KL Score Research Articles

MR study of longitudinal variations in proximal femur 3D morphological shape and associations with cartilage health in hip osteoarthritis

The goal of this study was to use quantitative MRI analysis to longitudinally observe the relationship between 3D proximal femur shape and hip joint degenerative changes. Forty-six subjects underwent unilateral hip MR imaging at three time points (baseline, 18 and 36 months). 3D shape analysis, hip cartilage T1ρ /T2 relaxation time quantification, and SHOMRI MRI grading were performed at each time point. Subjects were grouped based on KL, SHOMRI, and HOOS pain scores. Associations between these score groupings, time, and longitudinal variation in shape, were analyzed using a generalized estimating equation. One-way ANCOVA was conducted to evaluate change in shape as a predictor of the worsening of degenerative changes at 36 months. Our results demonstrated that subjects displayed an increase in the volume of the femoral head and neck (Mode 3) over time. This shape mode was significantly more prevalent in patients that reported pain. Longitudinal changes in this shape mode also served as borderline predictors of elevated T1ρ values (p = 0.055) and of cartilage lesions (p = 0.068). Subjects showed a change in the Femoral Neck Anteversion angle (FNA) over time (Mode 6). This shape mode showed a significant interaction with the presence of cartilage lesions. The results of this study suggest that specific variations in bone shape quantified through 3D-MRI based Statistical Shape modeling show an observable relationship with hip joint compositional and morphological changes. The shapes observed lead to early degenerative changes, which may lead into OA, thus confirming the important role of bone shape changes in the pathogenesis of OA. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.

097 Identifying novel acoustic emission biomarkers for use in knee osteoarthritis clinical trials

Background: The recent development of techniques to measure high-frequency acoustic emission (AE) from knees has opened up the possibility of identifying AE features which reflect the integrity of interactions between joint components during weight bearing movement. The objective of this study was to determine whether novel candidate biomarkers, based on AE measurements, can be identified for future use in clinical trials and stratified medicine applications for knee osteoarthritis (OA). We focused on testing the reproducibility of candidate AE biomarkers and their association with other markers, using a cohort approach. Methods: Participants with knee pain and KL scores between 1-4 were recruited from local NHS primary and secondary care organisations. AE data were collected and analysed from the worse knee, as identified by each participant, using our established sit-stand-sit movement protocol. Variation in AE measurement was analysed in 45 participants by fitting two linear mixed effects models. In addition to random effects terms for practitioners and visits, respectively, both models included a fixed effect term for the AE machines and random effects terms to capture between-participant variability and residual error. Associations with other markers were tested in 68 participants by fitting a linear mixed effects model for each candidate biomarker. The model included fixed effects for the covariates of interest, a participant-specific random effect that accounts for correlation between repeated measurements within the same individual, and a residual error term. A multiple regression model was developed using forward selection based on the likelihood ratio test with a cut-off for significance of p < 0.1. Results: Of four candidate AE biomarkers tested, AE number of hits showed the best reproducibility profile regarding variation within session, day to day, week to week, between practitioner, and between machines. AE number of hits was higher in people with KL2, 3 or 4 scores than in those with KL1. Hits occurred predominantly in two of the four pre-defined sit-stand movement quadrants. AE number of hits also showed significant associations with contralateral knee pain, and with body weight. The protocol used was feasible and acceptable to all participants and health professionals involved. Conclusion: Measurement of AE hits using a simple sit-stand-sit movement protocol offers a novel and convenient approach for assessing the integrity of interactions between joint components during weight bearing movement. AE number of hits offers a novel potential knee OA biomarker for use in large multicentre clinical trials of knee OA treatments. AE measurement may reflect a composite of knee structural changes and joint loading factors. Refinement of the method may further strengthen the utility of the AE approach for clinical trials. This approach may also have applications for monitoring knee OA in primary care.

