Single nucleotide polymorphism genes and mitochondrial DNA haplogroups as biomarkers for early prediction of knee osteoarthritis structural progressors: use of supervised machine learning classifiers.

BACKGROUND: Knee osteoarthritis is the most prevalent chronic musculoskeletal debilitating disease. Current treatments are only symptomatic, and to improve this, we need a robust prediction model to stratify patients at an early stage according to the risk of joint structure disease progression. Some genetic factors, including single nucleotide polymorphism (SNP) genes and mitochondrial (mt)DNA haplogroups/clusters, have been linked to this disease. For the first time, we aim to determine, by using machine learning, whether some SNP genes and mtDNA haplogroups/clusters alone or combined could predict early knee osteoarthritis structural progressors. METHODS: Participants (901) were first classified for the probability of being structural progressors. Genotyping included SNP genes TP63, FTO, GNL3, DUS4L, GDF5, SUPT3H, MCF2L, and TGFA; mtDNA haplogroups H, J, T, Uk, and others; and clusters HV, TJ, KU, and C-others. They were considered for prediction with major risk factors of osteoarthritis, namely, age and body mass index (BMI). Seven supervised machine learning methodologies were evaluated. The support vector machine was used to generate gender-based models. The best input combination was assessed using sensitivity and synergy analyses. Validation was performed using tenfold cross-validation and an external cohort (TASOAC). RESULTS: From 277 models, two were defined. Both used age and BMI in addition for the first one of the SNP genes TP63, DUS4L, GDF5, and FTO with an accuracy of 85.0%; the second profits from the association of mtDNA haplogroups and SNP genes FTO and SUPT3H with 82.5% accuracy. The highest impact was associated with the haplogroup H, the presence of CT alleles for rs8044769 at FTO, and the absence of AA for rs10948172 at SUPT3H. Validation accuracy with the cross-validation (about 95%) and the external cohort (90.5%, 85.7%, respectively) was excellent for both models. CONCLUSIONS: This study introduces a novel source of decision support in precision medicine in which, for the first time, two models were developed consisting of (i) age, BMI, TP63, DUS4L, GDF5, and FTO and (ii) the optimum one as it has one less variable: age, BMI, mtDNA haplogroup, FTO, and SUPT3H. Such a framework is translational and would benefit patients at risk of structural progressive knee osteoarthritis.

Knee effusion volume assessed by magnetic resonance imaging and progression of knee osteoarthritis: data from the Osteoarthritis Initiative.

Objective: To examine whether baseline knee joint effusion volume and the change in effusion volume over 1 year are associated with cartilage volume loss, progression of radiographic OA (ROA) over 4 years and risk of total knee replacement over 6 years. Methods: This study included 4115 Osteoarthritis Initiative participants with knee joint effusion volume quantified by MRI at baseline. The change in effusion volume over 1 year was assessed. Cartilage volume loss and progression of ROA over 4 years were assessed using MRI and X-ray and total knee replacement over 6 years was assessed. Multiple linear regression and binary logistic regression were used for data analyses. Results: Baseline knee effusion volume (per 5 ml) was positively associated with a loss of medial and lateral cartilage volume [regression coefficient 0.13%/year (95% CI 0.10, 0.17) and 0.13%/year (95% CI 0.10, 0.16), respectively, both P < 0.001], progression of ROA [odds ratio (OR) 1.28 (95% CI 1.20, 1.37), P < 0.001], and risk of knee replacement [OR 1.12 (95% CI 1.05, 1.20), P = 0.001]. A 5 ml increase in knee effusion volume over 1 year was positively associated with medial cartilage volume loss [regression coefficient 0.09%/year (95% CI 0.04, 0.15), P = 0.001], progression of ROA [OR 1.21 (95% CI 1.11, 1.33), P < 0.001] and risk of knee replacement [OR 1.24 (95% CI 1.12, 1.37), P < 0.001]. Conclusions: Knee joint effusion volume assessed from MRI provides a continuous and sensitive measure that was associated with cartilage volume loss, progression of ROA and risk of total knee replacement. It may provide a method to identify individuals with an inflammatory OA phenotype who are at higher risk of disease progression.

Bone curvature changes can predict the impact of treatment on cartilage volume loss in knee osteoarthritis: data from a 2-year clinical trial.

