Minimum Joint Space Research Articles

Relevance of Biomarkers in Serum vs. Synovial Fluid in Patients with Knee Osteoarthritis.

The association between structural changes and pain sensation in osteoarthritis (OA) remains unclear. Joint deterioration in OA leads to the release of protein fragments that can either systemically (serum) or locally (synovial fluid; SF) be targeted as biomarkers and describe structural changes and potentially pain. Biomarkers of collagen type I (C1M), type II (C2M), type III (C3M), type X (C10C), and aggrecan (ARGS) degradation were measured in the serum and SF of knee OA patients. Spearman's rank correlation was used to assess the correlation of the biomarkers' levels between serum and SF. Linear regression adjusted for confounders was used to evaluate the associations between the biomarkers' levels and clinical outcomes. The serum C1M levels were negatively associated with subchondral bone density. The serum C2M levels were negatively associated with KL grade and positively associated with minimum joint space width (minJSW). The C10C levels in SF were negatively associated with minJSW and positively associated with KL grade and osteophyte area. Lastly, the serum C2M and C3M levels were negatively associated with pain outcomes. Most of the biomarkers seemed to mainly be associated with structural outcomes. The overall biomarkers of extracellular matrix (ECM) remodeling in serum and SF may provide different information and reflect different pathogenic processes.

Machine learning as an adjunct to expert observation in classification of radiographic knee osteoarthritis: findings from the Hertfordshire Cohort Study

BackgroundOsteoarthritis is the most prevalent type of arthritis. Many approaches exist for characterising radiographic knee OA, including machine learning (ML).AimsTo examine Kellgren and Lawrence (K&L) scores from ML and expert observation, minimum joint space and osteophyte in relation to pain and function.MethodsParticipants from the Hertfordshire Cohort Study, comprising individuals born in Hertfordshire from 1931 to 1939, were analysed. Radiographs were assessed by clinicians and ML (convolutional neural networks) for K&L scoring. Medial minimum joint space and osteophyte area were ascertained using the knee OA computer-aided diagnosis (KOACAD) program. The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) was administered. Receiver operating characteristic analysis was implemented for minimum joint space, osteophyte, and observer- and ML-derived K&L scores in relation to pain (WOMAC pain score > 0) and impaired function (WOMAC function score > 0).Results359 participants (aged 71–80) were analysed. Among both sexes, discriminative capacity regarding pain and function was fairly high for observer-derived K&L scores [area under curve (AUC): 0.65 (95% CI 0.57, 0.72) to 0.70 (0.63, 0.77)]; results were similar among women for ML-derived K&L scores. Discriminative capacity was moderate among men for minimum joint space in relation to pain [0.60 (0.51, 0.67)] and function [0.62 (0.54, 0.69)]. AUC < 0.60 for other sex-specific associations.DiscussionObserver-derived K&L scores had higher discriminative capacity regarding pain and function compared to minimum joint space and osteophyte. Among women, discriminative capacity was similar for observer- and ML-derived K&L scores.ConclusionML as an adjunct to expert observation for K&L scoring may be beneficial due to the efficiency and objectivity of ML.

An Interpretable Machine Learning Model for Predicting 10-Year Total Hip Arthroplasty Risk

BackgroundAs the demand for total hip arthroplasty (THA) rises, a predictive model for THA risk may aid patients and clinicians in augmenting shared decision-making. We aimed to develop and validate a model predicting THA within 10 years in patients using demographic, clinical, and deep learning (DL)-automated radiographic measurements. MethodsPatients enrolled in the osteoarthritis initiative were included. DL algorithms measuring osteoarthritis- and dysplasia-relevant parameters on baseline pelvis radiographs were developed. Demographic, clinical, and radiographic measurement variables were then used to train generalized additive models to predict THA within 10 years from baseline. A total of 4,796 patients were included [9,592 hips; 58% female; 230 THAs (2.4%)]. Model performance using 1) baseline demographic and clinical variables 2) radiographic variables, and 3) all variables was compared. ResultsUsing 110 demographic and clinical variables, the model had a baseline area under the receiver operating curve (AUROC) of 0.68 and area under the precision recall curve (AUPRC) of 0.08. Using 26 DL-automated hip measurements, the AUROC was 0.77 and AUPRC was 0.22. Combining all variables, the model improved to an AUROC of 0.81 and AUPRC of 0.28. Three of the top five predictive features in the combined model were radiographic variables, including minimum joint space, along with hip pain and analgesic use. Partial dependency plots revealed predictive discontinuities for radiographic measurements consistent with literature thresholds of osteoarthritis progression and hip dysplasia. ConclusionA machine learning model predicting 10-year THA performed more accurately with DL radiographic measurements. The model weighted predictive variables in concordance with clinical THA pathology assessments.