Genetic exploration of osteoarthritis endophenotypes identifies new biological pathways in osteoarthritis

Purpose: Genetic studies can help to identify novel genes involved in OA and in that way elucidate OA etiological pathways. However to date, GWAS (genome-wide association studies) in OA have yielded only few loci, which is partly explained by the phenotypic and ethiological heterogeneity of OA. Therefore, we have stratified OA definitions into endophenotypes, which help to identify underlying disease etiology. We have focused on separate radiographic features of the OA process: radiographic measured joint space width (JSW), Joint space narrowing (JSN) and osteophytosis as proxies for the separate biological processes underlying OA pathology. Methods: Using the Rotterdam Study cohorts (RS1, RS2, RS3) as a discovery, we conducted GWAS on 30 OA endophenotypes based on radiographic measurements. We have used the following radiographic measurements to create (semi)-quantitative endophenotypes for the hip, knee, hand, finger and thumb joints: JSN, JSW, Osteophytes, and the quantitative KL score. GWAS were carried out under an additive model in RV-test using HRC v1.0 imputations, with adjustment for age, sex and the first 4 principle components. EasyQC was used to conduct quality control across cohorts (excluded: MAF<0.05). Cleaned results were combined in a joint meta-analysis using METAL. Functional assessed of the identified loci was done by examining if the identidied SNPs changed RNA expression in multiple tissues (GTEX), Pathway analysis (GO biological functions, reactome, KEGG, WIKIPathways), and to see if there were DNA interactions at the identified SNPs (3D genome browser). Results: In total we defined 30 different OA endophenotypes for the hip, knee, and hand joints in the Rotterdam Study cohorts. On average each GWAS performed has a relative small sample size of ∼8000 individuals. We have identified 94 different loci (100 SNPs) with a P<1E-6 of which 16 loci (20 SNPs) reached genome-wide significance (P<5E-8), We find 3 known (DOT1L , MGP and CCD91 ) and 14 novel loci to be genome-wide significantly associated to thumb, hand and knee OA endophenotypes. The most significant novel locus is located on chr1, associated to thumb OA endophynotypes, Knee JSN and (nominal significant) hip cartilage thickness. Within the same topological associated domain in this locus is WNT9A and WNT3A. WNT9A plays a central role in early synovial joint development, as ectopic expression of WNT9a in early differentiating chondrocytes induces joint formation. The other novel loci are located near DAB1, KCNK1-SLC25F3, KCND3-CTTNBP2NL, DCBLD2, COL25A1, FIP1L1-PDGFRA, ESR1, CCDC82-CNTN5, TLE3-UACA, MT1G, DYM, and MYPOP genes. Gene-function enrichment and pathway analysis using the 17 top loci shows enrichment for i.a. Regulation of growth (Padj = 4.21E-5), Female sex differentiation (Padj = 4.73E-5) and Skeletal development (Padj = 7.99E-3). Pathway enrichments is seen for i.a. differentiation Pathways ( Padj = 1.55E-3) and Wnt-signaling (Padj = 2.49E-2), in addition we also see an enrichment for height associated loci (Padj = 1.87E-5). In addition, we have examined all known OA loci in our endophenotype dataset and found striking patterns of endophenotype association. For example, the established GDF5 locus shows strong signals with all osteophytosis endophenotypes, but not with cartilage endophenotypes. Conclusions: We have identified 14 novel loci associated to different aspects of OA pathology. In addition we have identified another 80 loci with suggestive evidence for association (P<1E-6). Examination of known genetic OA loci showed striking patterns of association, and suggests that the GDF5 association is driven by bone formation pathways rather then cartilage driven pathways. Our findings highlight the potential of endophenotypes in OA genetic studies. Future analysis will consist of validation in other cohorts, and further functional assessment of the identified loci to gain etiological insight into the biological mechanism underlying the relationship between genetic variation and OA.