Objectives: Knee bone curvature assessed by MRI was associated with OA cartilage loss. A recent knee OA trial demonstrated the superiority of chondroitin sulfate over celecoxib (comparator) at reducing cartilage volume loss (CVL) in the medial compartment (condyle). The main objectives were to identify which baseline bone curvature regions of interest (BCROI) best associated with CVL and investigate whether baseline BCROI and 2-year change are correlated with the protective effect of chondroitin sulphate on CVL. Methods: This post hoc analysis of a clinical trial used the according-to-protocol population (chondroitin sulphate, n = 57; celecoxib, n = 63) baseline and 2-year MRI to assess bone curvature and CVL. Global optimum search identified the BCROI in the medial condyle using celecoxib as reference. Statistical analyses were performed with Pearson's correlation, Mann-Whitney U -test, Student's t -test and analysis of covariance. Results: The BCROI including the medial posterior condyle and lateral central condyle was found to correlate best with medial condyle CVL at 2 years ( r = 0.33, P = 0.008). In patients with a baseline BCROI value less than the median (more flattened bone), chondroitin sulphate demonstrated a protective effect on CVL compared with celecoxib in the medial compartment (P = 0.037). In patients with 2-year BCROI changes greater than the median (greater severity of bone flattening), chondroitin sulphate protected against CVL in the medial compartment, condyle and central plateau (P ⩽ 0.030). Conclusion: This study is the first to demonstrate the feasibility and usefulness of bone curvature measurements to predict effectiveness of OA treatment on CVL. The results identify bone curvature as a potential novel biomarker for knee OA clinical trials.

The levels of the adipokines adipsin and leptin are associated with knee osteoarthritis progression as assessed by MRI and incidence of total knee replacement in symptomatic osteoarthritis patients: a post hoc analysis.

OBJECTIVE: Limited studies have explored the association between adipokines and knee OA structural progression using quantitative MRI (qMRI), and very few have included total knee replacement (TKR) as a disease outcome. The objective of this study was to compare serum levels of five adipokines to cartilage volume loss (CVL) and investigate their predictive value for TKR. METHODS: The according-to-protocol population (n = 138) of a knee OA trial was used. Serum levels of adipsin (complement factor D), leptin, adiponectin, resistin and serpin E1, and cartilage volume were determined at baseline and 24 months with specific ELISAs and qMRI, respectively. Study knee TKR incidence up to 4 years post-trial was also assessed. RESULTS: Greater baseline values of adipsin and leptin correlated with increased CVL in the global knee and medial femur (P ⩽ 0.032) and of adipsin in the lateral compartment and femur (P ⩽ 0.028). Adiponectin showed an inverse correlation in the medial compartment and femur (P ⩽ 0.027). Resistin and serpin E1 were not associated with CVL. Multivariate analyses revealed that patients in the highest tertile at baseline of adipsin presented a greater odds ratio of CVL in the lateral compartment and femur (⩾2.87; P ⩽ 0.011), and those in the highest tertile of leptin in the medial compartment (2.78; P = 0.038). Most clinically relevant, patients in the highest tertile of adipsin or leptin at baseline had significantly greater incidence of TKR (P = 0.027). CONCLUSION: Data demonstrate that both adipsin and leptin predict greater CVL over time in the lateral and medial compartment, respectively. Importantly, this study also demonstrates that higher baseline levels of adipsin or leptin are associated with higher incidence of TKR.

Change in knee structure and change in tibiofemoral joint space width: a five year longitudinal population-based study.

