The KNee OsteoArthritis Prediction (KNOAP2020) challenge: An image analysis challenge to predict incident symptomatic radiographic knee osteoarthritis from MRI and X-ray images.

OBJECTIVES: The KNee OsteoArthritis Prediction (KNOAP2020) challenge was organized to objectively compare methods for the prediction of incident symptomatic radiographic knee osteoarthritis within 78 months on a test set with blinded ground truth. DESIGN: The challenge participants were free to use any available data sources to train their models. A test set of 423 knees from the Prevention of Knee Osteoarthritis in Overweight Females (PROOF) study consisting of magnetic resonance imaging (MRI) and X-ray image data along with clinical risk factors at baseline was made available to all challenge participants. The ground truth outcomes, i.e., which knees developed incident symptomatic radiographic knee osteoarthritis (according to the combined ACR criteria) within 78 months, were not provided to the participants. To assess the performance of the submitted models, we used the area under the receiver operating characteristic curve (ROCAUC) and balanced accuracy (BACC). RESULTS: Seven teams submitted 23 entries in total. A majority of the algorithms were trained on data from the Osteoarthritis Initiative. The model with the highest ROCAUC (0.64 (95% confidence interval (CI): 0.57-0.70)) used deep learning to extract information from X-ray images combined with clinical variables. The model with the highest BACC (0.59 (95% CI: 0.52-0.65)) ensembled three different models that used automatically extracted X-ray and MRI features along with clinical variables. CONCLUSION: The KNOAP2020 challenge established a benchmark for predicting incident symptomatic radiographic knee osteoarthritis. Accurate prediction of incident symptomatic radiographic knee osteoarthritis is a complex and still unsolved problem requiring additional investigation.

Is increased joint loading detrimental to obese patients with knee osteoarthritis? A secondary data analysis from a randomized trial.

OBJECTIVE: To investigate whether increased knee joint loading due to improved ambulatory function and walking speed following weight loss achieved over 16 weeks accelerates symptomatic and structural disease progression over a subsequent 1 year weight maintenance period in an obese population with knee osteoarthritis (OA). METHODS: Data from a prospective study of weight loss in obese patients with knee OA (the CARtilage in obese knee OsteoarThritis (CAROT) study) were used to determine changes in knee joint compressive loadings (model estimated) during walking after a successful 16 week weight loss intervention. The participants were divided into 'Unloaders' (participants that reduced joint loads) and 'Loaders' (participants that increased joint loads). The primary symptomatic outcome was changes in knee symptoms, measured with the Knee injury and Osteoarthritis Outcome Score (KOOS) questionnaire, during a subsequent 52 weeks weight maintenance period. The primary structural outcome was changes in tibiofemoral cartilage loss assessed semi-quantitatively (Boston Leeds Knee Osteoarthritis Score (BLOKS) from MRI after the 52 weight maintenance period. RESULTS: 157 participants (82% of the CAROT cohort) with medial and/or lateral knee OA were classified as Unloaders (n = 100) or Loaders (n = 57). The groups showed similar significant changes in symptoms (group difference: -2.4 KOOS points [95% CI -6.8:1.9]) and cartilage loss (group difference: -0.06 BLOKS points [95% CI -0.22:0.11) after 1 year, with no statistically significant differences between Loaders and Unloaders. CONCLUSION: For obese patients undergoing a significant weight loss, increased knee joint loading for 1 year was not associated with accelerated symptomatic and structural disease progression compared to a similar weight loss group that had reduced ambulatory compressive knee joint loads. CLINICALTRIALSGOV: NCT00655941.

Vertebral fracture risk (VFR) score for fracture prediction in postmenopausal women.

SUMMARY: Early prognosis of osteoporosis risk is not only important to individual patients but is also a key factor when screening for osteoporosis drug trial populations. We present an osteoporosis fracture risk score based on vertebral heights. The score separated individuals who sustained fractures (by follow-up after 6.3 years) from healthy controls at baseline. INTRODUCTION: This case-control study was designed to assess the ability of three novel fracture risk scoring methods to predict first incident lumbar vertebral fractures in postmenopausal women matched for classical risk factors such as BMD, BMI, and age. METHODS: This was a case-control study of 126 postmenopausal women, 25 of whom sustained at least one incident lumbar fracture and 101 controls that maintained skeletal integrity over a 6.3-year period. Three methods for fracture risk assessment were developed and tested. They are based on anterior, middle, and posterior vertebral heights measured from vertebrae T12-L5 in lumbar radiographs at baseline. Each score's fracture prediction potential was investigated in two variants using (1) measurements from the single most deformed vertebra or (2) average measurements across vertebrae T12-L5. Emphasis was given to the vertebral fracture risk (VFR) score. RESULTS: All scoring methods demonstrated significant separation of cases from controls at baseline. Specifically, for the VFR score, cases and controls were significantly different (0.67 ± 0.04 vs. 0.35 ± 0.03, p < 10 (-6)) with an AUC of 0.82. Dividing the VFR scores into tertiles, the fracture odds ratio for the highest versus lowest tertile was 35 (p < 0.001). Sorting the combined case-control group according to VFR score resulted in 90% of cases in the top half. CONCLUSION: At baseline, the three scores separated cases from controls and, especially, the VFR score appears to be predictive of fractures. Control experiments, however also, indicate that VFR-based fracture prediction is operator/annotator dependent and high-quality annotations are needed for good fracture prediction.