Identification of a new constitutional mutation of COMP gene associated with a case of primary osteoarthritis

Purpose: Osteoarthritis (OA) is a multifactorial disease linked to age but also to genetic and environmental factors. Twelve genes were identified in OA suffering families, however they do not explain all genetic forms. EXORHUM project aims to identify new mutations involved in genetic determinism of OA. Methods: In order to focus on the most evocative cases of hereditary forms of osteoarthritis, we defined strict inclusion criteria: early severe OA (less than 5O years), confirmed by radiography (KL score >2) without any obvious cause (obesity, trauma, dysplasia..) Results: We report here a case of an early idiopathic hip OA in a familial context. Pain began at age of 25 and diagnosis of severe and bilateral hip OA were done thereafter. The patient underwent hip arthroplasty at age of 39 and 45. We identified a missense mutation in exon 13 of Cartilage Oligomeric Matrix Protein COMP gene (c.1358A>G, p.Asn453Ser), leading to substitution of asparagine by serine in position 453, in one of thrombospondine type 3 repeats of the protein. The literature associates this mutation to multiple epiphyseal dysplasias. However, the patient does not display this phenotype unlike one of his brothers. Conclusions: We show for the first time that constitutional mutations of COMP gene are not only linked to epiphyseal dysplasia but also to primitive OA case. This study allows to extend the phenotypic spectrum of mutations of this gene and suggests that the related of patients suffering from dysplasia should benefit from suitable support in order to prevent occurrence and development of OA, even in the absence of clinical signs.

Type 2 diabetes patients have accelerated cartilage matrix degeneration compared to diabetes free controls: data from the Osteoarthritis Initiative

Osteoarthritis (OA) and diabetes mellitus (DM) share common risk factors with a potential underlying relationship between both diseases. The purpose of this study was to investigate the longitudinal effects of DM on cartilage deterioration over 24-months with MR-based T2 relaxation time measurements. From the Osteoarthritis Initiative (OAI) cohort 196 diabetics were matched in small sets for age, sex, BMI and Kellgren-Lawrence score with 196 non-diabetic controls. Knee cartilage semi-automatic segmentation was performed on 2D multi-slice multi-echo spin-echo sequences. Texture of cartilage T2 maps was obtained via grey level co-occurrence matrix analysis. Linear regression analysis was used to compare cross-sectional and changes in T2 and texture parameters between the groups. Both study groups were similar in age (63.3 vs 63.0 years, P=0.70), BMI (30.9 vs 31.2kg/m2, P=0.52), sex (female 53.6% vs 54.1%, P=0.92) and KL score distribution (P=0.97). In diabetics, except for the patella, all compartments showed a significantly higher increase in mean T2 values when compared to non-diabetic controls. Global T2 values increased almost twice as much; 1.77ms vs 0.98ms (0.79ms [CI: 0.39,1.19]) (P<0.001). Additionally, global T2 values showed a significantly higher increase in the bone layer (P=0.006), and in a separate analysis of the texture parameters, diabetics also showed consistently higher texture values (P<0.05), indicating a more disordered cartilage composition. Cartilage T2 values in diabetics show a faster increase with a consistently more heterogeneous cartilage texture composition. DM seems to be a risk factor for developing early OA with an accelerated degeneration of the articular cartilage in the knee.

Tool for osteoarthritis risk prediction (TOARP) over 8 years using baseline clinical data, X-ray, and MRI: Data from the osteoarthritis initiative.

Osteoarthritis (OA), a multifactorial disease causing joint degeneration, often leads to severe disability. The rising rates of disability highlight the need for implementing preventative measures at early stages of the disease, which would especially benefit subjects at high risk for OA development. To develop a risk prediction tool for moderate-severe OA (TOARP) over 8 years based on subject characteristics, knee radiographs, and MRI data at baseline using data from the Osteoarthritis Initiative (OAI). Retrospective. 641 subjects with no/mild radiographic OA (Kellgren-Lawrence [KL] 0-2) and no clinically significant symptoms (Western Ontario and McMaster Universities Arthritis Index [WOMAC] 0-1) were selected from the OAI. MR images were obtained using 3.0T. Compartment-specific cartilage and meniscus morphology and cartilage T2 were assessed. Baseline subject demographics, risk factors, KL score, cartilage WORMS score, presence of meniscus tear, and cartilage T2 were used to predict the development of moderate/severe OA (KL = 3-4 or WOMAC pain ≥5 or total knee replacement [TKR]) over 8 years. Best subsets variable selection followed by cross-validation were used to assess which combinations of variables best predict moderate/severe OA. Model 1 included KL score, previous knee injury in the last 12 months, age, gender, and BMI. Model 2 included all variables in Model 1 plus presence of cartilage defects in the lateral femur and patella, and presence of a meniscal tear. Model 3 included all variables in Models 1 and 2, plus cartilage T2 in the medial tibia and medial femur. Compared to Model 1 (cross-validated AUC = 0.67), Model 3 performed significantly better (AUC = 0.72, P = 0.04), while Model 2 showed a statistical trend (AUC = 0.71, P = 0.08). We established a risk calculator for the development of moderate/severe knee OA over 8 years that includes radiographic and MRI data. The inclusion of MRI-based morphological abnormalities and cartilage T2 significantly improved model performance. 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1517-1526.