BACKGROUND: Change in knee cartilage volume is frequently used as a proxy for change in knee joint space width over time, but longitudinal data on these associations is limited. We aimed to determine whether change in knee cartilage volume, new or worsening meniscal extrusion (ME), meniscal tears and cartilage defects over 2.4 years correlated with change in joint space width (JSW) over 5 years in older community dwelling adults. METHODS: Participants (n = 153) had their right knee imaged using MR imaging and x-ray at baseline, and after 2.4 years (MRI) and 5 years (x-ray). Cartilage volume, cartilage defects, meniscal extrusions and meniscal tears were assessed on sagittal T1-weighted fat-suppressed MRI. JSW was assessed using standard fixed semi-flexed view radiographs, and scored on those with adequate alignment. RESULTS: Participants were 51-79 (mean 62) years old; 48% were female. Cartilage volume reduced over time (medial -134 ± 202 µL/year, lateral -106 ± 165 µL/year, p < 0.001), as did JSW (medial -0.05 ± 0.16 mm/year, lateral -0.12 ± 0.24 mm/year, p < 0.001). In multivariable analysis, the only consistent predictor of change in JSW was new or worsening ME (medial tibia R(2) 3.1%, p = 0.031; medial femur R(2) 3.2%, p = 0.024); change in cartilage volume correlated with change in JSW laterally (R(2) 4.8%, p = 0.007) and was borderline medially (R(2) 2.2%, p = 0.064); there was no association for meniscal tears or cartilage defects. The magnitude of these associations were similar albeit somewhat greater for ME in participants with radiographic OA (R(2) 6.2%, p = 0.017). CONCLUSION: Change in ME and cartilage volume weakly predict change in JSW, but the vast majority of the variation remains unexplained. Since MRI examines cartilage directly while radiographs examine it indirectly, these results cast doubt on the validity of using JSW as a proxy measure of cartilage loss.

Disease-modifying effect of strontium ranelate in a subset of patients from the Phase III knee osteoarthritis study SEKOIA using quantitative MRI: reduction in bone marrow lesions protects against cartilage loss.

OBJECTIVE: To explore, using MRI, the disease-modifying effect of strontium ranelate (SrRan) treatment on cartilage volume loss (CVL) and bone marrow lesions (BMLs) in a subset of patients from a Phase III clinical trial in knee osteoarthritis (OA) (SrRan Efficacy in Knee OsteoarthrItis triAl (SEKOIA)). MATERIAL AND METHODS: Patients with primary symptomatic knee OA were randomised to receive either SrRan 1 g/day or 2 g/day or placebo (SEKOIA study). A subset of these patients had MRIs at baseline, 12, 24 and 36 months to assess the knee cartilage volume and BMLs. Missing values were imputed and the analyses were adjusted according to Bonferroni. RESULTS: In this MRI subset, the distribution of patients (modified intention-to-treat; n=330) was 113, 105 and 112 for SrRan 1 g/day, 2 g/day and placebo, respectively. The groups were fairly balanced at baseline regarding demographics, clinical symptoms or imaging characteristics. Treatment with SrRan 2 g/day significantly decreased CVL on the plateaus at 12 (p=0.002) and 36 (p=0.003) months compared with placebo. Of note, in the medial femur and plateau, SrRan 1 g/day, but not SrRan 2 g/day, had more CVL than placebo. In patients with BML in the medial compartment at baseline, the BML score at 36 months was decreased in both treatment groups compared with the placebo group (SrRan 1 g/day, p=0.002 and SrRan 2 g/day p=0.001, respectively), and CVL significantly decreased with SrRan 2 g/day (p=0.023) in the plateau compared with placebo. CONCLUSIONS: In knee OA patients, treatment with SrRan 2 g/day was found to have beneficial effects on structural changes by significantly reducing CVL in the plateau and BML progression in the medial compartment.

First-line analysis of the effects of treatment on progression of structural changes in knee osteoarthritis over 24 months: data from the osteoarthritis initiative progression cohort.

OBJECTIVE: To determine, using data from participants enrolled in the progression cohort of the OAI, the effects of conventional osteoarthritis (OA) pharmacological treatment and those of the combination of glucosamine and chondroitin sulfate (Glu/CS) on knee structural changes. METHODS: Six hundred patients with knee OA were stratified based on whether or not they received for 24 consecutive months the OA conventional pharmacological treatment and/or Glu/CS. The main outcomes were knee structural changes, including the loss of joint space width (JSW) and of cartilage volume measured by quantitative MRI. RESULTS: Participants reported taking (+) (n=300) or not taking (-) (n=300) OA treatment (analgesic/NSAIDs). The +analgesic/NSAIDs participants had higher Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores (p<0.001) and smaller JSW (p=0.01), reflecting more severe disease at baseline. In the -analgesic/NSAIDs group, participants taking Glu/CS had significantly reduced loss of cartilage volume at 24 months in the medial central plateau (p=0.007). Further subdivision revealed that this effect of Glu/CS occurred in participants with a higher severity of the disease (JSW≤median). In the +analgesic/NSAIDs group, those taking Glu/CS had significantly reduced loss of cartilage volume in the global plateau at 12 months (p=0.05), and in the central plateau at 24 months (p=0.05). These effects occurred in participants with less disease severity (JSW>median). By contrast, no significant reduction in JSW was found between all groups. CONCLUSIONS: In +analgesic/NSAIDs groups and -analgesic/NSAIDs groups, participants who took Glu/CS had reduced loss of cartilage volume over 24 months in subregions when assessed with qMRI, arguing for a disease-modifying effect of Glu/CS which could not be identified by X-rays.

