Progression Of Joint Space Narrowing Research Articles

The mediating role of synovitis in meniscus pathology and knee osteoarthritis radiographic progression

Meniscus pathologies (damage, extrusion) and synovitis are associated with knee osteoarthritis (KOA); however, whether synovitis mediates the relationship between meniscus pathologies and KOA radiographic progression remains unclear. We conducted an observational study in the Osteoarthritis Initiative (OAI) cohort, with a 48-month follow-up. Meniscus pathology and synovitis were measured by MRI osteoarthritis knee score (MOAKS) at baseline and 24 months, and a comprehensive synovitis score was calculated using effusion and Hoffa synovitis scores. The knee osteoarthritis radiographic progression was considered that Kellgren–Lawrence (KL) grade and joint space narrowing (JSN) grade at 48 months were increased compared to those at baseline. This study included a total of 589 participants, with KL grades mainly being KL1 (26.5%), KL2 (34.1%), and KL3 (30.2%) at baseline, while JSN grades were mostly 0 at baseline. A logistic regression model was used to analyze the relationship between meniscus pathology, synovitis, and KOA progression. Mediation analysis was used to evaluate the mediation effect of synovitis. The average age of the participants was 61 years old, 62% of which were female. The medial meniscus extrusion was longitudinally correlated with the progression of KL (odds ratio [OR]: 2.271, 95% confidence interval [CI]: 1.412–3.694) and medial JSN (OR: 3.211, 95% CI: 2.040–5.054). Additionally, the longitudinal correlation between medial meniscus damage and progression of KOA (OR: 1.853, 95% CI: 1.177–2.941) and medial JSN (OR: 1.655, 95% CI: 1.053–2.602) was significant. Synovitis was found to mediate the relationship between medial meniscus extrusion and KL and medial JSN progression at baseline (β: 0.029, 95% CI: 0.010–0.053; β: 0.022, 95% CI: 0.005–0.046) and beyond 24 months (β: 0.039, 95% CI: 0.016–0.068; β: 0.047, 95% CI: 0.020–0.078). However, we did not find evidence of synovitis mediating the relationship between meniscal damage and KOA progression. Synovitis mediates the relationship between medial meniscus extrusion (rather than meniscus damage) and KOA progression.

Subtle Radiographic Progression at Six Months Can Be Detected Using Automated Quantitative Software in Rheumatoid Arthritis While Receiving Tocilizumab.

We investigated whether our in-house software equipped with partial image phase-only correlation (PIPOC) can detect subtle radiographic joint space narrowing (JSN) progression at six months and predict JSN progression in rheumatoid arthritis (RA) patients receiving Tocilizumab. The study included 39 RA patients who were treated with Tocilizumab. Radiological progression of the metacarpophalangeal and the proximal interphalangeal joints was evaluated according to the Genant-modified Sharp score (GSS) at 0, 6, and 12 months. Automatic measurements were performed with the software. We validated the software in terms of accuracy in detecting the JSN progression. The success rate of the software for joint space width (JSW) measurement was 96.8% (449/464). The 0-12-month JSW change by the software was significantly greater in joints with the 0-6-month PIPOC (+) group than the 0-6-month PIPOC (-) group (p < 0.001). The 0-12-month JSW change by the software was 0-12-month GSS (+) than with 0-12-month GSS (-) (p = 0.02). Here, "(+)" indicates the JSN progression during the follow-up period. Meanwhile, "(-)" indicates no JSN progression during the follow-up period. Linear regression tests showed significant correlations between the 0-6-month and the 0-12-month PIPOC in the left 2nd and 3rd MCP joints (R2 = 0.554 and 0.420, respectively). Our in-house software equipped with PIPOC could predict subsequent JSN progression with only short-term observations.

Severity and progression of structural hand OA is not associated with progression of structural knee OA: The IMI-APPROACH cohort

