Association of subchondral bone texture on magnetic resonance imaging with radiographic knee osteoarthritis progression: data from the Osteoarthritis Initiative Bone Ancillary Study.

OBJECTIVES: To assess whether initial or 12-18-month change in magnetic resonance imaging (MRI) subchondral bone texture is predictive of radiographic knee osteoarthritis (OA) progression over 36 months. METHODS: This was a nested case-control study including 122 knees/122 participants in the Osteoarthritis Initiative (OAI) Bone Ancillary Study, who underwent MRI optimised for subchondral bone assessment at either the 30- or 36-month and 48-month OAI visits. Case knees (n = 61) had radiographic OA progression between the 36- and 72-month OAI visits, defined as ≥ 0.7 mm minimum medial tibiofemoral radiographic joint space (minJSW) loss. Control knees (n = 61) without radiographic OA progression were matched (1:1) to cases for age, sex, body mass index and initial medial minJSW. Texture analysis was performed on the medial femoral and tibial subchondral bone. We assessed the association of texture features with radiographic progression by creating a composite texture score using penalised logistic regression and calculating odds ratios. We evaluated the predictive performance of texture features for predicting radiographic progression using c-statistics. RESULTS: Initial (odds ratio [95% confidence interval] = 2.13 [1.41-3.40]) and 12- 18-month change (3.76 [2.04-7.82]) texture scores were significantly associated with radiographic OA progression. Combinations of texture features were significant predictors of radiographic progression using initial (c-statistic [95% confidence interval] = 0.65 [0.64-0.65], p = 0.003) and 12-18-month change (0.68 [0.68-0.68], p < 0.001) data. CONCLUSIONS: Initial and 12-18-month changes in MRI subchondral bone texture score were significantly associated with radiographic progression at 36 months, with better predictive performance for 12-18-month change in texture. These results suggest that texture analysis may be a useful biomarker of subchondral bone in OA. KEY POINTS: • Subchondral bone MRI texture analysis is a promising knee osteoarthritis imaging biomarker. • In this study, subchondral bone texture was associated with knee osteoarthritis progression. • This demonstrates predictive and concurrent validity of MRI subchondral bone texture analysis. • This method may be useful in clinical trials with interventions targeting bone

Evaluation of bone marrow lesion volume as a knee osteoarthritis biomarker - longitudinal relationships with pain and structural changes: data from the Osteoarthritis Initiative

Abstract Introduction Bone marrow lesion (BML) size may be an important imaging biomarker for osteoarthritis-related clinical trials and reducing BML size may be an important therapeutic goal. However, data on the interrelationships between BML size, pain, and structural progression are inconsistent and rarely examined in the same cohort. Therefore, we evaluated the cross-sectional and longitudinal associations of BML volume with knee pain and joint space narrowing (JSN). Methods A BML volume assessment was performed on magnetic resonance images of the knee collected at the 24- and 48-month Osteoarthritis Initiative visits from a convenience sample of 404 participants in the progression cohort. During the same visits, knee pain was assessed with WOMAC pain scores and knee radiographs were acquired and scored for JSN. BML volume was summed to generate a total knee volume and an index tibiofemoral compartment volume (compartment with greater baseline JSN). Primary analyses included multiple linear regressions (outcome = pain, predictor = total knee BML volume) and logistic regressions (outcome = JSN, predictor = index tibiofemoral compartment BML volume). Results This sample was 49% female with a mean age of 63 (9.2 standard deviation (SD)) years, and 71% had radiographic osteoarthritis in the study knee. Larger baseline BMLs were associated with greater baseline knee pain (P = 0.01), the presence of JSN at baseline (odds ratio (OR) = 1.50, 95% confidence interval (CI) = 1.23 to 1.83), and JSN progression (OR = 1.27, 95%CI = 1.11 to 1.46). Changes in total knee BML volume had a positive association with changes in knee pain severity (P = 0.004) and this association may be driven by knees that were progressing from no or small baseline BMLs to larger BMLs. In contrast, we found no linear positive relationship between BML volume change and JSN progression. Instead, regression of medial tibiofemoral BML volume was associated with JSN progression compared to knees with no or minimal changes in BML volume (OR = 3.36, 95%CI = 1.55 to 7.28). However, follow-up analyses indicated that the association between JSN progression and BML volume change may primarily be influenced by baseline BML volume. Conclusion Large baseline BMLs are associated with greater baseline knee pain, the presence of JSN at baseline, and disease progression. Additionally, BML regression is associated with decreased knee pain but not a reduced risk of concurrent JSN progression