A Machine Learning Model to Predict Knee Osteoarthritis Cartilage Volume Changes over Time Using Baseline Bone Curvature.

The hallmark of osteoarthritis (OA), the most prevalent musculoskeletal disease, is the loss of cartilage. By using machine learning (ML), we aimed to assess if baseline knee bone curvature (BC) could predict cartilage volume loss (CVL) at one year, and to develop a gender-based model. BC and cartilage volume were assessed on 1246 participants using magnetic resonance imaging. Variables included age, body mass index, and baseline values of eight BC regions. The outcome consisted of CVL at one year in 12 regions. Five ML methods were evaluated. Validation demonstrated very good accuracy for both genders (R ≥ 0.78), except the medial tibial plateau for the woman. In conclusion, we demonstrated, for the first time, that knee CVL at one year could be predicted using five baseline BC region values. This would benefit patients at risk of structural progressive knee OA.

Vastus medialis intramuscular fat is associated with reduced quadriceps strength, but not knee osteoarthritis severity.

BACKGROUND: Vastus medialis intramuscular fat has been proposed to be a modifiable determinant of knee cartilage loss in patients with knee osteoarthritis. The objective was to determine whether vastus medialis intramuscular fat relates to osteoarthritis severity and quadriceps muscle strength in patients with non-traumatic and post-traumatic knee osteoarthritis. METHODS: For this cross-sectional study, participants with knee osteoarthritis were classified into two groups: non-traumatic (n = 22; mean age = 60 years) and post-traumatic (n = 19; mean age = 56 years). Healthy adults were included (n = 22; mean age = 59 years). A 3-Tesla magnetic resonance imaging was used to measure vastus medialis cross-sectional area and intramuscular fat. Isometric knee extensor muscle torque was assessed using an isokinetic dynamometer and normalized to body mass (Nm/kg). Knee osteoarthritis severity was assessed using standing antero-posterior radiographs (Kellgren-Lawrence scores). Regression analyses examined relationships between 1) vastus medialis intramuscular fat with knee osteoarthritis severity and osteoarthritis group, after accounting for sex and body mass index, and 2) knee extensor muscle torque with vastus medialis intramuscular fat, after accounting for sex and vastus medialis cross-sectional area. FINDINGS: Vastus medialis intramuscular fat was positively associated with body mass index (B = 0.321, P < 0.001), but not with osteoarthritis severity or group (P > 0.05). Higher vastus medialis intramuscular fat was associated with reduced knee extensor muscle torque (B = -0.040, P = 0.018). INTERPRETATION: Greater vastus medialis intramuscular fat was associated with lower quadriceps muscle strength in patients with knee OA. It is unclear whether this is due to the accumulation of vastus medialis intramuscular fat or other potential factors, such as diet and physical inactivity.

Chondroitin sulphate reduces both cartilage volume loss and bone marrow lesions in knee osteoarthritis patients starting as early as 6 months after initiation of therapy: a randomised, double-blind, placebo-controlled pilot study using MRI.

OBJECTIVE: To determine the effect of chondroitin sulphate (CS) treatment on cartilage volume loss, subchondral bone marrow lesions (BML), synovitis and disease symptoms in patients with knee osteoarthritis (OA). METHODS: In this pilot multicentre, randomised, double-blind, controlled trial in primary knee OA, 69 patients with clinical signs of synovitis were randomised to receive CS 800 mg or placebo once daily for 6 months followed by an open-label phase of 6 months in which patients in both groups received CS 800 mg once daily. Cartilage volume and BML were assessed by MRI at baseline and at 6 and 12 months; synovial membrane thickness was assessed at baseline and at 6 months. RESULTS: The CS group showed significantly less cartilage volume loss than the placebo group as early as 6 months for the global knee (p=0.030), lateral compartment (p=0.015) and tibial plateaus (p=0.002), with significance persisting at 12 months. Significantly lower BML scores were found for the CS group at 12 months in the lateral compartment (p=0.035) and the lateral femoral condyle (p=0.044). Disease symptoms were similar between the two groups. CONCLUSION: CS treatment significantly reduced the cartilage volume loss in knee OA starting at 6 months of treatment, and BML at 12 months. These findings suggest a joint structure protective effect of CS and provide new in vivo information on its mode of action in knee OA.