ObjectiveTo investigate whether structural hand OA or its progression is associated with structural knee OA progression after two years in a population with symptomatic knee OA. MethodsWe used baseline and two-year follow-up data from the IMI-APPROACH cohort. Symptomatic hand and knee OA were defined using ACR criteria. Radiographs of hands and knees were scored semi-quantitatively for osteophytes and joint space narrowing (JSN) following the OARSI atlas, and Kellgren-Lawrence (KL) scale. Knee images were also scored quantitatively with the Knee Image Digital Analysis (KIDA). Progression was defined as change above the minimal detectable change on patient level, except for KIDA (most affected knee compartment level). With logistic regression analyses the severity or progression of hand OA was associated with knee OA progression. ResultsIn 221 participants (mean age 66, 77% women, mean BMI 27.7, 19% hand OA), OA progression occurred in 18%–28%, and 9%–38% in hands and knees respectively, depending on features. Baseline structural hand OA features were not significantly associated with knee OA progression, except for hand osteophytes with KIDA osteophytes progression (odds ratio (OR) 1.03, 95% confidence interval (CI) 1.01–1.06). Progression of structural hand OA features was not significantly associated with knee OA progression, except for hand osteophyte or JSN progression, which was significantly associated with knee osteophyte progression (OR 0.44, 95%CI 0.22–0.84 and OR 0.43, 95%CI 0.18–0.94, respectively), and hand osteophyte progression for knee JSN (OR 2.51, 95%CI 1.15–5.48). ConclusionsIn patients with symptomatic knee OA, no consistent associations between baseline structural hand OA or hand OA progression and knee OA progression were shown.

Corrections to "A Sub-Pixel Accurate Quantification of Joint Space Narrowing Progression in Rheumatoid Arthritis".

Presents corrections to the article "A Sub-Pixel Accurate Quantification of Joint Space Narrowing Progression in Rheumatoid Arthritis".

A deep registration method for accurate quantification of joint space narrowing progression in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that leads to progressive articular destruction and severe disability. Joint space narrowing (JSN) has been regarded as an important indicator for RA progression and has received significant attention. Radiology plays a crucial role in the diagnosis and monitoring of RA through the assessment of joint space. A new framework for monitoring joint space by quantifying joint space narrowing (JSN) progression through image registration in radiographic images has emerged as a promising research direction. This framework offers the advantage of high accuracy; however, challenges still exist in reducing mismatches and improving reliability. In this work, we utilize a deep intra-subject rigid registration network to automatically quantify JSN progression in the early stages of RA. In our experiments, the mean-square error of the Euclidean distance between the moving and fixed images was 0.0031, the standard deviation was 0.0661 mm and the mismatching rate was 0.48%. Our method achieves sub-pixel level accuracy, surpassing manual measurements significantly. The proposed method is robust to noise, rotation and scaling of joints. Moreover, it provides misalignment visualization, which can assist radiologists and rheumatologists in assessing the reliability of quantification, exhibiting potential for future clinical applications. As a result, we are optimistic that our proposed method will make a significant contribution to the automatic quantification of JSN progression in RA. Code is available at https://github.com/pokeblow/Deep-Registration-QJSN-Finger.git.

The effect of interactions between BMI and sustained depressive symptoms on knee osteoarthritis over 4 years: data from the osteoarthritis initiative

BackgroundTo assess the compound effects of BMI and sustained depressive symptoms on changes in knee structure, cartilage composition, and knee pain over 4 years using statistical interaction analyses.MethodsOne thousand eight hundred forty-four individuals from the Osteoarthritis Initiative Database were analyzed at baseline and 4-year follow-up. Individuals were categorized according to their BMI and presence of depressive symptoms (based on the Center for Epidemiological Studies Depression Scale (threshold≥16)) at baseline and 4-year follow-up. 3 T MRI was used to quantify knee cartilage T2 over 4 years, while radiographs were used to assess joint space narrowing (JSN). Mixed effects models examined the effect of BMI-depressive symptoms interactions on outcomes of cartilage T2, JSN, and knee pain over 4-years.ResultsThe BMI-depressive symptoms interaction was significantly associated with knee pain (p < 0.001) changes over 4 years, but not with changes in cartilage T2 (p = 0.27). In women, the BMI-depressive symptoms interaction was significantly associated with JSN (p = 0.01). In a group-based analysis, participants with obesity and depression had significantly greater 4-year changes in knee pain (coeff.(obesity + depression vs. no_obesity + no_depression) = 4.09, 95%CI = 3.60–4.58, p < 0.001), JSN (coeff. = 0.60, 95%CI = 0.44–0.77, p < 0.001), and cartilage T2 (coeff. = 1.09, 95%CI = 0.68–1.49, p < 0.001) than participants without depression and normal BMI.ConclusionsThe compound effects of obesity and depression have greater impact on knee pain and JSN progression compared to what would be expected based on their individual effects.