Development and evaluation of nomograms for predicting osteoarthritis progression based on MRI cartilage parameters: data from the FNIH OA biomarkers Consortium

BackgroundOsteoarthritis (OA) is a leading cause of disability worldwide. However, the existing methods for evaluating OA patients do not provide enough comprehensive information to make reliable predictions of OA progression. This retrospective study aimed to develop prediction nomograms based on MRI cartilage that can predict disease progression of OA.MethodsA total of 600 subjects with mild-to-moderate osteoarthritis from the Foundation for National Institute of Health (FNIH) project of osteoarthritis initiative (OAI). The MRI cartilage parameters of the knee at baseline were measured, and the changes in cartilage parameters at 12- and 24-month follow-up were calculated. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to extract the valuable characteristic parameters at different time points including cartilage thickness, cartilage volume, subchondral bone exposure area and uniform cartilage thickness in different sub regions of the knee, and the MRI cartilage parameters score0, scoreΔ12, and scoreΔ24 at baseline, 12 months, and 24 months were constructed. ScoreΔ12, and scoreΔ24 represent changes between 12 M vs. baseline, and 24 M vs. baseline, respectively. Logistic regression analysis was used to construct the nomogram0, nomogramΔ12, and nomogramΔ24, including MRI-based score and risk factors. The area under curve (AUC) was used to evaluate the differentiation of nomograms in disease progression and subgroup analysis. The calibration curve and Hosmer-Lemeshow (H-L) test were used to verify the calibration of the nomograms. Clinical usefulness of each prediction nomogram was verified by decision curve analysis (DCA). The nomograms with predictive efficacy were analyzed by secondary analysis. Internal verification was assessed using bootstrapping validation.ResultsEach nomogram included cartilage score, KL grade, WOMAC pain score, WOMAC disability score, and minimum joint space width. The AUC of nomogram0, nomogramΔ12, and nomogramΔ24 in predicing the progression of radiology and pain were 0.69, 0.64, and 0.71, respectively. All three nomograms had good calibration. Analysis by DCA showed that the clinical effectiveness of nomogramΔ24 was higher than others. Secondary analysis showed that nomogram0 and nomogramΔ24 were more capable of predicting OA radiologic progression than pain progression.ConclusionNomograms based on MRI cartilage change were useful for predicting the progression of mild to moderate OA.

A Semi-Automatic Approach for Holistic 3D Assessment of Temporomandibular Joint Changes

The literature lacks a reliable holistic approach for the three-dimensional (3D) assessment of the temporomandibular joint (TMJ) including all three adaptive processes, which are believed to contribute to the position of the mandible: (1) adaptive condylar changes, (2) glenoid fossa changes, and (3) condylar positional changes within the fossa. Hence, the purpose of the present study was to propose and assess the reliability of a semi-automatic approach for a 3D assessment of the TMJ from cone-beam computed tomography (CBCT) following orthognathic surgery. The TMJs were 3D reconstructed from a pair of superimposed pre- and postoperative (two years) CBCT scans, and spatially divided into sub-regions. The changes in the TMJ were calculated and quantified by morphovolumetrical measurements. To evaluate the reliability, intra-class correlation coefficients (ICC) were calculated at a 95% confidence interval on the measurements of two observers. The approach was deemed reliable if the ICC was good (>0.60). Pre- and postoperative CBCT scans of ten subjects (nine female; one male; mean age 25.6 years) with class II malocclusion and maxillomandibular retrognathia, who underwent bimaxillary surgery, were assessed. The inter-observer reliability of the measurements on the sample of the twenty TMJs was good to excellent, ICC range (0.71-1.00). The range of the mean absolute difference of the repeated inter-observer condylar volumetric and distance measurements, glenoid fossa surface distance measurements, and change in minimum joint space distance measurements were (1.68% (1.58)-5.01% (3.85)), (0.09 mm (0.12)-0.25 mm (0.46)), (0.05 mm (0.05)-0.08 mm (0.06)) and (0.12 mm (0.09)-0.19 mm (0.18)), respectively. The proposed semi-automatic approach demonstrated good to excellent reliability for the holistic 3D assessment of the TMJ including all three adaptive processes.