Conservatively treated knee injury is associated with knee cartilage matrix degeneration measured with MRI-based T2 relaxation times: data from the osteoarthritis initiative.

To investigate the association of cartilage degeneration with previous knee injuries not undergoing surgery, determined by morphologic and quantitative 3-T magnetic resonance imaging (MRI). We performed a nested cross-sectional study of right knee MRIs from participants in the Osteoarthritis Initiative (OAI) aged 45-79 with baseline Kellgren-Lawrence score of 0-2. Cases were 142 right knees of patients with self-reported history of injury limiting the ability to walk for at least 2 days. Controls were 426 right knees without history of injury, frequency-matched to cases on age, BMI, gender, KL scores and race (1:3 ratio). Cases and controls were compared using covariate-adjusted linear regression analysis, with the outcomes of region-specific T2 mean, laminar analysis and heterogeneity measured by texture analysis to investigate early cartilage matrix abnormalities and the Whole-Organ Magnetic Resonance Imaging Score (WORMS) to investigate morphologic knee lesions. Compared to control subjects, we found significantly higher mean T2 values in the injury [lateral tibia (28.10ms vs. 29.11ms, p=0.001), medial tibia (29.70ms vs. 30.40ms, p=0.014) and global knee cartilage (32.73ms vs. 33.29ms, p=0.005)]. Injury subjects also had more heterogeneous cartilage as measured by GLCM texture contrast, variance and entropy (p<0.05 in 14 out of 18 texture parameters). WORMS gradings were not significantly different between the two groups (p>0.05). A history of knee injury not treated surgically is associated with higher and more heterogeneous T2 values, but not with morphologic knee abnormalities. Our findings suggest that significant, conservatively treated knee injuries are associated with permanent cartilage matrix abnormalities.

Degenerative disease of knee joint: a clinico-radiological correlation

Background: This study was done from January 2014 to July 2016, in 128 patients of knee joint osteoarthritis. We assessed epidemiology of osteoarthritis of knee and various MRI findings.Methods: In all the 128 patients radiographs (anteroposterior) were taken in extended and weight bearing position. Staging of osteoarthritis of knee was done using Kellgren-Lawrence scoring system and then we performed magnetic resonance imaging of the knee. All these patients were then interviewed about their clinical symptoms and osteoarthritis of knee was graded by WOMAC scale.Results: Osteoarthritis has a positive correlation with age, female sex and BMI. However occupation of the patient was not associated with any statistical significance. No association was seen between cartilage defects, bone marrow edema, sub chondral cysts, subchondral sclerosis, Baker’s cysts subluxations of tibia and synovitis with clinical features. The patellofemoral compartment of knee joint mostly contributed to the clinical symptoms of the patients in our study population though not being statistically significant (P &gt;0. 05). In tibiofemoral compartment a statistically significant correlation was seen between most of the MRI findings and KL score, however in patellofemoral compartment this correlation is poor.Conclusions: Clinical findings and plain radiographs are still important in evaluating osteoarthritis of knee, MRI plays an important role in imaging the bony and soft tissues of knee as a whole organ, thereby helping in better management and outcome of the disease. Also MRI plays an important role in depicting early changes of osteoarthtis.