A Sub-Pixel Accurate Quantification of Joint Space Narrowing Progression in Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune disease that primarily affects peripheral synovial joints, like fingers, wrists and feet. Radiology plays a critical role in the diagnosis and monitoring of RA. Limited by the current spatial resolution of radiographic imaging, joint space narrowing (JSN) progression of RA for the same reason above can be less than one pixel per year with universal spatial resolution. Insensitive monitoring of JSN can hinder the radiologist/rheumatologist from making a proper and timely clinical judgment. In this paper, we propose a novel and sensitive method that we call partial image phase-only correlation which aims to automatically quantify JSN progression in the early RA. The majority of the current literature utilizes the mean error, root-mean-square deviation and standard deviation to report the accuracy at pixel level. Our work measures JSN progression between a baseline and its follow-up finger joint images by using the phase spectrum in the frequency domain. Using this study, the mean error can be reduced to 0.0130 mm when applied to phantom radiographs with ground truth, and 0.0519 mm standard deviation for clinical radiography. With the sub-pixel accuracy far beyond usual manual measurements, we are optimistic that the proposed work is a promising scheme for automatically quantifying JSN progression.

Fully automatic software for detecting radiographic joint space narrowing progression in rheumatoid arthritis: phantom study and comparison with visual assessment.

We have developed an in-house software equipped with partial image phase-only correlation (PIPOC) which can automatically quantify radiographic joint space narrowing (JSN) progression. The purpose of this study was to evaluate the software in phantom and clinical assessments. In the phantom assessment, the software's performance on radiographic images was compared to the joint space width (JSW) difference using a micrometer as ground truth. A phantom simulating a finger joint was scanned underwater. In the clinical assessment, 15 RA patients were included. The software measured the radiological progression of the finger joints between baseline and the 52nd week. The cases were also evaluated with the Genant-modified Sharp score (GSS), a conventional visual scoring method. We also quantitatively assessed these joints' synovial vascularity (SV) on power Doppler ultrasonography (0, 8, 20 and 52weeks). In the phantom assessment, the PIPOC software could detect changes in JSN with a smallest detectable difference of 0.044mm at 0.1mm intervals. In the clinical assessment, the JSW change of the joints with GSS progression detected by the software was significantly greater than those without GSS progression (p = 0.004). The JSW change of joints with positive SV at baseline was significantly higher than those with negative SV (p = 0.024). Our in-house software equipped with PIPOC can automatically and quantitatively detect slight radiographic changes of JSW in clinically inactive RA patients.

Increased lesion depth, higher body mass index and older age are risk factors for osteoarthritis during long-term follow-up in patients with osteochondritis dissecans of the knee

IntroductionTo report on the long-term prognosis of osteochondritis dissecans (OCD) patients regarding radiological and patient-reported outcomes and to analyze possible risk factors.Materials and methodsAll patients diagnosed with knee OCD between 2004 and 2014 with radiographic Kellgren–Lawrence (K–L) grades 0–2 at the time of diagnoses, ability to understand the language of the interview, and willingness to participate in the study were retrospectively reviewed. Current knee radiographs and the Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaire were prospectively collected between May 2020 and March 2021. The extent of osteoarthritis (OA) and KOOS questionnaire results were evaluated.Results90 patients (103 knees) with a mean age of 21 years (range 6–60) were included. The mean follow-up time was 12 years (range 7–20). 24 knees (23%) were treated conservatively, and 79 knees (77%) operatively. At the time of diagnoses, 90% of the patients had K–L grades of 0–1; during the follow-up period, 45% of the patients showed radiological progression of OA. Patient body mass index (BMI) (p = 0.004; 95% CI 0.25–0.29), age (p = 0.003; 95% CI 0.18–0.30), operative treatment (p = 0.0075; 95% CI 0.41–0.65) and lesion depth (p = 0.0007) were statistically significantly connected to K–L grade change. Patients with no progression in joint space narrowing had statistically significantly better overall KOOS scores (p = 0.03; 95% CI 0.77–0.88) than patients whose K–L grades worsened.ConclusionsDuring the long-term follow-up of 12 years, patients with knee OCD had good clinical results. Lac of radiological progression of cartilage degeneration was noted in 55% of the patients, regardless of treatment method. Lesion depth, higher BMI and older age were associated with the progression of OA. The progression of OA was related to a worsening of functional scores.Level of evidenceIV.

