Article

Automatic morphometric cartilage quantification in the medial tibial plateau from MRI for osteoarthritis grading

IT University of Copenhagen, København, Capital Region, Denmark
Osteoarthritis and Cartilage (Impact Factor: 4.17). 07/2007; 15(7):808-18. DOI: 10.1016/j.joca.2007.01.013
Source: PubMed

ABSTRACT

To evaluate whether a novel, fully automatic, morphometric cartilage quantification framework is suitable for assessing level of knee osteoarthritis (OA) in clinical trials.
The population was designed with a normal population and groups with varying degree of OA of both sexes and at ages from 21 to 78. Posterior-anterior X-rays were acquired in semi-flexed, load-bearing position. The radiographic signs of OA were evaluated based on the Kellgren and Lawrence score (KL) and the joint space width (JSW) was measured. Turbo 3D T1 magnetic resonance imaging (MRI) scans were acquired with resolution 0.7x0.7x0.8mm(3) from a 0.18T scanner. The morphometric cartilage quantification from MRI resulted in volume, surface area, thickness and surface curvature for the medial tibial cartilage compartment. These quantifications were evaluated against JSW with respect to precision and ability to separate healthy subjects from OA subjects.
The automatic, morphometric cartilage quantifications allowed fairly precise measurements with scan-rescan coefficient of variations (CVs) in the range from 3.4% to 6.3%. All quantifications, including JSW, allowed separation of the groups of healthy and OA subjects. However, for separation of the healthy from the borderline cases (KL 0 vs KL 1), only the Cartilage Curvature quantification allowed statistically significant separation (P<0.01).
The novel morphometric framework shows promise for use in clinical trials. The ability of the Cartilage Curvature quantification to detect the early stages of OA and the effectiveness of the focal thickness Q10 measure are particularly noteworthy. Furthermore, these results may indirectly support that low-field MRI may be a low-cost option for clinical trials.

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Available from: Jenny Folkesson, Jan 28, 2016
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    • "Quantitative measures of surface curvature and joint incongruity have also been determined from MR images [37] and were observed to discriminate between subjects with various radiographic OA grades cross-sectionally at 0.2 T [38, 39]. Curvature estimates at different scales (at 0.2 T) were reported to be associated with the magnitude of cartilage loss longitudinally [40] and cartilage homogeneity (quantified by measuring entropy from the distribution of signal intensities in tibial cartilage from 0.2 T gradient echo images) was reported to discriminate between subjects without and with early radiographic OA [18]. "
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    ABSTRACT: Quantitative measures of cartilage morphology (i.e., thickness) represent potentially powerful surrogate endpoints in osteoarthritis (OA). These can be used to identify risk factors of structural disease progression and can facilitate the clinical efficacy testing of structure modifying drugs in OA. This paper focuses on quantitative imaging of articular cartilage morphology in the knee, and will specifically deal with different cartilage morphology outcome variables and regions of interest, the relative performance and relationship between cartilage morphology measures, reference values for MRI-based knee cartilage morphometry, imaging protocols for measurement of cartilage morphology (including those used in the Osteoarthritis Initiative), sensitivity to change observed in knee OA, spatial patterns of cartilage loss as derived by subregional analysis, comparison of MRI changes with radiographic changes, risk factors of MRI-based cartilage loss in knee OA, the correlation of MRI-based cartilage loss with clinical outcomes, treatment response in knee OA, and future directions of the field.
    Full-text · Article · Jan 2011
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    • "The implementation extends the earlier version[18]by Jenny Folkesson (then at University of Copenhagen). We would like to acknowledge CCBR for the study data and scans[21]. "
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    ABSTRACT: Fully automatic imaging biomarkers may allow quantification of patho-physiological processes that a radiologist would not be able to assess reliably. This can introduce new insight but is problematic to validate due to lack of meaningful ground truth expert measurements. Rather than quantification accuracy, such novel markers must therefore be validated against clinically meaningful end-goals such as the ability to allow correct diagnosis. We present a method for automatic cartilage surface smoothness quantification in the knee joint. The quantification is based on a curvature flow method used on tibial and femoral cartilage compartments resulting from an automatic segmentation scheme. These smoothness estimates are validated for their ability to diagnose osteoarthritis and compared to smoothness estimates based on manual expert segmentations and to conventional cartilage volume quantification. We demonstrate that the fully automatic markers eliminate the time required for radiologist annotations, and in addition provide a diagnostic marker superior to the evaluated semi-manual markers.
    Full-text · Article · Mar 2010 · Proceedings of SPIE - The International Society for Optical Engineering
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    • "In previous work, we used MRI cartilage markers normalized by the width of the tibial plateau to adjust for joint size. This improved diagnostic performance for the markers [22] and can also be used in the aggregate markers [41]. Using normalized MRI markers [22], both the diagnostic longevity marker (AUC = 0.84, nGEE/nPA = 21/16) and the prognostic longevity marker (AUC = 0.75, OR = 4.8, nGEE/nPA = 28/39) retained very similar performance as the non-normalized markers. "
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    ABSTRACT: At present, no disease-modifying osteoarthritis drugs (DMOADS) are approved by the FDA (US Food and Drug Administration); possibly partly due to inadequate trial design since efficacy demonstration requires disease progression in the placebo group. We investigated whether combinations of biochemical and magnetic resonance imaging (MRI)-based markers provided effective diagnostic and prognostic tools for identifying subjects with high risk of progression. Specifically, we investigated aggregate cartilage longevity markers combining markers of breakdown, quantity, and quality. The study included healthy individuals and subjects with radiographic osteoarthritis. In total, 159 subjects (48% female, age 56.0 +/- 15.9 years, body mass index 26.1 +/- 4.2 kg/m2) were recruited. At baseline and after 21 months, biochemical (urinary collagen type II C-telopeptide fragment, CTX-II) and MRI-based markers were quantified. MRI markers included cartilage volume, thickness, area, roughness, homogeneity, and curvature in the medial tibio-femoral compartment. Joint space width was measured from radiographs and at 21 months to assess progression of joint damage. Cartilage roughness had the highest diagnostic accuracy quantified as the area under the receiver-operator characteristics curve (AUC) of 0.80 (95% confidence interval: 0.69 to 0.91) among the individual markers (higher than all others, P < 0.05) to distinguish subjects with radiographic osteoarthritis from healthy controls. Diagnostically, cartilage longevity scored AUC 0.84 (0.77 to 0.92, higher than roughness: P = 0.03). For prediction of longitudinal radiographic progression based on baseline marker values, the individual prognostic marker with highest AUC was homogeneity at 0.71 (0.56 to 0.81). Prognostically, cartilage longevity scored AUC 0.77 (0.62 to 0.90, borderline higher than homogeneity: P = 0.12). When comparing patients in the highest quartile for the longevity score to lowest quartile, the odds ratio of progression was 20.0 (95% confidence interval: 6.4 to 62.1). Combination of biochemical and MRI-based biomarkers improved diagnosis and prognosis of knee osteoarthritis and may be useful to select high-risk patients for inclusion in DMOAD clinical trials.
    Full-text · Article · Jul 2009 · Arthritis research & therapy
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