Analysis of Hand Joint Space Morphology in Women and Men with Hereditary Hemochromatosis

Hereditary hemochromatosis (HH) causes unbalanced iron deposition in many organs including the joints leading to severe cartilage loss and bone damage in the metacarpophalangeal joints (MCPJ). High-resolution peripheral quantitative computed tomography (HR-pQCT) and its joint space width (JSW) quantification algorithm quantifies in vivo 3D joint morphology. We therefore aimed to (i) determine feasibility and performance of the JSW algorithm in HH, (ii) quantify joint space morphology, and (iii) investigate the relationship between morphological and clinical parameters in HH. Here, we performed an exploratory study on 24 HH patients and sex- and age-matched controls using HR-pQCT imaging of MCPJ. Mineralized bone structure was automatically segmented from the grayscale image data and periosteal surface bone masks and joint space masks were generated. Mean, minimal, and maximal joint space width (JSW; JSW.MIN; JSW.MAX), JSW heterogeneity (JSW.SD), JSW asymmetry (JSW.AS), and joint space volume (JSV) were computed. Demographics and, for HH patients, disease-specific parameters were recorded. Segmentation of JS was very good with 79.7% of MCPJs successfully segmented at first attempt and 20.3% requiring semi-manual correction. HH men showed larger JSV at all MCPs (+ 25.4% < JSV < + 41.8%, p < 0.05), larger JSW.MAX at MCP 3-4 (+ 14%, 0.006 < p < 0.062), and wider JSW (+ 13%, p = 0.043) at MCP 4 relative to HH women. Compared to controls, both HH men and HH women showed larger JSW.AS and smaller JSW.MIN at all MCP levels, reaching significance for HH men at MCP 2 and 3 (JSW.AS: + 323% < JSW.AS < + 359%, 0.020 < p < 0.043; JSW.MIN: − 216% < JSW.MIN < − 225%, p < 0.043), and for women at MCP 3 (JSW.AS: + 180%, p = 0.025; JSW.MIN: − 41.8%, p = 0.022). Time since HH diagnosis was correlated positively with MCP 4 JSW.AS and JSW.SD (0.463 < ρ < 0.499, p < 0.040), and the number of phlebotomies since diagnosis was correlated with JSW.SD at all MCPs (0.432 < ρ < 0.535, p < 0.050). HR-pQCT-based JSW quantification in MCPJ of HH patients is feasible, performs well even in narrow JS, and allows to define the microstructural joint burden of HH.

Relationship of early postoperative perceived leg length discrepancy to the progression of osteoarthritis in the contralateral hip after unilateral total hip arthroplasty-a retrospective cohort study using propensity score matching.

[Purpose] This study aimed to identify the relationship between the early postoperative perceived leg length discrepancy after unilateral total hip arthroplasty and the progression of osteoarthritis in the contralateral hip. [Participants and Methods] This was a retrospective cohort study of 65 patients who underwent primary unilateral total hip arthroplasty for bilateral hip osteoarthritis. The minimum joint space width of the contralateral hip was measured preoperatively. The change in minimum joint space width one year postoperatively compared with preoperatively was measured. At three weeks postoperatively, patients were divided into the perceived and non-perceived leg length discrepancy groups using the block test. Patients with a perceived leg length discrepancy of 2 mm or more and less than 2 mm were grouped into the perceived and non-perceived leg length discrepancy groups, respectively. Before and after propensity score matching, the change in minimum joint space width between the two groups from the preoperative period to one year postoperatively was compared. [Results] In the pre-propensity matching sample, there was no significant difference in the change in minimum joint space width between the two groups. In the post-propensity matching sample, the change in minimum joint space width in the perceived leg length discrepancy group was significantly larger than that in the non-perceived leg length discrepancy group. [Conclusion] The early postoperative perceived leg length discrepancy after unilateral total hip arthroplasty may affect the progression of osteoarthritis in the contralateral hip.