Risk factors predictive of joint replacement in a 2-year multicentre clinical trial in knee osteoarthritis using MRI: results from over 6 years of observation.

OBJECTIVE: To identify predictive factors for total knee replacement (TKR) using data from MRI of knee osteoarthritis patients in a phase III multicentre disease-modifying osteoarthritis drug (DMOAD) study. METHODS: Knee osteoarthritis patients from a 2-year clinical trial evaluating licofelone versus naproxen were investigated for the incidence of TKR of the study knee. Patients (n=161) who completed the study according to protocol were selected. Incidence of TKR was assessed blindly to the treatment following telephone interviews (n=123). RESULTS: 18 TKR (14.6%) were performed in 4-7 years following enrolment in the original study. More TKR were performed within the naproxen than the licofelone group (61% vs 39%, p=0.232). Baseline score of bone marrow lesions (BML) in the medial compartment (p=0.0001), medial joint space width (JSW) as assessed by standardised radiographs (p=0.0008), presence of severe medial meniscal tear (p=0.004), medial meniscal extrusion (p=0.013), and C-reactive protein level (p=0.049) were strong predictors of TKR. Changes at the end of the study also yielded strong predictors: change in cartilage volume of the medial compartment (p=0.005) and of the global knee (p=0.034), reduction in the JSW of greater than 7% (p=0.009), and WOMAC pain (p=0.009) and function (p=0.023) scores. Multivariate analysis showed that baseline severe medial meniscal tear (p=0.023) and presence of medial BML (p=0.025) were the strongest independent long-term predictors of TKR. CONCLUSION: This study shows that in the context of osteoarthritis trials, clinical data and structural changes identified by MRI allow prediction of a 'hard' outcome such as TKR. The findings support the usefulness and predictive value of MRI in defining study outcome in DMOAD trials.

A warning machine learning algorithm for early knee osteoarthritis structural progressor patient screening.

AIM: In osteoarthritis (OA) there is a need for automated screening systems for early detection of structural progressors. We built a comprehensive machine learning (ML) model that bridges major OA risk factors and serum levels of adipokines/related inflammatory factors at baseline for early prediction of at-risk knee OA patient structural progressors over time. METHODS: The patient- and gender-based model development used baseline serum levels of six adipokines, three related inflammatory factors and their ratios (36), as well as major OA risk factors [age and bone mass index (BMI)]. Subjects (677) were selected from the Osteoarthritis Initiative (OAI) progression subcohort. The probability values of being structural progressors (PVBSP) were generated using our previously published prediction model, including five baseline structural features of the knee, i.e. two X-rays and three magnetic resonance imaging variables. To identify the most important variables amongst the 47 studied in relation to PVBSP, we employed the ML feature classification methodology. Among five supervised ML algorithms, the support vector machine (SVM) demonstrated the best accuracy and use for gender-based classifiers development. Performance and sensitivity of the models were assessed. A reproducibility analysis was performed with clinical trial OA patients. RESULTS: Feature selections revealed that the combination of age, BMI, and the ratios CRP/MCP-1 and leptin/CRP are the most important variables in predicting OA structural progressors in both genders. Classification accuracies for both genders in the testing stage (OAI) were >80%, with the highest sensitivity of CRP/MCP-1. Reproducibility analysis showed an accuracy ⩾92%; the ratio CRP/MCP-1 demonstrated the highest sensitivity in women and leptin/CRP in men. CONCLUSION: This is the first time that such a framework was built for predicting knee OA structural progressors. Using this automated ML patient- and gender-based model, early prediction of knee structural OA progression can be performed with high accuracy using only three baseline serum biomarkers and two risk factors. PLAIN LANGUAGE SUMMARY: Machine learning model for early knee osteoarthritis structural progression Knee osteoarthritis is a well-known debilitating disease leading to reduced mobility and quality of life - the main causes of chronic invalidity. Disease evolution can be slow and span many years; however, for some individuals, the progression/evolution can be fast. Current treatments are only symptomatic and conventional diagnosis of osteoarthritis is not very effective in early identification of patients who will progress rapidly. To improve therapeutic approaches, we need a robust prediction model to stratify osteoarthritis patients at an early stage according to risk of joint structure disease progression.We hypothesize that a prediction model using a machine learning system would enable such an early identification of individuals for whom osteoarthritis knee structure will degrade rapidly. Data were from the Osteoarthritis Initiative, a National Institute of Health (United States) databank, and the robustness and generalizability of the developed model was further evaluated using osteoarthritis patients from an external cohort. Using the supervised machine learning system (support vector machine), we developed an automated patient- and gender-based model enabling an early clinical prognosis for individuals at high risk of structural progressive osteoarthritis. In brief, this model employed at baseline (when the subject sees a physician) easily obtained features consisting of the two main osteoarthritis risk factors, age and bone mass index (BMI), in addition to the serum levels of three molecules. Two of these molecules belong to a family of factors names adipokines and one to a related inflammatory factor. In brief, the model comprising a combination of age, BMI, and the ratios CRP/MCP-1 and leptin/CRP were found very robust for both genders, and the high accuracy persists when tested with an external cohort conferring the gender-based model generalizability. This study offers a new automated system for identifying early knee osteoarthritis structural progressors, which will significantly improve clinical prognosis with real time patient monitoring.