Managing knee osteoarthritis in an academic primary care practice: Opportunities for improvement

s / Osteoarthritis and Cartilage 23 (2015) A82eA416 A332 Results: The OA group was significantly older, had greater BMI, KL scores and WOMAC scores compared to the asymptomatic group (Table). The OA group had significantly less MVPA, bouted MVPA, and steps per day based on accelerometer data, but self-reported more time spent doing bouted vigorous and bouted MVPA (Table). In terms of meeting guidelines, based on accelerometer data, 44.4% of asymptomatic individuals and 8.5% of those with moderate OA met physical activity guidelines ( >1⁄4150 bouted MVPA min/week), while 18.5% of asymptomatic individuals and 36% of those with moderate OA were considered inactive (no bouts of MVPA/week). Using self-reports, 74.1% of asymptomatic individuals and 89.4% of thosewithmoderate OA met physical activity guidelines, while only 3% of asymptomatic individuals and 2% of those with moderate OA were considered inactive. Conclusions: Based on objective accelerometer data, the moderate knee OA group had similar sedentary (9 hours per day) and light (4 hours per day) PA as asymptomatic individuals. Given that long sedentary bouts are particularly detrimental to health outcomes, further work is needed to determine how this timewas distributed over the day in both groups. The moderate OA group engaged in less time in MVPA and accrued fewer steps per day compared to asymptomatic individuals based on accelerometer data. Interesting, the moderate OA group selfreported greater levels of MVPA. These findings suggest PA levels are substantially overestimated using the IPAQ, particularly in individuals with moderate knee OA, questioning its value in physical activity assessment in the OA population. The accelerometer data support efforts to identify safe and effective interventions to increase MVPA in those with knee joint pathology to ensure PA benefits are achieved in the OA population. Mean (SD) group demographics and daily physical activity levels. Asymptomatic Moderate OA p-value Age (years) 54.7 (7.8) 62.3 (6.8) <0.001 BMI (kg/m) 27.6 (4.7) 31.2 (5.8) <0.001 WOMAC e Total 2.1 (5.8) 22.3 (18.5) <0.001 KL Global* 2.0 (2) 3 (2) <0.001 Accelerometer e Sedentary (mins) 573.9 (90.7) 541.1 (102.0) 0.181 Accelerometer e Light (mins) 261.6 (54.7) 278.2 (78.1) 0.103 Accelerometer e MVPA (mins) 39.9 (25.0) 21.7 (15.0) <0.001 Accelerometer e Bouted MVPA (mins) 22.4 (21.2) 7.71 (11.12) <0.001 Accelerometer e Step Counts 8357 (2993) 6518 (2426) <0.001 IPAQ e Bouted MVPA (mins) 99.5 (111.6) 171.5 (186.8) 0.01 BMIe Body Mass Index, WOMAC, KL e Kellgren Lawrence (*Mann-Whitney U Test), MVPA emoderate-vigorous physical activity, IPAQ e International Physical Activity

Limitations of Human Genetic Studies on Osteoarthritis

1 (control; mAF=15.2%) [10]. The mAF of the omitted KL=2 subgroup was 12.3%, confirming an inverse relationship between mAF of the SNP and KL scores. This clearly indicates that inclusion of the KL=2 subjects in the case group had caused a decrease in the detection power. In fact, this association was not reproduced by conventional Japanese and Chinese studies that include KL=2 in the case group [11]. Considering that prevalence of the KL=2 subgroup is shown to be fairly high in representative epidemiologic studies (17.3-41.3%; difference between KL ≥ 2 and KL ≥ 3 in Table 2), removal of this subgroup may inevitably cause a decrease in the total sample size. Generally, a lack of objective and quantitative measure for the disease definition remains a fatal limitation of clinical OA studies. The ROAD study has recently established the fully automatic program KOACAD (knee OA computer-aided diagnosis) to quantify the major OA parameters (joint space, osteophyte, etc.) on plain radiographs [8]. We believe that the KOACAD system as well as magnetic resonance image systems [12] will serve as optimal measures for the definition of OA in the near future, just as bone mineral density does in osteoporosis.