Artificial intelligence in osteoarthritis: repair by knee joint distraction shows association of pain, radiographic and immunological outcomes.

Knee joint distraction (KJD) has been associated with clinical and structural improvement and SF marker changes. The current objective was to analyse radiographic changes after KJD using an automatic artificial intelligence-based measurement method and relate these to clinical outcome and SF markers. Twenty knee osteoarthritis patients were treated with KJD in regular care. Radiographs and WOMAC were collected before and ∼1 year post-treatment. SF was aspirated before, during and after treatment; biomarker levels were assessed by immunoassay. Radiographs were analysed to obtain compartmental minimum and standardized joint space width (JSW), Kellgren-Lawrence (KL) grades, compartmental joint space narrowing (JSN) scores, and osteophytosis and sclerosis scores. Results were analysed for the most affected compartment (MAC) and least affected compartment. Radiographic changes were analysed using the Wilcoxon signed rank test for categorical and paired t-test for continuous variables. Linear regression was used to calculate associations between changes in JSW, WOMAC pain and SF markers. Sixteen patients could be evaluated. JSW, KL and JSN improved in around half of the patients, significant only for MAC JSW (P < 0.05). MAC JSW change was positively associated with WOMAC pain change (P < 0.04). Greater monocyte chemoattractant protein 1 (MCP-1) and lower TGFβ-1 increases were significantly associated with changes in MAC JSW (P < 0.05). MCP-1 changes were positively associated with WOMAC pain changes (P < 0.05). Automatic radiographic measurements show improved joint structure in most patients after KJD in regular care. MAC JSW increased significantly and was associated with SF biomarker level changes and even with improvements in pain as experienced by these patients.

Pain Sensitization and Neuropathic Pain-like Symptoms Associated with Effectiveness of Exercise Therapy in Patients with Hip and Knee Osteoarthritis.

Pain sensitization and neuropathic pain-like symptoms are some of the common pain symptoms in patients with lower limbs, including hip and knee, osteoarthritis (HOA/KOA). Exercise therapy has been the first-line treatment; however, the effects differ for each patient. This prospective cohort study investigated the relationship between the effectiveness of exercise therapy and pretreatment characteristics (radiologic severity, pain sensitization, and neuropathic pain-like symptoms) of patients with HOA/KOA. We assessed the pain intensity using a numerical rating scale (NRS) before and after 12 weeks of exercise therapy in patients with HOA/KOA (n = 101). Before treatment, the Kellgren–Lawrence (K-L) grade; minimum joint space width (mJSW); pressure pain threshold (PPT) and temporal summation of pain (TSP) at the affected joint, tibia, and forearm; Central Sensitization Inventory-9; and painDETECT questionnaire (PDQ) were assessed. Cluster analysis was based on the pretreatment NRS and change in NRS with exercise therapy to identify the subgroups of pain reduction. The pretreatment characteristics of each cluster were compared. According to the results of the cluster analyses, patients in cluster 1 had severe pain that did not improve after exercise therapy, patients in cluster 2 had severe pain that improved, and those in cluster 3 had mild pain that improved. The patients in cluster 1 exhibited lower PPT at all measurement sites, higher TSP at the affected joint, and higher PDQ scores than those in other clusters. There was no difference in the K-L grade and mJSW among the clusters. The subgroup with severe pain and pain sensitization or neuropathic pain-like symptoms at pretreatment, even with mild joint deformity, may have difficulty in achieving improvement in pain after 12 weeks of exercise therapy. These findings could be useful for prognosis prediction and for planning exercise therapy and combining with other treatment.

A Comprehensive, Multidisciplinary Assessment for Knee Osteoarthritis Following Traumatic Unilateral Lower Limb Loss in Service Members.