Machine Learning-Based Individualized Survival Prediction Model for Total Knee Replacement in Osteoarthritis: Data From the Osteoarthritis Initiative.

OBJECTIVE: By using machine learning, our study aimed to build a model to predict risk and time to total knee replacement (TKR) of an osteoarthritic knee. METHODS: Features were from the Osteoarthritis Initiative (OAI) cohort at baseline. Using the lasso method for variable selection in the Cox regression model, we identified the 10 most important characteristics among 1,107 features. The prognostic power of the selected features was assessed by the Kaplan-Meier method and applied to 7 machine learning methods: Cox, DeepSurv, random forests algorithm, linear/kernel support vector machine (SVM), and linear/neural multi-task logistic regression models. As some of the 10 first-found features included similar radiographic measurements, we further looked at using the least number of features without compromising the accuracy of the model. Prediction performance was assessed by the concordance index, Brier score, and time-dependent area under the curve (AUC). RESULTS: Ten features were identified and included radiographs, bone marrow lesions of the medial condyle on magnetic resonance imaging, hyaluronic acid injection, performance measure, medical history, and knee-related symptoms. The methodologies Cox, DeepSurv, and linear SVM demonstrated the highest accuracy (concordance index scores of 0.85, Brier score of 0.02, and an AUC of 0.87). DeepSurv was chosen to build the prediction model to estimate the time to TKR for a given knee. Moreover, we were able to decrease the features to only 3 and maintain the high accuracy (concordance index of 0.85, Brier score of 0.02, and AUC of 0.86), which included bone marrow lesions, Kellgren/Lawrence grade, and knee-related symptoms, to predict risk and time of a TKR event. CONCLUSION: For the first time, we developed a model using the OAI cohort to predict with high accuracy if a given osteoarthritic knee would require TKR, when a TKR would be required, and who would likely progress fast toward this event.

Clinical relevance of MRI knee abnormalities in Australian rules football players: a longitudinal study.

BACKGROUND/AIM: The clinical relevance of MRI knee abnormalities in athletes is unclear. This study aimed to determine the prevalence of MRI knee abnormalities in Australian Rules Football (ARF) players and describe their associations with pain, function, past and incident injury and surgery history. METHODS: 75 male players (mean age 21, range 16-30) from the Tasmanian State Football League were examined early in the playing season (baseline). History of knee injury/surgery and knee pain and function were assessed. Players underwent MRI scans of both knees at baseline. Clinical measurements and MRI scans were repeated at the end of the season, and incident knee injuries during the season were recorded. RESULTS: MRI knee abnormalities were common at baseline (67% bone marrow lesions, 16% meniscal tear/extrusion, 43% cartilage defects, 67% effusion synovitis). Meniscal tears/extrusion and synovial fluid volume were positively associated with knee symptoms, but these associations were small in magnitude and did not persist after further accounting for injury history. Players with a history of injury were at a greater risk of having meniscal tears/extrusion, effusion synovitis and greater synovial fluid volume. In contrast, players with a history of surgery were at a greater risk of having cartilage defects and meniscal tears/extrusion. Incident injuries were significantly associated with worsening symptoms, BML development and incident meniscal damage. CONCLUSIONS: MRI abnormalities are common in ARF players, are linked to a previous knee injury and surgery history, as well as incident injury but do not dictate clinical symptomatology.

