Cartilage Topography Assessment With Local-Area Cartilage Segmentation for Knee Magnetic Resonance Imaging

Abstract

Objective: Local-area cartilage segmentation (LACS) software was developed to segment medial femur (MF) cartilage on magnetic resonance imaging (MRI). Our objectives were 1) to extend LACS to the lateral femur (LF), medial tibia (MT), and lateral tibia (LT), 2) to compare LACS to an established manual segmentation method, and 3) to visualize cartilage responsiveness over each cartilage plate.

Methods: Osteoarthritis Initiative participants with symptomatic knee osteoarthritis (OA) were selected, including knees selected at random (n = 40) and knees identified with loss of cartilage based on manual segmentation (Chondrometrics GmbH), an enriched sample of 126 knees. LACS was used to segment cartilage in the MF, LF, MT, and LT on sagittal 3D double-echo steady-state MRI scans at baseline and at 2-year follow-up. We compared LACS and Chondrometrics average thickness measures by estimating the correlation in each cartilage plate and estimating the standardized response mean (SRM) for 2-year cartilage change. We illustrated cartilage loss topographically with SRM heatmaps.

Results: The estimated correlation between LACS and Chondrometrics measures was r = 0.91 (95% confidence interval [95% CI] 0.86, 0.94) for LF, r = 0.93 (95% CI 0.89, 0.95) for MF, r = 0.97 (95% CI 0.96, 0.98) for LT, and r = 0.87 (95% CI 0.81, 0.91) for MT. Estimated SRMs for LACS and Chondrometrics measures were similar in the random sample, and SRM heatmaps identified subregions of LACS-measured cartilage loss.

Conclusion: LACS cartilage thickness measurement in the MF and LF and tibia correlated well with established manual segmentation-based measurement, with similar responsiveness to change, among knees with symptomatic knee OA. LACS measurement of cartilage plate topography enables spatiotemporal analysis of cartilage loss in future knee OA studies.

Figure 1

Reader-involved steps of bone and cartilage segmentation using the Local Area Cartilage Segmentation (LACS) software. (a) A reader indicates the medial, lateral, and central margin of the bone, and the bone texture. Based on these variables, the software creates the bone margin. (b) The reader then indicates anatomical landmarks on the femur (in three slides, creating a cylindrical coordinate system) and the tibia (in two slides, creating a warped 2D Cartesian coordinate system). (c) Automated edge detection algorithms outline the cartilage in consistent areas, and the reader corrects cartilage margins when necessary by placing seed points (yellow x’s).

Figure 2

LACS coordinate-derived segmentation areas in femur and tibia. (a) In the femur, a cylindrical coordinate system defines locations in 3D space by 3 variables: r, θ, and z. (b) In the tibia, a two-axis coordinate system defines locations in 2D space by 2 variables: x and y. MF = medial femur; LF = lateral femur; MT = medial tibia; LT = lateral tibia.

Figure 3

LACS cartilage thickness vs. Chondrometrics cartilage thickness in 126 knees, at baseline and two-year follow-up. A. Lateral femur; B. Medial femur; C. Lateral tibia; D. Medial tibia.

Figure 4

Bland-Altman plots of the differences between LACS and Chondrometrics measurements.

Figure 5

LACS SRM Heat-maps; A. Lateral femur; B. Medial femur; C. Lateral tibia; D. Medial tibia; randomly selected knees (left panels), and knees selected for two-year loss by Chondrometrics measures (right panels); darker regions represent greater responsiveness over two years.