Knee osteoarthritis (KOA) is a primary source of long-term disability and decreased quality of life (QoL) in service members (SM) with lower limb loss (LL); however, it remains difficult to preemptively identify and mitigate the progression of KOA and KOA-related symptoms. The objective of this study was to explore a comprehensive cross-sectional evaluation, at the baseline of a prospective study, for characterizing KOA in SM with traumatic LL. Thirty-eight male SM with traumatic unilateral LL (23 transtibial and 15 transfemoral), 9.5 ± 5.9 years post-injury, were cross-sectionally evaluated at initial enrollment into a prospective, longitudinal study utilizing a comprehensive evaluation to characterize knee joint health, functionality, and QoL in SM with LL. Presences of medial, lateral, and/or patellofemoral articular degeneration within the contralateral knee were identified via magnetic resonance imaging(for medically eligible SM; Kellgren-Lawrence Grade [n = 32]; and Outerbridge classification [OC; n = 22]). Tri-planar trunk and pelvic motions, knee kinetics, along with temporospatial parameters, were quantified via full-body gait evaluation and inverse dynamics. Concentrations of 26 protein biomarkers of osteochondral tissue degradation and inflammatory activity were identified via serum immunoassays. Physical function, knee symptoms, and QoL were collected via several patient reported outcome measures. KOA was identified in 12 of 32 (37.5%; KL ≥ 1) SM with LL; however, 16 of 22 SM presented with patellofemoral degeneration (72.7%; OC ≥ 1). Service members with versus without KOA had a 26% reduction in the narrowest medial tibiofemoral joint space. Biomechanically, SM with versus without KOA walked with a 24% wider stride width and with a negative correlation between peak knee adduction moments and minimal medial tibiofemoral joint space. Physiologically, SM with versus without KOA exhibited elevated concentrations of pro-inflammatory biomarker interleukin-7 (+180%), collagen breakdown markers collagen II cleavage (+44%), and lower concentrations of hyaluronic acid (-73%) and bone resorption biomarker N-telopeptide of Type 1 Collagen (-49%). Lastly, there was a negative correlation between patient-reported contralateral knee pain severity and patient-reported functionality and QoL. While 37.5% of SM with LL had KOA at the tibiofemoral joint (KL ≥ 1), 72.7% of SM had the presence of patellofemoral degeneration (OC ≥ 1). These findings demonstrate that the patellofemoral joint may be more susceptible to degeneration than the medial tibiofemoral compartment following traumatic LL.

Effects of pericapsular soft tissue and realignment exercises for patients with osteoarthritis of the hip and Harris Hip Score below 60 points

Objective To investigate the effectiveness of pericapsular soft tissue and realignment (PSTR) exercises for patients with osteoarthritis (OA) of the hip and Harris Hip Score (HHS) below 60 points. Most previous studies of hip exercise have not been applied for patients with moderate to severe hip OA, especially those with an HHS below 60 points. Most studies of hip exercise in OA have involved muscle strength training, stretching, functional training and aerobic fitness programs, and have not included pelvic realignment exercise. We investigated the effect of pelvic realignment exercise for patients with hip OA and HHS below 60 points. Methods Design: multicenter, prospective, observational, single-arm study. Setting: clinical examination on an outpatient basis. Participants: 193 patients with hip OA and HHS below 60 points. Interventions: patient education and supervised PSTR exercises. Outcome measures: primary outcome: HHS; secondary outcomes: changes in numerical rating scale (NRS) scores, abduction of range of motion, Timed Up and Go (TUG) test within 30 min after PSTR exercises at baseline and other six items, full analysis set (FAS, all participants who performed PSTR exercises) and subgroup analysis (participants with minimal joint space (MJS) of 0 mm at baseline). Results FAS analysis (N = 193): significant differences in HHS were found between baseline and 3 month follow-up, and between baseline and 6 month follow-up in the Unilateral and Bilateral OA groups (p < .001). All mean differences were within the 95% confidence interval. Significant improvement in NRS scores, abduction of range of motion, and TUG test within 30 min after PSTR exercises were found at baseline (p < .001). Subgroup analysis (N = 130): the results revealed significant differences (p < .001) in HHS and NRS, abduction of range of motion and TUG test within 30 min after PSTR exercises at baseline, as in the FAS analysis. Conclusion Our findings suggested that PSTR exercises were effective for patients with HHS below 60 points, even those with MJS of 0 mm. Clinical Trials Registry 20 July 2017 (UMIN000028277)

Fully Automatic Knee Joint Segmentation and Quantitative Analysis for Osteoarthritis from Magnetic Resonance (MR) Images Using a Deep Learning Model.