Relationship between bone marrow lesions, cartilage loss and pain in knee osteoarthritis: results from a randomised controlled clinical trial using MRI.

OBJECTIVE: To assess in a multicentre randomised double-blind phase III clinical trial evaluating the effect of licofelone in comparison with naproxen on knee osteoarthritis (OA) the presence of, and change in, bone marrow lesions (BML) over time, their relationship to cartilage volume loss, meniscal extrusion and pain. METHODS: Patients with knee OA were selected from the dataset of a recently published randomised controlled trial. MRI was performed at baseline, 6, 12 and 24 months to assess BML score (modified Whole-Organ MRI Score) and cartilage volume changes over time. Pain levels were assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaire. RESULTS: One hundred and sixty-one patients completed the study according to protocol. The global knee and all subregions showed increased BML scores over time (p <0.001, 24 months) except for the medial tibial plateau in the licofelone group. In multivariate regression analysis, licofelone treatment predicted reduction in BML score in the medial tibial plateau (ß= -0.280, p = 0.026). BML scores at baseline correlated with cartilage volume over time; however, correlation was limited to 12 months. No positive correlation was found between BML and WOMAC scores. CONCLUSIONS: BML scores were found to increase over time, probably owing to accumulation of chronic structural changes. Correlation between BML and cartilage volume was strong at baseline but not over time, probably due to the study drug. Licofelone reduced the BML score in the medial tibial plateau. In contrast to previous reports, no positive relationship was found between BML score (baseline or change over time) and pain, probably an effect of the selected population.

Meniscal extrusion predicts increases in subchondral bone marrow lesions and bone cysts and expansion of subchondral bone in osteoarthritic knees.

OBJECTIVES: Meniscal extrusion is often present in knees with OA, and has been associated with cartilage changes. It is unknown whether meniscal extrusion is related to subchondral bone. The aim of the study was to examine the relationship between meniscal extrusion and knee cartilage and subchondral bone, and also changes in these structures over 2 years in a cohort with mild to moderate knee OA. METHODS: One hundred and seventeen subjects with knee OA entered the study and underwent MRI on their symptomatic knee at baseline and approximately 2 years later. Meniscal extrusion was assessed at baseline; tibial cartilage volume and plateau bone area, subchondral bone marrow lesions (BMLs) and bone cysts were measured at baseline and follow-up. RESULTS: At baseline, meniscal extrusion was associated with reduced tibial cartilage volume, increased tibial plateau area, increased prevalence of BMLs and bone cysts in both medial and lateral tibiofemoral compartments (all P < or = 0.001). Baseline medial meniscal extrusion was associated with increased expansion of tibial plateau bone (P = 0.04), increases in BMLs (P = 0.02) and bone cysts (P = 0.003) in the medial tibiofemoral compartment over 2 years. CONCLUSIONS: Meniscal extrusion predicts increases in subchondral bone lesions and tibial plateau bone expansion in patients with knee OA. These data suggest that subchondral bone changes are an early consequence of meniscal extrusion. This may reflect the impaired ability of an extruded meniscus to optimally distribute mechanical loading across the tibial plateau.

Bone marrow lesions in people with knee osteoarthritis predict progression of disease and joint replacement: a longitudinal study.