AB1330 AUTOMATIC SUBPIXEL MEASUREMENT OF RADIOGRAPHIC FINGER JOINT SPACE NARROWING IN RHEUMATOID ARTHRITIS PATIENTS UNDER TOCILIZUMAB TREATMENT

BackgroundThe conventional scoring methods of radiographic joint space narrowing (JSN) in rheumatoid arthritis (RA) such as the Genant-modified Sharp score (GSS) are widely accepted but include subjective and time-consuming nature1. Therefore, we have developed an in-house software equipped with partial image phase-only correlation (PIPOC)2 which can automatically quantify joint space width (JSW) change.ObjectivesThe purpose of this study was to investigate whether the in-house software can predict the inhibitory effect of tocilizumab on joint destruction in a short period of time.MethodsThe study included 39 RA patients (35 female) who were treated with tocilizumab (Table 1). Radiological progression of the metacarpophalangeal and the proximal interphalangeal joints was evaluated according to the GSS at 0, 6, and 12 months. Automatic measurement was performed by the in-house software (Figure 1). We then validated in-house software in terms of accuracy in detecting the JSN.Figure 1.The algorithm flow of in-house software equipped with PIPOCTable 1.Clinical characteristics of RA patientsvariablebaseline6 months12 monthsTotal number of patients39Sex, female/male35/4Rheumatoid factor status, positive/negative29/10Age, mean (SD) years61.5 (14.6)Duration of disease, mean (SD) months111.4 (85.0)Swollen joint count, mean (SD)6.0 (4.7)3.5 (3.5)2.9 (4.0)Tender joint count, mean (SD)6.4 (3.5)2.9 (2.2)1.9 (2.0)DAS28-ESR, mean (SD)4.9 (1.2)3.0 (1.1)2.6 (1.0)DAS28-CRP, mean (SD)4.4 (1.1)3.0 (0.9)2.6 (0.8)RA, rheumatoid arthritis; SD, standard deviation; DAS28, disease activity score with 28 joints; ESR, erythrocyte sedimentation rate; CRP, C-reactive proteinResultsTo ensure homogeneity of the subjects, we targeted the joints with GSS = 0 at baseline in the software analysis. The success rate of the in-house software for JSW measurement was 96.8% (449/464). Here, the GSS (+)/PIPOC (+) were defined as joints with JSN progression according to the GSS and the software analysis, respectively. Otherwise, joints were defined as the GSS (-)/PIPOC (-) namely non-progressive JSN. The 0–12-month GSS with the 0–6-month GSS (+) group was significantly more JSN progression than the 0–6-month GSS (-) group (Mann-Whitney U test, p &lt; 0.001). Similarly, the 0–12-month PIPOC with the 0–6-month PIPOC (+) group was significantly more JSN progression than the 0–6-month PIPOC (-) group (p &lt; 0.001). The 0–12-month JSW change of finger joints with the 0–12-month GSS (+) detected by the in-house software was significantly greater than the 0–12-month GSS (-) (p = 0.02).ConclusionOur in-house software equipped with PIPOC might be able to predict the subsequent joint destruction with 6 months observations.

Diagnosis for early stage knee osteoarthritis: probability stratification, internal and external validation; data from the CHECK and OAI cohorts

ObjectiveTo internally and externally validate our diagnostic criteria of early stage knee osteoarthritis (OA) in the CHECK and OAI cohorts. DesignWe applied two previously developed diagnostic models to all knees in CHECK and OAI cohorts to calculate probabilities of early stage knee OA at baseline. Knees were categorized into three groups based on probability: ‘no OA’ (probability ≤ 30%), ‘uncertain’ (probability between 30% and 70%) and ‘early stage OA’ (probability ≥ 70%). To validate the diagnosis, we obtained OA related outcome measures at 10-year follow-up in the CHECK cohort, and at 8-9-year follow-up in the OAI cohort. We compared outcome measures between ‘no OA’ and ‘early stage OA’ knees, and between ‘no OA’ and ‘uncertain’ knees using generalized estimating equations. ResultsIn CHECK (n = 1042 knees) both models showed ‘early stage OA’ knees presented with significant and clinically relevant higher WOMAC scores, higher Kellgren & Lawrence (KL) grade, and higher rates of joint space narrowing (JSN) progression after 10 years, compared to ‘no OA’ knees. In OAI (n = 2937 knees) both models showed ‘early stage OA’ knees presented with significant and clinically relevant higher WOMAC scores, higher KL grade, and higher rates of KL and JSN progression after 8-9 years, compared to ‘no OA’ knees. Smaller, but still significant differences between ‘uncertain’ and ‘no OA’ knees were observed in both cohorts. ConclusionsThese results support internal and external validity of the two sets of diagnostic criteria for early stage knee OA.

