Dataset Information

Brief Report: Cartilage Thickness Change as an Imaging Biomarker of Knee Osteoarthritis Progression: Data From the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium.

ABSTRACT: OBJECTIVE:To investigate the association of cartilage thickness change over 24 months, as determined by magnetic resonance imaging (MRI), with knee osteoarthritis (OA) progression at 24-48 months. METHODS:This nested case-control study included 600 knees with a baseline Kellgren/Lawrence (K/L) grade of 1-3 from 600 Osteoarthritis Initiative (OAI) participants. Case knees (n?=?194) had both medial tibiofemoral radiographic joint space loss (?0.7 mm) and a persistent increase in the Western Ontario and McMaster Universities Osteoarthritis Index pain score (?9 on a 0-100 scale) 24-48 months from baseline. Control knees (n?=?406) included 200 with neither radiographic nor pain progression, 103 with radiographic progression only, and 103 with pain progression only. Medial and lateral femorotibial cartilage was segmented from sagittal 3T MRIs at baseline, 12 months, and 24 months. Logistic regression was used to assess the association of change in cartilage thickness, with a focus on the central medial femorotibial compartment, and OA progression. RESULTS:Central medial femorotibial compartment thickness loss was significantly associated with case status, with an odds ratio (OR) of 1.9 (95% confidence interval [95% CI] 1.6-2.3) (P < 0.0001). Association with case status reached P < 0.05 for both the central femur (OR 1.8 [95% CI 1.5-2.2]) and the central tibia (OR 1.6 [95% CI 1.3-1.9]). Lateral femorotibial compartment cartilage thickness loss, in contrast, was not significantly associated with case status. A reduction in central medial femorotibial compartment cartilage thickness was strongly associated with radiographic progression (OR 4.0 [95% CI 2.9-5.3]; P < 0.0001) and only weakly associated with pain progression (OR 1.3 [95% CI 1.1-1.6]; P < 0.01). CONCLUSION:Our findings indicate that loss of medial femorotibial cartilage thickness over 24 months is associated with the combination of radiographic and pain progression in the knee, with a stronger association for radiographic progression.

SUBMITTER: Eckstein F

PROVIDER: S-EPMC5495918 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Brief Report: Cartilage Thickness Change as an Imaging Biomarker of Knee Osteoarthritis Progression: Data From the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium.

Eckstein F F Collins J E JE Nevitt M C MC Lynch J A JA Kraus V B VB Katz J N JN Losina E E Wirth W W Guermazi A A Roemer F W FW Hunter D J DJ

Arthritis & rheumatology (Hoboken, N.J.) 20151201 12

<h4>Objective</h4>To investigate the association of cartilage thickness change over 24 months, as determined by magnetic resonance imaging (MRI), with knee osteoarthritis (OA) progression at 24-48 months.<h4>Methods</h4>This nested case-control study included 600 knees with a baseline Kellgren/Lawrence (K/L) grade of 1-3 from 600 Osteoarthritis Initiative (OAI) participants. Case knees (n = 194) had both medial tibiofemoral radiographic joint space loss (≥0.7 mm) and a persistent increase in the ...[more]

PMID: 26316262

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Project description:ObjectiveTo determine the optimal combination of imaging and biochemical biomarkers for use in the prediction of knee osteoarthritis (OA) progression.MethodsThe present study was a nested case-control trial from the Foundation of the National Institutes of Health OA Biomarkers Consortium that assessed study participants with a Kellgren/Lawrence grade of 1-3 who had complete biomarker data available (n = 539 to 550). Cases were participants' knees that had radiographic and pain progression between 24 and 48 months compared to baseline. Radiographic progression only was assessed in secondary analyses. Biomarkers (baseline and 24-month changes) that had a P value of <0.10 in univariate analysis were selected, including quantitative cartilage thickness and volume on magnetic resonance imaging (MRI), semiquantitative MRI markers, bone shape and area, quantitative meniscal volume, radiographic progression (trabecular bone texture [TBT]), and serum and/or urine biochemical markers. Multivariable logistic regression models were built using 3 different stepwise selection methods (complex models versus parsimonious models).ResultsAmong baseline biomarkers, the number of locations affected by osteophytes (semiquantitative), quantitative central medial femoral and central lateral femoral cartilage thickness, patellar bone shape, and semiquantitative Hoffa-synovitis predicted OA progression in most models (C statistic 0.641-0.671). In most models, 24-month changes in semiquantitative MRI markers (effusion-synovitis, meniscal morphologic changes, and cartilage damage), quantitative central medial femoral cartilage thickness, quantitative medial tibial cartilage volume, quantitative lateral patellofemoral bone area, horizontal TBT (intercept term), and urine N-telopeptide of type I collagen predicted OA progression (C statistic 0.680-0.724). A different combination of imaging and biochemical biomarkers (baseline and 24-month change) predicted radiographic progression only, which had a higher C statistic of 0.716-0.832.ConclusionThe present study highlights the combination of biomarkers with potential prognostic utility in OA disease-modifying trials. Properly qualified, these biomarkers could be used to enrich future trials with participants likely to experience progression of knee OA.