OBJECTIVES: The presence of bone marrow lesions (BMLs) has been linked to pain and progression of knee OA. The aim of this study was to determine the relationship between BMLs and longitudinal change in tibial cartilage volume and risk of knee joint replacement in subjects with knee OA. METHODS: One hundred and nine men and women with symptomatic knee OA were recruited. The same knee was imaged using MRI at baseline and ∼2 years later. Tibial cartilage volume and BMLs were measured. Knee joint replacement over 4 years was determined. RESULTS: The mean age of the subjects at baseline was 63.2 (s.d. 10.3) years. BMLs were present in 66% of the subjects. Cross-sectionally, BMLs were negatively associated with both medial (regression coefficient -121.4; 95% CI -183.8, -859.1; P<0.001) and lateral (regression coefficient -142.1; 95% CI -241.8, -42.4; P=0.01) tibial cartilage volume data. Longitudinally, for every 1-score increase in baseline BML severity (range 0-4), the annual total tibial cartilage loss was increased by 1.14% (95% CI 0.29%, 1.87%; P=0.01). The risk of knee joint replacement over 4 years increased with increasing BML score (odds ratio 1.57; 95% CI 1.04, 2.35; P=0.03). CONCLUSION: The prevalence and severity of BMLs are associated with less tibial cartilage volume and greater cartilage loss over 2 years. Moreover, severity of BMLs was positively associated with risk of knee joint replacement over 4 years. This provides further support for the importance of BMLs in identifying those with OA most likely to progress. Identifying factors that prevent or reduce the severity of BMLs may provide an important target in the prevention of disease progression and treatment of OA, and the subsequent need for arthroplasty.

Serum adipokines/related inflammatory factors and ratios as predictors of infrapatellar fat pad volume in osteoarthritis: Applying comprehensive machine learning approaches.

OBJECTIVE: The infrapatellar fat pad (IPFP) has been associated with knee osteoarthritis onset and progression. This study uses machine learning (ML) approaches to predict serum levels of some adipokines/related inflammatory factors and their ratios on knee IPFP volume of osteoarthritis patients. METHODS: Serum and MRI were from the OAI at baseline. Variables comprised the 3 main osteoarthritis risk factors (age, gender, BMI), 6 adipokines, 3 inflammatory factors, and their 36 ratios. IPFP volume was assessed on MRI with a ML methodology. The best variables and models were identified in Total-cohort (n = 678), High-BMI (n = 341) and Low-BMI (n = 337), using a selection approach based on ML methods. RESULTS: The best model for each group included three risk factors and adipsin/C-reactive protein combined for Total-cohort, adipsin/chemerin; High-BMI, chemerin/adiponectin HMW; and Low-BMI, interleukin-8. Gender separation improved the prediction (13-16%) compared to the BMI-based models. Reproducibility with osteoarthritis patients from a clinical trial was excellent (R: female 0.83, male 0.95). Pseudocodes based on gender were generated. CONCLUSION: This study demonstrates for the first time that the combination of the serum levels of adipokines/inflammatory factors and the three main risk factors of osteoarthritis could predict IPFP volume with high reproducibility, with the superior performance of the model accounting for gender separation.

Associations of Joint Line Tenderness and Patellofemoral Grind With Long-Term Knee Joint Outcomes: Data From the Osteoarthritis Initiative.

OBJECTIVE: To examine whether joint line tenderness and patellofemoral grind from physical examination were associated with cartilage volume loss, worsening of radiographic osteoarthritis, and the risk of total knee replacement. METHODS: This study examined 4,353 Osteoarthritis Initiative participants. For each measurement of joint line tenderness and patellofemoral grind, the patterns were defined as no (none at baseline and at 1 year), fluctuating (present at either time point), and persistent (present at both time points). Cartilage volume loss and worsening of radiographic osteoarthritis over 4 years were assessed using magnetic resonance imaging and radiographs, and total knee replacement over 6 years was assessed. RESULTS: A total of 35.0% of participants had joint line tenderness, and 15.8% had patellofemoral grind. Baseline patellofemoral grind, but not joint line tenderness, was associated with increased cartilage volume loss (1.08% per year versus 0.96% per year; P = 0.02) and an increased risk of total knee replacement (odds ratio [OR] 1.55 [95% confidence interval (95% CI) 1.11-2.17]; P = 0.01). While the patterns of joint line tenderness were not significantly associated with joint outcomes, participants with persistent patellofemoral grind had an increased rate of cartilage volume loss (1.30% per year versus 0.90% per year; P < 0.001) and an increased risk of total knee replacement (OR 2.10 [95% CI 1.30-3.38]; P = 0.002) compared with those participants without patellofemoral grind. CONCLUSION: Patellofemoral grind, but not joint line tenderness, may represent a clinical marker associated with accelerated cartilage volume loss over 4 years and an increased risk of total knee replacement over 6 years. This simple clinical examination may provide clinicians with an inexpensive way to identify those at higher risk of disease progression who should be targeted for surveillance and management.