image Analysis (ODIA). (A) The framework placed by ODIA. (B) The perpendiculars on the joint lines and the circles for subchondral bone density measurements. The circles were placed directly under the anticipated anterior edge of the tibia plateau. Joint space width (JSW) is measured as the circle diameters displayed in (C). The smallest circle diameter is the minimal JSW. Again, the anticipated anterior edge of the tibia plateau was used at the lateral side. Eminence heights are measured as can be seen in (D).
Figure 4.
Figure 4.
User interface of ODIA software, which performs fully automated measurements of the parameters joint space width (JSW), eminence height, subchondral bone intensity, and joint line convergence angle (JLCA). ODIA = Orthopedic Digital Image Analysis.
Figure 5.
Figure 5.
Overview of the 3 measurement methods used in this study. The manual KIDA method, the ODIA semi-auto method with manual checks of the segmentations and automated measurements, and twice the ODIA full auto method with automated segmentations and automated measurements. KIDA = Knee Imaging Digital Analysis; ODIA = Orthopedic Digital Image Analysis.
Figure 6.
Figure 6.
Bland-Altman plots of the measurements performed with ODIA and KIDA, with the means on the horizontal axis and the differences between the 2 measurement methods on the vertical axis. The red lines indicate the 95% limits of agreement, the green line indicates the mean difference. ODIA = Orthopedic Digital Image Analysis; KIDA = Knee Imaging Digital Analysis; JSW = joint space width; JLCA = joint line convergence angle.
Figure 7.
Figure 7.
Skewed view of the tibial plateau on a knee radiograph obtained using the Buckland-Wright protocol. There are visible posterior and anterior lateral tibial borders, which are hard to distinguish. Selecting different borders affects the tibial joint line significantly.
See this image and copyright information in PMC

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