Project description:OBJECTIVE:To investigate the predictive and concurrent validity of magnetic resonance imaging (MRI)-based cartilage thickness change between baseline (BL) and year-two (Y2) follow-up (predictive validity) and between Y2 and Y4 follow-up (concurrent validity) for symptomatic and radiographic knee osteoarthritis (OA) progression during Y2?Y4. METHODS:777 knees from 777 Osteoarthritis Initiative (OAI) participants (age: 61.3 ± 9.0 years, BMI: 30.1 ± 4.8 kg/m2) with Kellgren Lawrence (KL) grade 1-3 at Y2 (visit before progression interval) had cartilage thickness measurements from 3T MRI at BL, Y2 (n = 777), and Y4 (n = 708). Analysis of covariance and logistic regression were used to assess the association of pain progression (?9 WOMAC units [scale 0-100], n = 205/572 with/without progression) and radiographic progression (?0.7 mm minimum joint space width (mJSW) loss, n = 166/611 with/without progression) between Y2 and Y4 with preceding (BL?Y2) and concurrent (Y2?Y4) change in central medial femorotibial (cMFTC) compartment cartilage thickness. RESULTS:Symptomatic progression was associated with concurrent (Y2?Y4: -305 ± 470 ?m vs -155 ± 346 ?m, Odds ratios (OR) = 1.5 [1.2, 1.7]) but not with preceding cartilage thickness loss in cMFTC (-150 ± 276 ?m vs -151 ± 299 ?m, OR = 0.9 95% CI: [0.8, 1.1]). Radiographic progression, in contrast, was significantly associated with both concurrent (-542 ± 550 ?m vs -98 ± 255 ?m, OR = 3.4 [2.6, 4.3]) and preceding cMFTC thickness loss (-229 ± 355 ?m vs -130 ± 270 ?m, OR = 1.3 [1.1, 1.5]). CONCLUSIONS:These results extend previous reports that did not discern predictive vs concurrent associations of cartilage thickness loss with OA progression. The observed predictive and concurrent validity of cartilage thickness loss for radiographic progression and observed concurrent validity for symptomatic progression provide an important step in qualifying cartilage thickness loss as a biomarker of knee OA progression. CLINICALTRIALS. GOV IDENTIFICATION:NCT00080171.

Project description:ObjectiveTo study the longitudinal performance of fully automated cartilage segmentation in knees with radiographic osteoarthritis (OA), we evaluated the sensitivity to change in progressor knees from the Foundation for the National Institutes of Health OA Biomarkers Consortium between the automated and previously reported manual expert segmentation, and we determined whether differences in progression rates between predefined cohorts can be detected by the fully automated approach.MethodsThe OA Initiative Biomarker Consortium was a nested case-control study. Progressor knees had both medial tibiofemoral radiographic joint space width loss (≥0.7 mm) and a persistent increase in Western Ontario and McMaster Universities Osteoarthritis Index pain scores (≥9 on a 0-100 scale) after 2 years from baseline (n = 194), whereas non-progressor knees did not have either of both (n = 200). Deep-learning automated algorithms trained on radiographic OA knees or knees of a healthy reference cohort (HRC) were used to automatically segment medial femorotibial compartment (MFTC) and lateral femorotibial cartilage on baseline and 2-year follow-up magnetic resonance imaging. Findings were compared with previously published manual expert segmentation.ResultsThe mean ± SD MFTC cartilage loss in the progressor cohort was -181 ± 245 μm by manual segmentation (standardized response mean [SRM] -0.74), -144 ± 200 μm by the radiographic OA-based model (SRM -0.72), and -69 ± 231 μm by HRC-based model segmentation (SRM -0.30). Cohen's d for rates of progression between progressor versus the non-progressor cohort was -0.84 (P < 0.001) for manual, -0.68 (P < 0.001) for the automated radiographic OA model, and -0.14 (P = 0.18) for automated HRC model segmentation.ConclusionA fully automated deep-learning segmentation approach not only displays similar sensitivity to change of longitudinal cartilage thickness loss in knee OA as did manual expert segmentation but also effectively differentiates longitudinal rates of loss of cartilage thickness between cohorts with different progression profiles.

Dataset Information

Brief Report: Cartilage Thickness Change as an Imaging Biomarker of Knee Osteoarthritis Progression: Data From the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium.

Publications

Brief Report: Cartilage Thickness Change as an Imaging Biomarker of Knee Osteoarthritis Progression: Data From the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium.

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