3-D JOINT SPACE WIDTH FROM WEIGHT BEARING COMPUTED TOMOGRAPHY IS BETTER THAN 2-D RADIOGRAPHIC MEASURES AT PREDICTING FUTURE LATERAL JOINT SPACE NARROWING AT THE KNEE: A MULTICENTER OSTEOARTHRITIS STUDY INVESTIGATION

3-D joint space width (JSW) measured from weight bearing CT (WBCT) has been suggested to be more sensitive than radiographic 2-D measurement in detecting joint space narrowing (JSN), but its diagnostic value in osteoarthritis is yet to be established. To determine the predictive validity of 3-D JSW measurement from baseline WBCT compared to 2-D radiographic measures in identifying structural disease progression at the knee. WBCT knee imaging was acquired at the 144-month visit of the Multicenter Osteoarthritis Study (MOST) with radiographic Kellgren and Lawrence grade (KLG), medial and lateral tibiofemoral radiographic OARSI JSN grades. Progression in medial and lateral JSN grade was recorded 2 years subsequent. After semi-automatic segmentation of 663 available knees, joint space mapping was performed to create 3-D JSW maps. A template was registered to each individual joint surface, a 3-D statistical shape model created, and JSW measurements transferred to the template. A statistical parametric mapping (SPM) general linear model adjusted for age, sex, BMI, and the first 5 shape modes (controlling for effects of systematic misregistration) was used to test the dependence of baseline 3-D JSW on baseline medial and lateral JSN in turn. One knee per participant was included in the SPM model, when required selecting side according to worst baseline compartmental JSN grade or randomly if equal. Mean JSW values from significantly narrower SPM ROIs were taken for all knees and used in receiver operating characteristic analysis to deliver areas under the curve (AUC) in a leave-one-out cross-validation classifier predictive model for future worsening of medial and lateral JSN at 2 years. This prediction model also tested baseline KLG, medial and lateral JSN grade. All predictive models were controlled by inclusion of age, sex, and BMI and compared against each other. 10 knees did not have radiographic grading, so the study set consisted of 653 knees from 394 individuals. 218 participants were female, mean ± SD age was 63.5 ± 9.6 years, mass 82.7 ± 17.7 kg, height 170 ± 9 cm, and BMI 28. 5 ± 5.0 kg/m 2 . SPM revealed regions of significantly narrower baseline medial JSW up to ∼0.75 mm per increment in medial JSN grade (unmasked medial compartment red zone in fig. 1) and narrower baseline lateral JSW up to ∼1 mm per increment in baseline lateral JSN grade (unmasked lateral compartment red zone in fig. 2). Mean medial and lateral ROI JSW values were taken at all available knees for predictive modelling. AUC values with 95% confidence limits showed that baseline mean medial ROI JSW (0.68, 0.61-0.74) was worse than baseline KLG (0.75, 0.68-0.81) and no better than medial JSN (0.73, 0.65-0.79) or lateral JSN (0.66, 0.6-0.71) in predicting future medial JSN. However, baseline mean lateral ROI JSW (0.84, 0.72-0.91) was better than medial JSN (0.61, 0.49-0.72) and lateral JSN (0.71, 0.54-0.86) in prediction of future lateral JSN. It was also better than baseline KLG (0.77, 0.76-0.86) but not outside the 95% confidence limits, however combining baseline lateral ROI JSW and KLG in the model further improved the AUC (0.87, 0.78-0.92) beyond the limits for just KLG (0.77, 0.76-0.86). Baseline 3-D lateral compartment JSW from WBCT is better than 2-D radiographic measures at predicting progression in lateral compartment JSN, but the same was not seen for medial JSN. This suggests an important role for 3-D weight bearing JSW in assessment of knee osteoarthritis according to disease phenotype. National Institutes of Health, University of Kansas (R01AR071648), University of Iowa (U01AG18832) and University of California-San Francisco (U01AG19069). NS is a consultant for Integra BioLife, Trice Medical and Pacira Biosciences. The authors would like to thank participants and staff of the MOST study. CORRESPONDENCE ADDRESS: tom@turmezei.com

Identification of most important features based on a fuzzy ensemble technique: Evaluation on joint space narrowing progression in knee osteoarthritis patients

ObjectiveFeature selection (FS) is a crucial and at the same time challenging processing step that aims to reduce the dimensionality of complex classification or regression problems. Various techniques have been proposed in the literature to address this challenge with emphasis to medical applications. However, each one of the existing FS algorithms come with its own advantages and disadvantages introducing a certain level of bias. Materials and MethodsTo avoid bias and alleviate the defectiveness of single feature selection results, an ensemble FS methodology is proposed in this paper that aggregates the results of several FS algorithms (filter, wrapper and embedded ones). Fuzzy logic is employed to combine multiple feature importance scores thus leading to a more robust selection of informative features. The proposed fuzzy ensemble FS methodology was applied on the problem of knee osteoarthritis (KOA) prediction with special emphasis on the progression of joint space narrowing (JSN). The proposed FS methodology was integrated into an end-to-end machine learning pipeline and a thorough experimental evaluation was conducted using data from the Osteoarthritis Initiative (OAI) database. Several classifiers were investigated for their suitability in the task of JSN prediction and the best performing model was then post-hoc analyzed by using the SHAP method. ResultsThe results showed that the proposed method presented a better and more stable performance in contrast to other competitive feature selection methods, leading to an average accuracy of 78.14% using XG Boost at 31 selected features. The post-hoc explainability highlighted the important features that contribute to the classification of patients with JSN progression. ConclusionsThe proposed fuzzy feature selection approach improves the performance of the predictive models by selecting a small optimal subset of features compared to popular feature selection methods.