Increased urinary excretion of C-telopeptides of type II collagen (CTX-II) predicts cartilage loss over 21 months by MRI.

OBJECTIVE: Osteoarthritis (OA) is characterized by increased bone and cartilage metabolism leading to joint damage. The urinary excretion of C-telopeptides of type II collagen (CTX-II) has earlier predicted progression in radiographic OA (ROA)--useful for participant selection in clinical studies of potential disease modifying OA drugs (DMOADs). We investigated the longitudinal interrelationship between CTX-II and knee cartilage volume quantified from magnetic resonance imaging (MRI). METHODS: We followed 158 subjects [48% females, 36 with knee ROA at baseline (BL)] for 21 months. The Kellgren and Lawrence (KL) index and joint space width were assessed from radiographs (acquired load-bearing, semi-flexed). MRI scans were acquired from a 0.18 T Esaote scanner (40 degrees flip angle (FA), TR 50 ms, TE 16 ms, scan time 10 min, resolution 0.7 mm x 0.7 mm x 0.8 mm) and medial tibial and femoral cartilage volume was quantified. Radiographs and MRI were acquired at BL and follow-up. Fasting morning urine samples (second void) were collected for BL CTX-II measurement. RESULTS: CTX-II was 56% higher in ROA subjects (P=0.0001). In addition, elevated BL CTX-II was associated with radiographic progression (by KL or joint space narrowing) although not statistically significant. Contrarily, elevated BL CTX-II predicted longitudinal cartilage loss by MRI (middle/high tertiles had odds ratios 4.0/3.9, P<0.01) corresponding to 3.1% increased yearly cartilage loss. CONCLUSION: Prognostic markers in study selection criteria must ensure that placebo-treated participants progress to enable efficacy demonstration. And efficacy markers must allow progression detection within the study period. Our results support applying CTX-II for selection of high risk subjects and applying the fully automatic MRI-based framework for quantification of cartilage loss.

Biochemical markers and the FDA Critical Path: how biomarkers may contribute to the understanding of pathophysiology and provide unique and necessary tools for drug development.

The aim of this review is to discuss the potential usefulness of a novel class of biochemical markers, neoepitopes, in the context of the US Food and Drug Administration (FDA) Critical Path Initiative, which emphasizes biomarkers of safety and efficacy as areas of pivotal interest. Examples of protein degradation fragments--neoepitopes--that have proven useful for research on bone and cartilage are collagen type I and collagen type II degradation products, respectively. These markers have utility in the translational approach, as they can be used to estimate safety and efficacy in both preclinical models and clinical settings. Biochemical markers of tissue degradation may provide optimal tools, which in combination with other techniques, prove essential to drug discovery and development.

Should subchondral bone turnover be targeted when treating osteoarthritis?

OBJECTIVE: Osteoarthritis (OA) is the most common form of arthritic disease, and it is a major cause of disability and impaired quality of life in the elderly. OA is a complex disease of the entire joint, including bone and cartilage, thereby presenting alternative approaches for treatment. This review summarizes emerging observations from cell biology to preliminary clinical trials, describing interactions between the bone and cartilage components. We speculate whether a treatment for OA would be possible without targeting the bone compartment? METHODS: Peer-reviewed articles found using pre-defined search criteria and published in the PubMed database until June 2007 are summarized. In addition, abstracts from the OsteoArthritis Research Society International (OARSI) conferences in the time period 2000-2007 were included. RESULTS: Bone and cartilage health seem to be tightly associated. Ample evidence is found for bone changes during progression of OA, including, but not limited to, increased turnover in the subchondral bone, thinning of the trabecular structure, osteophytes, bone marrow lesions and sclerosis of the subchondral plate. In addition, a range of investigations has described secondary positive effects on cartilage health when bone resorption was suppressed, or deterioration of the cartilage when resorption is increased. CONCLUSION: An optimal treatment for OA might include targeting both the bone and cartilage compartments. Hence, as several cell systems are to be targeted in a safe manner, limited options seem possible.

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

OBJECTIVE: To evaluate whether a novel, fully automatic, morphometric cartilage quantification framework is suitable for assessing level of knee osteoarthritis (OA) in clinical trials. METHOD: 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. RESULTS: 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). CONCLUSION: 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.

