Choice of knee cartilage thickness change metric for different treatment goals in efficacy studies

Quantitative measurement of cartilage morphology in osteoarthritis: current knowledge and future directions

Quantitative measures of cartilage morphology ("cartilage morphometry") extracted from high resolution 3D magnetic resonance imaging (MRI) sequences have been shown to be sensitive to osteoarthritis (OA)-related change and also to treatment interventions. Cartilage morphometry is therefore nowadays widely used as outcome measure for observational studies and randomized interventional clinical trials. The objective of this narrative review is to summarize the current status of cartilage morphometry in OA research, to provide insights into aspects relevant for the design of future studies and clinical trials, and to give an outlook on future developments. It covers the aspects related to the acquisition of MRIs suitable for cartilage morphometry, the analysis techniques needed for deriving quantitative measures from the MRIs, the quality assurance required for providing reliable cartilage measures, and the appropriate participant recruitment criteria for the enrichment of study cohorts with knees likely to show structural progression. Finally, it provides an overview over recent clinical trials that relied on cartilage morphometry as a structural outcome measure for evaluating the efficacy of disease-modifying OA drugs (DMOAD).

Deep learning-based segmentation of knee MRI for fully automatic subregional morphological assessment of cartilage tissues: Data from the Osteoarthritis Initiative

Morphological changes in knee cartilage subregions are valuable imaging-based biomarkers for understanding progression of osteoarthritis, and they are typically detected from magnetic resonance imaging (MRI). So far, accurate segmentation of cartilage has been done manually. Deep learning approaches show high promise in automating the task; however, they lack clinically relevant evaluation. We introduce a fully automatic method for segmentation and subregional assessment of articular cartilage, and evaluate its predictive power in context of radiographic osteoarthritis progression. Two data sets of 3D double-echo steady-state (DESS) MRI derived from the Osteoarthritis Initiative were used: first, n = 88; second, n = 600, 0-/12-/24-month visits. Our method performed deep learning-based segmentation of knee cartilage tissues, their subregional division via multi-atlas registration, and extraction of subregional volume and thickness. The segmentation model was developed and assessed on the first data set. Subsequently, on the second data set, the morphological measurements from our and the prior methods were analyzed in correlation and agreement, and, eventually, by their discriminative power of radiographic osteoarthritis progression over 12 and 24 months, retrospectively. The segmentation model showed very high correlation (r > 0.934) and agreement (mean difference < 116 mm³ ) in volumetric measurements with the reference segmentations. Comparison of our and manual segmentation methods yielded r = 0.845-0.973 and mean differences = 262-501 mm³ for weight-bearing cartilage volume, and r = 0.770-0.962 and mean differences = 0.513-1.138 mm for subregional cartilage thickness. With regard to osteoarthritis progression, our method found most of the significant associations identified using the manual segmentation method, for both 12- and 24-month subregional cartilage changes. The method may be effectively applied in osteoarthritis progression studies to extract cartilage-related imaging biomarkers.

Diffuse tibiofemoral cartilage change prior to the development of accelerated knee osteoarthritis: Data from the osteoarthritis initiative

We compared the spatial distribution of tibiofemoral cartilage change between individuals who will develop accelerated knee osteoarthritis (KOA) versus typical onset of KOA prior to the development of radiographic KOA. We conducted a longitudinal case-control analysis of 129 individuals from the Osteoarthritis Initiative. We assessed the percent change in tibiofemoral cartilage on magnetic resonance images at 36 informative locations from 2 to 1 year prior to the development of accelerated (n = 44) versus typical KOA (n = 40). We defined cartilage change in the accelerated and typical KOA groups at 36 informative locations based on thresholds of cartilage percent change in a no KOA group (n = 45). We described the spatial patterns of cartilage change in the accelerated KOA and typical KOA groups and performed a logistic regression to determine if diffuse cartilage change (predictor; at least half of the tibiofemoral regions demonstrating change in multiple informative locations) was associated with KOA group (outcome). There was a non-significant trend that individuals with diffuse tibiofemoral cartilage change were 2.2 times more likely to develop accelerated knee OA when compared with individuals who develop typical knee OA (OR [95% CI] = 2.2 [0.90-5.14]. Adults with accelerated or typical KOA demonstrate heterogeneity in spatial distribution of cartilage thinning and thickening. These results provide preliminary evidence of a different spatial pattern of cartilage change between individuals who will develop accelerated versus typical KOA. These data suggest there may be different mechanisms driving the early structural disease progression between accelerated versus typical KOA. Clin. Anat. 32:369-378, 2019. © 2018 Wiley Periodicals, Inc.