Association between Patellofemoral and medial Tibiofemoral compartment osteoarthritis progression: exploring the effect of body weight using longitudinal data from osteoarthritis initiative (OAI).

To investigate the associations of medial and lateral patellofemoral osteoarthritis (PF-OA) at baseline with symptomatic and radiographic OA outcomes in the medial tibiofemoral compartment (MTFC) over 4years, according to baseline overweight status. Data and MRI images of 600 subjects in the FNIH-OA biomarkers consortium were used. Symptomatic worsening and radiographic progression of MTFC-OA were defined using Western Ontario and McMaster Universities Arthritis Index (WOMAC) pain scores and MTFC joint space narrowing (JSN) from baseline to 4-year follow-up. Baseline MRIs were read to establish PF-OA diagnosis. The association between baseline regional PF-OA pattern and odds for MTFC-OA progression was evaluated using regression models (adjusted for relevant confounding covariates including body mass index (BMI), age, sex, PF alignment measurements, KL grade, and knee alignment). To evaluate the effect modifying role for overweight status, stratification analysis was performed (BMI ≥ 25 vs. < 25kg/m2). At baseline, 340 (56.7%), 255 (42.5%), and 199 (33.2%) subjects had OA in the medial, lateral, and both PF compartments. Baseline medial PF-OA was associated with WOMAC pain score and MTFC JSN progression at 4years (Adjusted OR:1.56[95%CI:1.09-2.23] and 1.59[1.11-2.28], respectively) but not lateral PF-OA. In stratification analysis, overweight status was found to be an effect modifier for medial PF-OA and WOMAC pain (OR in overweight vs. non-overweight subjects:1.65[1.13-2.42] vs. 0.50[0.12-1.82]) as well as MTFC-JSN progression (1.63[1.12-2.4] vs. 0.75[0.19-2.81]). In addition to the known confounding effect of BMI for PF-OA and MTFC-OA, the overweight status may also play an effect modifier role in the association between baseline medial PF-OA and MTFC-OA progression, which is amenable to secondary prevention.

Meta-analysis on the association between knee extensor strength and structural changes of knee osteoarthritis.

This study aimed to perform a meta-analysis to evaluate whether knee extensor (KE) strength weakness was associated with increased structural worsening in knee osteoarthritis (KOA) including joint space narrowing (JSN) and cartilage loss. PubMed, Embase, Scopus, ScienceDirect, Web of Science, and Cochrane library were searched from their inception to May 2020, to identify eligible studies. Odds ratios (ORs) accompanied by 95% confidence intervals (CIs) were calculated for the relationship between KE strength and outcomes. Totally eleven longitudinal studies were included. The pooled crude OR indicated no significant association between KE strength weakness and KOA progression of JSN (OR: 1.13, 95% CI: 0.90, 1.42), and this result duplicated after confounders were adjusted (OR: 1.10, 95% CI: 0.87, 1.39). Subgroup analysis showed the association remained non-significant in sex-specific outcomes and subsets of neutral and malaligned knees, but there was a trend toward increased risk of JSN progression in female knees with low strength (OR: 1.24, 95% CI: 0.87, 1.76, I2 = 82%). The pooled crude OR showed that KE strength weakness was associated with increased risk of cartilage loss (OR:1.43, 95% CI: 1.05, 1.95). After adjustment, we found a non-significant trend that low KE strength could increase the risk of cartilage loss (OR: 1.25, 95% CI: 0.95, 1.64), and this trend was separately observed in tibiofemoral or patellofemoral compartments. This meta-analysis suggested that KE strength weakness was not significantly associated with an increased risk of radiographic structural KOA progression in patients with KOA or known risk factors for KOA. However, there was a trend that women with weaker KE strength displayed a higher risk of JSN worsening and that KE strength weakness had an association with an increased risk of cartilage damage. Key points • Knee extensor strength weakness is not significantly associated with an increased risk of radiographic structural KOA progression in patients with or at risk of knee osteoarthritis. • There is a non-significant trend toward an increased risk of JSN progression in female knees with low knee extensor strength. • There is a trend that low KE strength can increase the risk of cartilage loss no matter in tibiofemoral or patellofemoral compartments, but it's not significant.