BackgroundWe aimed to develop and evaluate a deep learning-based method for fully automatic segmentation of knee joint MR imaging and quantitative computation of knee osteoarthritis (OA)-related imaging biomarkers.Material/MethodsThis retrospective study included 843 volumes of proton density-weighted fat suppression MR imaging. A convolutional neural network segmentation method with multiclass gradient harmonized Dice loss was trained and evaluated on 500 and 137 volumes, respectively. To assess potential morphologic biomarkers for OA, the volumes and thickness of cartilage and meniscus, and minimal joint space width (mJSW) were automatically computed and compared between 128 OA and 162 control data.ResultsThe CNN segmentation model produced reasonably high Dice coefficients, ranging from 0.948 to 0.974 for knee bone compartments, 0.717 to 0.809 for cartilage, and 0.846 for both lateral and medial menisci. The OA-related biomarkers computed from automatic knee segmentation achieved strong correlation with those from manual segmentation: average intraclass correlations of 0.916, 0.899, and 0.876 for volume and thickness of cartilage, meniscus, and mJSW, respectively. Volume and thickness measurements of cartilage and mJSW were strongly correlated with knee OA progression.ConclusionsWe present a fully automatic CNN-based knee segmentation system for fast and accurate evaluation of knee joint images, and OA-related biomarkers such as cartilage thickness and mJSW were reliably computed and visualized in 3D. The results show that the CNN model can serve as an assistant tool for radiologists and orthopedic surgeons in clinical practice and basic research.

Predicted and actual 2-year structural and pain progression in the IMI-APPROACH knee osteoarthritis cohort.

The IMI-APPROACH knee osteoarthritis study used machine learning (ML) to predict structural and/or pain progression, expressed by a structural (S) and pain (P) predicted-progression score, to select patients from existing cohorts. This study evaluates the actual 2-year progression within the IMI-APPROACH, in relation to the predicted-progression scores. Actual structural progression was measured using minimum joint space width (minJSW). Actual pain (progression) was evaluated using the Knee injury and Osteoarthritis Outcomes Score (KOOS) pain questionnaire. Progression was presented as actual change (Δ) after 2 years, and as progression over 2 years based on a per patient fitted regression line using 0, 0.5, 1 and 2-year values. Differences in predicted-progression scores between actual progressors and non-progressors were evaluated. Receiver operating characteristic (ROC) curves were constructed and corresponding area under the curve (AUC) reported. Using Youden's index, optimal cut-offs were chosen to enable evaluation of both predicted-progression scores to identify actual progressors. Actual structural progressors were initially assigned higher S predicted-progression scores compared with structural non-progressors. Likewise, actual pain progressors were assigned higher P predicted-progression scores compared with pain non-progressors. The AUC-ROC for the S predicted-progression score to identify actual structural progressors was poor (0.612 and 0.599 for Δ and regression minJSW, respectively). The AUC-ROC for the P predicted-progression score to identify actual pain progressors were good (0.817 and 0.830 for Δ and regression KOOS pain, respectively). The S and P predicted-progression scores as provided by the ML models developed and used for the selection of IMI-APPROACH patients were to some degree able to distinguish between actual progressors and non-progressors. ClinicalTrials.gov, https://clinicaltrials.gov, NCT03883568.

Quantifying Joint Congruence With an Elastic Foundation.

The level of congruence between the articulating surfaces of a diarthrodial joint can vary substantially between individuals. Quantifying joint congruence using the most widespread metric, the "congruence index," is not straightforward: the areas of the segmented bone that constitute the articular surfaces require accurate identification, their shape must be carefully described with appropriate functions, and the relative orientation of the surfaces measured precisely. In this work, we propose a new method of measuring joint congruence, which does not require these steps. First, a finite element (FE) simulation of an elastic layer compressed between each set of segmented bones is performed. These are then interpreted using the elastic foundation model, enabling an equivalent, but simpler, contact geometry to be identified. From this, the equivalent radius (quantification of joint congruence) is found. This defines the radius of a sphere contacting plane (or "ball on flat") that produces an equivalent contact to that in each joint. The minimal joint space width (in this joint position) can also be estimated from the FE simulations. The new method has been applied to ten healthy instances of the thumb metacarpophalangeal (MCP) joint. The ten thumb MCPs had similar levels and variability of congruence as the other diarthrodial joints that have been characterized previously. This new methodology enables efficient quantification of joint congruence and minimal joint space width directly from CT- or MRI-derived bone geometry in any relative orientation. It lends itself to large data sets and coupling with kinematic models.