Barriers and facilitators to the adoption and implementation of evidence-based injury prevention training programmes: a narrative review

While there is a multitude of evidence supporting the efficacy of injury prevention training programmes, the literature investigating the implementation of these programmes is, in contrast, rather limited. This narrative review sought to describe the commonly reported barriers and facilitators of the implementation of injury prevention training programmes among athletes in organised sport. We also aimed to identify necessary steps to promote the uptake and sustainable use of these programmes in non-elite athletic communities. We identified 24 publications that discussed implementing evidence-based injury prevention training programmes. Frequently reported barriers to implementation include the perceived time and financial cost of the programme, coaches lacking confidence in their ability to implement it, and the programme including exercises that were difficult or confusing to follow. Frequently reported facilitators to implementation include the coach being aware of programme efficacy, shared motivation to complete the programme from both coaches and athletes, and the ability to easily integrate the programme into practice schedules. The current literature is focused on high-income, high-resource settings. We recommend that future studies focus on understanding the best practices of programme dissemination in culturally and economically diverse regions. Programmes ought to be of no financial burden to the user, be simply adaptable to different sports and individual athletes and be available for use in easily accessible forms, such as in a mobile smartphone application

Classification of patients with knee osteoarthritis in clinical phenotypes: data from the osteoarthritis initiative

<div><p>Objectives</p><p>The existence of phenotypes has been hypothesized to explain the large heterogeneity characterizing the knee osteoarthritis. In a previous systematic review of the literature, six main phenotypes were identified: Minimal Joint Disease (MJD), Malaligned Biomechanical (MB), Chronic Pain (CP), Inflammatory (I), Metabolic Syndrome (MS) and Bone and Cartilage Metabolism (BCM). The purpose of this study was to classify a sample of individuals with knee osteoarthritis (KOA) into pre-defined groups characterized by specific variables that can be linked to different disease mechanisms, and compare these phenotypes for demographic and health outcomes.</p><p>Methods</p><p>599 patients were selected from the OAI database FNIH at 24 months’ time to conduct the study. For each phenotype, cut offs of key variables were identified matching the results from previous studies in the field and the data available for the sample. The selection process consisted of 3 steps. At the end of each step, the subjects classified were excluded from the further classification stages. Patients meeting the criteria for more than one phenotype were classified separately into a ‘complex KOA’ group.</p><p>Results</p><p>Phenotype allocation (including complex KOA) was successful for 84% of cases with an overlap of 20%. Disease duration was shorter in the MJD while the CP phenotype included a larger number of Women (81%). A significant effect of phenotypes on WOMAC pain (F = 16.736 p <0.001) and WOMAC physical function (F = 14.676, p < 0.001) was identified after controlling for disease duration.</p><p>Conclusion</p><p>This study signifies the feasibility of a classification of KOA subjects in distinct phenotypes based on subgroup-specific characteristics.</p></div

Composite quantitative knee structure metrics predict the development of accelerated knee osteoarthritis:data from the osteoarthritis initiative