Prediction of Joint Space Narrowing Progression in Knee Osteoarthritis Patients.

Osteoarthritis is a joint disease that commonly occurs in the knee (KOA). The continuous increase in medical data regarding KOA has triggered researchers to incorporate artificial intelligence analytics for KOA prognosis or treatment. In this study, two approaches are presented to predict the progression of knee joint space narrowing (JSN) in each knee and in both knees combined. A machine learning approach is proposed with the use of multidisciplinary data from the osteoarthritis initiative database. The proposed methodology employs: (i) A clustering process to identify groups of people with progressing and non-progressing JSN; (ii) a robust feature selection (FS) process consisting of filter, wrapper, and embedded techniques that identifies the most informative risk factors; (iii) a decision making process based on the evaluation and comparison of various classification algorithms towards the selection and development of the final predictive model for JSN; and (iv) post-hoc interpretation of the features’ impact on the best performing model. The results showed that bounding the JSN progression of both knees can result to more robust prediction models with a higher accuracy (83.3%) and with fewer risk factors (29) compared to the right knee (77.7%, 88 risk factors) and the left knee (78.3%, 164 risk factors), separately.

Meniscal Deficiency Period and High Body Mass Index Are Preoperative Risk Factors for Joint Space Narrowing After Meniscal Allograft Transplantation

Background: Several studies have reported further reduction in joint space width (JSW) after meniscal allograft transplantation; some contributing postoperative factors are known, although preoperative factors remain unclear. This study is the first to analyze the preoperative risk factors for reduced JSW in patients after lateral meniscal allograft transplantation (LMAT). Hypothesis: Poor cartilage status and high preoperative body mass index (BMI) influence the postoperative progression of joint space narrowing. Study Design: Case-control study; Level of evidence, 3. Methods: We retrospectively studied 79 patients after LMAT who were observed for at least 5 years. JSWs on weightbearing flexion posteroanterior radiographs were measured preoperatively and at the 5-year mark. Differences in JSW were divided into more progression and less progression groups. The modified Outerbridge cartilage grades based on magnetic resonance imaging assessments were compared at subtotal/total meniscectomy and at LMAT to determine the difference between time points. Preoperative between-group differences in sex, age, surgical side, follow-up period, weight, height, BMI, and meniscal deficiency period were analyzed. Clinical outcomes were evaluated using the Lysholm score. Data were examined using univariate and multivariate logistic regressions. Results: Radiographically, the overall change in JSW from preoperative to follow-up was 0.58 mm (range, –0.23 to 1.83 mm). Reductions in JSW in the more progression and less progression groups were 0.94 ± 0.32 and 0.22 ± 0.21 mm (mean ± SD), respectively. There was no difference in cartilage status between the groups at meniscectomy or LMAT; however, changes between time points were significant on the lateral femoral condyle and lateral tibial plateau. Clinically, there were significant differences in weight, BMI, and meniscal deficiency period between the 2 groups. Postoperative Lysholm scores increased as compared with the preoperative scores, but there was no difference among the postoperative time points. In the univariate logistic regression risk analysis, weight, BMI, meniscal deficiency period, and the difference in cartilage status between time points for the lateral femoral condyle and lateral tibial plateau were identified as significant. In the subsequent multivariate logistic regression, BMI (odds ratio, 1.45; P = .016) and meniscal deficiency period (odds ratio, 1.21; P = .037) were the statistically significant factors. Conclusion: BMI and meniscal deficiency period were preoperative risk factors for JSW narrowing after LMAT. This suggests that the meniscal deficiency period from meniscectomy to LMAT may be shortened and that proper weight management can lead to successful LMAT.