OA20 Radiographic hip osteoarthritis classified semi-automatically on dual-energy x-ray absorptiometry scans is strongly predictive of total hip replacement: findings from UK Biobank

Abstract Background/Aims Radiographic hip osteoarthritis (rHOA) is traditionally defined on hip x-rays, using subjective methods such as Kellgren-Lawrence scoring. Associations between subjective rHOA measures and symptoms are inconsistent. Applying digital tools to high-resolution dual-energy X-ray absorptiometry (DXA) scans, we aimed to develop a novel semi-automated classifier for rHOA and evaluate the face validity of the classifier based on relationships with hip pain, hospital diagnosed OA (HES OA), and risk of total hip replacement (THR). Methods Using hip DXAs in UK Biobank, osteophyte grades 0-3 were assigned based on manually measured osteophyte area. Minimum joint space width (mJSW) was automatically measured using outline points placed by a machine learning-based algorithm and then used to categorise individuals into joint space narrowing (JSN) grades 0-3. Osteophyte and JSN grades were combined, using a novel system giving greater to weight to osteophytes, to categorise individuals into rHOA grades 0-4. Logistic regression giving odds ratios (OR) was used to examine associations between rHOA grade and hip pain, and HES OA. Cox proportional hazard models giving hazard ratios (HR) were used to examine associations between rHOA grade and subsequent THR. Our adjusted model included age, sex, height and weight as covariates. Results 40,340 individuals were included in the study (mean age 63.7 [range 44-82], 19294/21046 male/female). 32758 (81.2%) had rHOA grade 0, 4565 (11.3%) grade 1, 2317 (5.7%) grade 2, 543 (1.3%) grade 3, 157 (0.4%) grade 4, with all features of rHOA being more common in males than females. rHOA grades ≥2 were associated with all three clinical outcomes in both unadjusted and adjusted models, a clear dose-response relationship was seen with each increase in grade showing a large rise in OR/HRs (Table 1). Grade 4 rHOA was strongly predictive of THR (HR 57.70 [95%CI 38.08-87.44]). Conclusion We successfully applied a novel semi-automated classifier to over 40,000 individuals from UKB. The validity of our classifier was supported by the strong and progressive relationships observed between rHOA and hip pain, and HES OA and risk of THR. We conclude that hip DXAs provide a promising means of defining rHOA, with potential screening applications in the clinic. Disclosure B.G. Faber: None. R. Ebsim: None. F.R. Saunders: None. M. Frysz: None. C. Lindner: None. J.S. Gregory: None. R.M. Aspden: None. N.C. Harvey: None. G. Davey Smith: None. T. Cootes: None. J.H. Tobias: None.

ASSOCIATIONS BETWEEN PREDICTED AND ACTUAL STRUCTURAL PROGRESSION IN THE APPROACH COHORT

Purpose: Since osteoarthritis (OA) is a heterogeneous disease in terms of progression, many trials include patients showing barely or no progression, particularly in early stages of the disease. In the APPROACH study, machine learning models were trained to predict structural and pain progression of individual participants before inclusion. Predicted progression was differentiated into a structural (S) and pain (P) progression score, where the score (range 0-1) reflected the likelihood of a participant being a progressor. Structural progression was defined as a decrease in minimum joint space width (JSW) of at least 0.3mm/year. Only participants with the estimated highest 75% combined (P+S) score after screening were included. The purpose of the current study was to evaluate the associations between the predicted and actual structural progression according to different parameters over two years.

A GENOME WIDE ASSOCIATION STUDY OF DXA-DERIVED MINIMUM JOINT SPACE WIDTH OF THE HIP PROVIDES FURTHER INSIGHTS INTO ITS GENETIC ARCHITECTURE: FINDINGS FROM UK BIOBANK

Purpose: Cartilage is vital for joint health and function with its degeneration being a key feature of osteoarthritis (OA). Minimum joint space width measured on X-rays (mJSWX-ray) or high-resolution dual-energy X-ray absorptiometry images (mJSWDXA) can provide a proxy for cartilage thickness and pathological joint space narrowing (JSN). Defining the genetic architecture of mJSW provides a route to identify new biological pathways involved in JSN pathogenesis, some of which may represent future therapeutic targets.