BACKGROUND: We aimed to determine if composite structural measures of knee osteoarthritis (KOA) progression on magnetic resonance (MR) imaging can predict the radiographic onset of accelerated knee osteoarthritis. METHODS: We used data from a nested case-control study among participants from the Osteoarthritis Initiative without radiographic KOA at baseline. Participants were separated into three groups based on radiographic disease progression over 4 years: 1) accelerated (Kellgren-Lawrence grades [KL] 0/1 to 3/4), 2) typical (increase in KL, excluding accelerated osteoarthritis), or 3) no KOA (no change in KL). We assessed tibiofemoral cartilage damage (four regions: medial/lateral tibia/femur), bone marrow lesion (BML) volume (four regions: medial/lateral tibia/femur), and whole knee effusion-synovitis volume on 3 T MR images with semi-automated programs. We calculated two MR-based composite scores. Cumulative damage was the sum of standardized cartilage damage. Disease activity was the sum of standardized volumes of effusion-synovitis and BMLs. We focused on annual images from 2 years before to 2 years after radiographic onset (or a matched time for those without knee osteoarthritis). To determine between group differences in the composite metrics at all time points, we used generalized linear mixed models with group (3 levels) and time (up to 5 levels). For our prognostic analysis, we used multinomial logistic regression models to determine if one-year worsening in each composite metric change associated with future accelerated knee osteoarthritis (odds ratios [OR] based on units of 1 standard deviation of change). RESULTS: Prior to disease onset, the accelerated KOA group had greater average disease activity compared to the typical and no KOA groups and this persisted up to 2 years after disease onset. During a pre-radiographic disease period, the odds of developing accelerated KOA were greater in people with worsening disease activity [versus typical KOA OR (95% confidence interval [CI]): 1.58 (1.08 to 2.33); versus no KOA: 2.39 (1.55 to 3.71)] or cumulative damage [versus typical KOA: 1.69 (1.14 to 2.51); versus no KOA: 2.11 (1.41 to 3.16)]. CONCLUSIONS: MR-based disease activity and cumulative damage metrics may be prognostic markers to help identify people at risk for accelerated onset and progression of knee osteoarthritis

Early pre-radiographic structural pathology precedes the onset of accelerated knee osteoarthritis.

BACKGROUND: Accelerated knee osteoarthritis (AKOA) is characterized by more pain, impaired physical function, and greater likelihood to receive a joint replacement compared to individuals who develop the typical gradual onset of disease. Prognostic tools are needed to determine which structural pathologies precede the development of AKOA compared to individuals without AKOA. Therefore, the purpose of this manuscript was to determine which pre-radiographic structural features precede the development of AKOA. METHODS: The sample comprised participants in the Osteoarthritis Initiative (OAI) who had at least one radiographically normal knee at baseline (Kellgren-Lawrence [KL] grade  3) and No AKOA. The index visit was the study visit when participants met criteria for AKOA or a matched timepoint for those who did not develop AKOA. Magnetic resonance (MR) images were assessed for 12 structural features at the OAI baseline, and 1 and 2 years prior to the index visit. Separate logistic regression models (i.e. OAI baseline, 1 and 2 years prior) were used to determine which pre-radiographic structural features were more likely to antedate the development of AKOA compared to individuals not developing AKOA. RESULTS: At the OAI baseline visit, degenerative cruciate ligaments (Odds Ratio [OR] = 2.2, 95% Confidence Interval [CI] = 1.3,3.5), infrapatellar fat pad signal intensity alteration (OR = 2.0, 95%CI = 1.2,3.2), medial/lateral meniscal pathology (OR = 2.1/2.4, 95%CI = 1.3,3.4/1.5,3.8), and greater quantitative knee effusion-synovitis (OR = 2.2, 95%CI = 1.4,3.4) were more likely to antedate the development of AKOA when compared to those that did not develop AKOA. These results were similar at one and two years prior to disease onset. Additionally, medial meniscus extrusion at one year prior to disease onset (OR = 3.5, 95%CI = 2.1,6.0) increased the likelihood of developing AKOA. CONCLUSIONS: Early ligamentous degeneration, effusion/synovitis, and meniscal pathology precede the onset of AKOA and may be prognostic biomarkers

Bone marrow lesion volume reduction is not associated with improvement of other periarticular bone measures: data from the Osteoarthritis Initiative