Separation of healthy and early osteoarthritis by automatic quantification of cartilage homogeneity.

OBJECTIVE: Cartilage loss as determined either by magnetic resonance imaging (MRI) or by joint space narrowing in X-rays is the result of cartilage erosion. However, metabolic processes within the cartilage that later result in cartilage loss may be a more accurate assessment method for early changes. Early biological processes of cartilage destruction are among other things, a combination of proteoglycan turnover, as a result of altered charge distributions, and local alterations in water content (edema). As water distribution is detectable by MRI, the aim of this study was to investigate cartilage homogeneity visualized by MRI related to water distribution, as a potential very early marker for early detection of knee osteoarthritis (OA). DESIGN: One hundred and fourteen right and left knees from 71 subjects aged 22-79 years were scanned using a Turbo 3D T(1) sequence on a 0.18T MRI Esaote scanner. The medial compartment of the tibial cartilage sheet was segmented using a fully automatic voxel classification scheme based on supervised learning. From the segmented cartilage sheet, homogeneity was quantified by measuring entropy from the distribution of signal intensities inside the compartment. For each knee an X-ray was acquired and the knees were categorized by the Kellgren and Lawrence (KL) index and the joint space width (JSW) was measured. The P-values for separating the groups by each of JSW, cartilage volume, cartilage mean intensity, and cartilage homogeneity were calculated using the unpaired t-test. RESULTS: The P-value for separating the group diagnosed as KL 0 from the group being KL 1 based on JSW, volume and mean signal intensity the values were P=0.9, P=0.4 and P=0.0009, respectively. In contrast, the P-value for homogeneity was P=0.0004. The precision of the measures assessed, as a test-retest root mean square coefficient of variation (RMS-CV%) was 3.9% for JSW, 7.4% for volume, 3.9% for mean signal intensity and 3.0% for homogeneity quantification. CONCLUSION: These data demonstrate that the distribution of components of the articular matrix precedes erosion, as measured by cartilage homogeneity related to water concentration. We show that homogeneity was able to separate early OA from healthy individuals in contrast to traditional volume and JSW quantifications. These data suggest that cartilage homogeneity quantification may be able to quantify early biochemical changes in articular cartilage prior to cartilage loss and thereby provide better identification of patients for OA trials who may respond better to medicinal intervention of some treatments. In addition, this study supports the feasibility of using low-field MRI in clinical studies.

RNA pseudoknots: translational frameshifting and readthrough on viral RNAs.

Ribosomal frameshifting on retroviral RNAs has been proposed to be mediated by slippage of two adjacent tRNAs into the -1 direction at a specific heptanucleotide sequence. Here we report a computer-aided analysis of the structure around the established or putative frameshift sites in a number of retroviral, coronaviral, toroviral, and luteoviral RNAs and two dsRNA yeast viruses. In almost all cases a stable hairpin was predicted four to nine nucleotides downstream of the shifty heptanucleotide. More than half of the resulting hairpin loops give rise to potential pseudoknotting with sequences downstream of this hairpin. Especially in the case of the shifty heptanucleotides U UUA AAC and G GGA AAC, stable downstream pseudoknots are present. Indications were also found for the presence of pseudoknots downstream of amber stop condons at readthrough sites in some retroviral RNAs.

Analysis of the role of the pseudoknot component in the SRV-1 gag-pro ribosomal frameshift signal: loop lengths and stability of the stem regions.

The simian retrovirus-1 (SRV-1) gag-pro frameshift signal was identified in previous work, and the overall structure of the pseudoknot involved was confirmed (ten Dam E, Brierley I, Inglis S, Pleij C, 1994, Nucleic Acids Res 22:2304-2310). Here we report on the importance of specific elements within the pseudoknot. Some mutations in stem S1 that maintain base pairing have reduced frameshift efficiencies. This indicates that base pairing in itself is not sufficient. In contrast, frameshifting correlates qualitatively with the calculated stability of mutations in S2. The stems thus play different roles in the frameshift event. The nature of the base in L1 has little influence on frameshift efficiency. It is however required to bridge S2; deleting it lowers frameshifting from 23 to 9%. In L2, frameshift efficiency was not affected in a mutant that changed 10 to 12 bases. This makes it unlikely that the primary sequence of L2 plays a role in -1 frameshifting, in contrast to readthrough in Moloney murine leukemia virus (Wills N, Gesteland R, Atkins J, 1994, EMBO J 13:4137-4144). Deletions of 2 and 3 bases gave more frameshifting than the wild type, probably reflecting the increased stability of the pseudoknot due to a shorter loop L2. Deleting even more bases reduces frameshifting compared to wild-type levels. At this point, stress will build up in L2, and this will reduce overall pseudoknot stability.