Medial Tibial Osteophyte Width Strongly Reflects Medial Meniscus Extrusion Distance and Medial Joint Space Width Moderately Reflects Cartilage Thickness in Knee Radiographs.

BackgroundThe presence of medial tibial osteophytes on knee radiographs suggests cartilage wear, but may be associated with medial meniscus extrusion (MME). The joint space width of the medial compartment consists anatomically of cartilage and the medial meniscus, but which is most responsible for joint space narrowing remains unclear. Magnetic resonance imaging (MRI) reveals MME and cartilage thickness.PurposesTo determine which radiographic medial tibial osteophyte width correlates better with cartilage thickness or MME distance and which radiographic medial joint space width correlates better with cartilage thickness or MME distance.Study TypeCross‐sectional.PopulationTotal of 527 subjects, 253 females and 274 males, aged 30–79 years, included in the Kanagawa Knee Study.Field Strength/Sequence3 T/fat‐suppressed spoiled gradient echo and proton density weighted.AssessmentThe medial tibial osteophyte width and “the minimum joint space width at the medial compartment” (mJSW) were measured from plain radiographs. The cartilage region was automatically extracted from MRI data using software. The medial femoral and tibial cartilage regions were each divided into nine subregions, and the average thickness of the cartilage was determined in each region and subregion. MME was manually measured by two orthopedic surgeons using MRI coronal section images.Statistical TestsPearson's correlation coefficient and their comparison, with P < 0.05 considered statistically significant.ResultsThe absolute values of the correlation coefficients were 0.33 at maximum between osteophyte width and cartilage thickness and 0.76 between osteophyte width and MME; the value was significantly higher with MME than with cartilage thickness (P < 0.001). The absolute values of the correlation coefficients were 0.50 at maximum between mJSW and cartilage thickness and 0.16 between mJSW and MME; the value was significantly higher with cartilage thickness than with MME (P < 0.001).Data ConclusionThe medial tibial osteophyte width strongly reflected MME and the medial joint space width moderately reflected cartilage thickness.Level of Evidence3Technical Efficacy Stage3

Identification of early response to hypertonic dextrose prolotherapy markers in knee osteoarthritis patients by an inflammation-related cytokine array.

Osteoarthritis (OA) is one of the most common forms of arthritis, and hypertonic dextrose prolotherapy has long been used clinically to treat knee OA. The aim of this study was to investigate the inflammation-related protein-expression profile characterizing the efficacy of the hypertonic dextrose prolotherapy in knee OA as prognostic markers. OA patients over the age of 65 were recruited for Western Ontario McMaster University Osteoarthritis (WOMAC) index, knee X-ray evaluation and knee joint synovial fluid analysis before and after hypertonic dextrose prolotherapy. The expressions of inflammation-related factors were measured using a novel cytokine antibody array methodology. The cytokine levels were quantified by quantitative protein expression and analyzed by ELISA using the patients' knee-joint synovial fluid. The WOMAC Index and minimum joint space width before receiving the intra-articular injection and at 2-week intervals were compared. Twelve patients who received OA intervention were enrolled and finally a clinical evaluation of 12 knee joints and knee synovial fluid samples were analyzed. In this study, after receiving hypertonic dextrose prolotherapy, the OA patients clearly demonstrated a significant improvement in WOMAC index and increasing tendency in the medial minimum joint space width after intervention. Meanwhile, we observed a significantly associated tendency between hypertonic dextrose treatment of knee OA and the upregulation of MMP2, TIMP-1, EGF, CXCL9 and IL-22. The findings provide knee OA patients receiving hypertonic dextrose prolotherapy, which is accompained by the improvemeny of knee symptoms and associated tendency of upregulation of MMP2, EGF, CXCL 9 and IL-22.

PREVALENCE OF POTENTIAL MRI-BASED EXCLUSIONARY FINDINGS IN OSTEOARTHRITIS CLINICAL TRIALS: DATA FROM THE OSTEOARTHRITIS INITIATIVE (OAI)

PREVALENCE OF POTENTIAL MRI-BASED EXCLUSIONARY FINDINGS IN OSTEOARTHRITIS CLINICAL TRIALS: DATA FROM THE OSTEOARTHRITIS INITIATIVE (OAI)