Predictors of radiographic erosion and joint space narrowing progression in patients with early rheumatoid arthritis: a cohort study

BackgroundRadiographic damage in rheumatoid arthritis (RA) includes erosions and joint space narrowing (JSN). Different mechanisms may underlie their development. The objective of this study was to evaluate predictors of these entities separately.MethodsConsecutive early RA patients (symptom duration ≤12 months) from a defined area (Malmö, Sweden) recruited during 1995–2005 were investigated. Radiographs of hands and feet were scored by a trained reader according to the modified Sharp-van der Heijde score. Fat mass and lean mass distribution were measured at baseline using dual energy x-ray absorptiometry. Potential predictors of erosion and JSN progression from inclusion to the 5-year follow-up were evaluated.ResultsTwo hundred and thirty-three patients were included. Radiographs at baseline and 5 years were available for 162 patients. The median (interquartile) progression of erosion and JSN scores were 4 (0–8) and 8 (1–16), respectively. Rheumatoid factor (RF) was a robust significant predictor of both erosion and JSN score progression. In adjusted analyses, anti-CCP antibodies predicted erosions while the erythrocyte sedimentation rate was predictive of both outcomes. Smoking and high baseline disease activity (DAS28 > 5.1) predicted progression of erosions. Baseline erosion score was associated with progression of both erosion and JSN progression, while baseline JSN score was predictive only of the progression of JSN. Overweight/obesity (BMI ≥ 25 kg/m2) was a significant negative predictor of JSN score progression (β = − 0.14, p = 0.018, adjusted for RF, age, baseline JSN score) also when additionally adjusting for ever smoking (p = 0.041). Among female patients, this effect was observed in those of estimated post-menopausal age (> 51 years), but not in younger women. The truncal to peripheral fat ratio was associated with less JSN score progression in women, but not in men.ConclusionsOverweight RA patients had less JSN progression, independent of smoking status. This effect was seen in particular among older women (mainly post-menopausal), but not younger. Truncal fat was associated with less JSN progression in female patients. Smoking predicted erosion progression, and erosions may precede JSN. BMI and fat distribution may influence cartilage damage in early RA and might be related to hormonal factors.

Validation of Fully Automatic Quantitative Software for Finger Joint Space Narrowing Progression for Rheumatoid Arthritis Patients.

In rheumatoid arthritis (RA), the radiographic progression of joint space narrowing (JSN) is evaluated using visual assessments. However, those methods are complicated and time-consuming. We developed an automatic system that can detect joint locations and compute the joint space difference index (JSDI), which was defined as the chronological change in JSN between two radiographs. The purpose of this study was to establish the validity of the software that automatically evaluates the temporal change of JSN. This study consisted of 39 patients with RA. All patients were treated with tocilizumab and underwent hand radiography (left and right hand separately) at 0, 6, and 12 months. The JSN was evaluated using mTSS (modified Total Sharp Score) by one musculoskeletal radiologist as well as our automatic system. Software measurement showed that JSDI between 0 and 12 months was significantly higher than that between 0 and 6 months (p < 0.01). While, there was no significant difference in mTSS between 0, 6, and 12 months. The group with higher disease activity at 0 months had significantly higher JSDI between 0 and 6 months than that with lower disease activity (p = 0.02). The automatic software can evaluate JSN progression of RA patients in the finger joint on X-ray.

Predictors of joint damage progression and stringent remission in patients with established rheumatoid arthritis in clinical remission.

To study if clinical, radiographic and MRI markers can predict MRI and radiographic damage progression and achievement of stringent remission in patients with established RA in clinical remission followed by a targeted treatment strategy. RA patients (DAS28-CRP <3.2, no swollen joints) receiving conventional synthetic DMARDs were randomized to conventional or MRI-targeted treat-to-target strategies with predefined algorithmic treatment escalations. Potentially predictive baseline variables were tested in multivariate logistic regression analyses. In the 171 patients included, baseline MRI osteitis independently predicted progression in MRI erosion [odds ratio (OR) 1.13 (95% CI 1.06, 1.22)], joint space narrowing [OR 1.15 (95% CI 1.07, 1.24)] and combined damage [OR 1.23 (95% CI 1.13, 1.37)], while tenosynovitis independently predicted MRI erosion progression [OR 1.13 (95% CI 1.03, 1.25)]. A predictor of radiographic erosion progression was age, while gender predicted progression in joint space narrowing. Following an MRI treat-to-target strategy predicted stringent remission across all remission definitions: Clinical Disease Activity Index remission OR 2.94 (95% CI 1.25, 7.52), Simplified Disease Activity Index remission OR 2.50 (95% CI 1.01, 6.66), ACR/EULAR Boolean remission OR 5.47 (95% CI 2.33, 14.13). Similarly, low tender joint count and low patient visual analogue scale pain and global independently predicted achievement of more stringent remission. Baseline MRI osteitis and tenosynovitis were independent predictors of 2 year MRI damage progression in RA patients in clinical remission, while independent predictors of radiographic damage progression were age and gender. Following an MRI treat-to-target strategy, low scores of patient-reported outcomes and low tender joint count predicted achievement of stringent remission. ClinicalTrials.gov (https://clinicaltrials.gov), NCT01656278.