Abstract Introduction We evaluated the associations between bone marrow lesion (BML) volume change and changes in periarticular bone mineral density (paBMD) as well as subchondral sclerosis to determine whether BML change is associated with other local bone changes. Methods The convenience sample comprised participants in the Osteoarthritis Initiative (OAI) with weight-bearing posterior-anterior knee radiographs and magnetic resonance images (MRIs) at the 24- and 48-month visits and dual-energy x-ray absorptiometry (DXA) at the 30-/36-month and 48-month visits. The right knee was assessed unless contraindicated for MRI. We used knee DXA scans to measure medial tibia paBMD and medial/lateral paBMD ratio (M:L paBMD). Knee radiographs were scored for sclerosis (grades 0 to 3) in the medial tibia. Two raters determined BML volume on sagittal fat-suppressed MRI by using a semiautomated segmentation method. To focus on knees with only medial tibia BML changes, knees with lateral tibial BMLs were excluded. Medial tibial BML volume change was classified into three groups: BML regression (lowest quartile of medial tibial BML volume change), no-to-minimal change (middle two quartiles), and BML progression (highest quartile). We used proportional odds logistic regression models to evaluate the association between quartiles of changes in medial paBMD or M:L paBMD ratio, as outcomes, and BML volume change. Results The sample (n = 308) included 163 (53%) female subjects, 212 (69%) knees with radiographic osteoarthritis, and participants with a mean age of 63.8 ± 9.3 years and mean body mass index of 29.8 ± 4.7 kg/m2. We found an association between greater increases in medial tibia paBMD and BML regression (OR = 1.7 (95% confidence interval (CI) = 1.1 to 2.8)) and a similar trend for BML progression (OR = 1.6 (95% CI = 1.0 to 2.6]). We also detected associations between greater increase in M:L paBMD and BML regression (OR = 1.6 (95% CI = 1.0 to 2.7]) and BML progression (OR = 1.8 (95% CI = 1.1 to 3.0)), although BML regression had borderline statistical significance. The frequency of sclerosis progression in the medial tibia (n = 14) was greater among knees with BML progression or regression compared with knees without BML change (P = 0.01 and P = 0.04, respectively). Conclusion BML regression and BML progression are characterized by concurrent increases in paBMD and sclerosis, which are characteristic of increased radiographic osteoarthritis severity. At least during 24 months, BML regression is not representative of improvement in other periarticular bone measures

Bearings in Hip Arthroplasty:Joint Registries vs Precision Medicine: Review Article

Background: Precision medicine has been adopted in a range of clinical settings where omics data have led to greater characterisation of disease and stratification of patients into subcategories of phenotypes and pathologies. However, in orthopaedics, precision medicine lags behind other disciplines such as cancer. Joint registries have now amassed a huge body of data pertaining to implant performance which can be broken down into performance statistics for different material types in different cohorts of patients. The National Joint Registry of England, Wales and Northern Ireland (NJR) is now one of the largest datasets available. Other registries such as those from Sweden and Australia however contain longer follow-up. Together, these registries can provide a wealth of informative for the orthopaedics community when considering which implant to give to any particular patient. Questions/Purposes: We aim to explore the benefits of combining multiple large data streams including joint registries, published data on osteoarthritis (OA) pathogenesis and pathology and data concerning performance of each implant material combination in terms of biocompatibility. We believe that this analysis will provide a comprehensive overview of implant performance hopefully aiding surgeons in making more informed choices about which implant should be used in which patient. Methods: Data from three joint registries were combined with established literature to highlight the heterogeneity of OA disease and the different clinical outcomes following arthroplasty with a range of material types. Results: This review confirms that joint registries are unable to consider differences in arthritis presentation or underlying drivers of pathology. OA is now recognised to present with varying pathology with differing morbidity in different patient populations. Equally, just as OA is a heterogeneous disease, there are disparate responses to wear debris from different material combinations used in joint replacement surgery. This has been highlighted by recent high-profile scrutiny of early failure of metal-on-metal total hip replacement (THR) implants. Conclusions: Bringing together data from joint registries, biomarker analysis, phenotyping of OA patients and knowledge of how different patients respond to implant debris will lead to a truly personalised approach to treating OA patients, ensuring that the correct implant is given to the correct patient at the correct time