OP0145 Metabolic Syndrome, Accelerated Aging and Hand Osteoarthritis: the HIV Metafib-Oa Study

BackgroundObesity is associated with a 2-fold increase of hand osteoarthritis (HOA). However, the association with MetS or its components, independently of the weight, has never been investigated in HOA.ObjectivesSince HIV...

SAT0436 Association between Joint SPACE Width, Kellgren-Lawrence Score, Pain and Progression in Osteoarthritis Subjects from Two Phase III Studies – A Clinical Study Reference Database

BackgroundOsteoarthritis (OA) is a heterogeneous disorder, which has been described in several different population studies. However there is a significant difference between patient populations recruited in OA interventional clinical trials...

THU0211 Genetic Polymorphisms Can Predict Knee Osteoarthritis Progression. Results from the Arthrotest Multicenter Association Study

BackgroundSingle Nucleotide Polymorphisms (SNPs) are inherited genetic variations that can predispose or protect individuals against clinical events. Osteoarthritis (OA) has a multifactorial etiology with a strong genetic component. Genetic factors...

Sex related differences in mri features between two etiologically different osteoarthritis subpopulations: data from the osteoarthritis initiative

Purpose: The observed heterogeneity in osteoarthritis with respect to e.g. risk factors, symptoms, affected joints and progression, gave rise to the idea that OA is in fact a collection of distinct disease subtypes. In this study we explored whether two etiologically distinct subtypes of knee OA with equal radiological OA severity, differ in osteoarthritis features as seen on MRI. The subtypes comprised a group with metabolic syndrome and a group of lean physically active subjects. Methods: From all subjects of the Osteoarthritis Initiative (OAI) incidence subcohort, who had a KL score ≥ 2 in at least one knee at 48 months follow-up, we included two groups of 50 subjects, matched for KL score. To be included in the metabolic syndrome group subjects needed to have a BMI > 30 kg/m2 or abdominal circumference >94 cm for males or >80 cm for females. Further, 2 out of 3 of the following criteria needed to be present: hypertension (RR > 130/85 mmHg or use of hypertension medication), insulin resistance (reported high blood sugar or use of diabetic medication) or dyslipidemia (use of lipid lowering medication). Inclusion criteria for the physically active lean group were a BMI < 25 kg/m2 and a Physical activity scale for the elderly (PASE) score ≥ 2, which indicates strenuous sport/recreation activities. MRI scans made at 48 month follow-up were requested for these subjects from the OAI database, and one randomly selected OA knee from each subject was scored using the MRI Osteoarthritis Knee Score (MOAKS). Results: The metabolic syndrome group consisted of 28 females and 22 males with an average age of 63.4 years while the physically active lean group consisted of 37 females and 13 males with an average age of 61.3 years. Scores for bone marrow lesions (BMLs), and cartilage damage were consistently higher in most of the knee compartments in the metabolic syndrome group, but only for females and only significant for cartilage damage. In the lateral tibia, however, scores for BMLs and cartilage damage were lower in the metabolic syndrome group, for both sexes. Osteophyte scores were higher for all compartments in the metabolic syndrome group, irrespective of sex, though these differences were only significant for a few compartments in females (see Fig.). Scores of meniscal tears and Hoffa synovitis were significantly higher in the physically active lean group while high prepatellar signal was more often seen in the metabolic syndrome group, especially in the females. Conclusions: Metabolic OA and OA related to physical activity showed clear differences in MRI OA features, depending on sex and knee compartment. Intriguing is the difference between men and women in the pattern in which cartilage damage and BMLs are distributed over the compartments (see Fig.). This is suggestive of differences in biomechanics of the knee between the sexes, which have been shown to underlie the higher prevalence of patello-femoral problems in women. The fact that metabolic syndrome is associated with worse scores in women but not in men might be attributed to differences in fat distribution. Fat in females is deposited mostly subcutaneously, while males have more visceral fat. The subcutaneous amount of fat is related to leptin levels, and interestingly, leptin levels have been shown to influence OA, especially in women. Another interesting finding is that osteophyte scores behave differently than scores for BMLs and cartilage damage, in that the distribution over the compartments is less pronounced, and that scores are higher in the metabolic syndrome group, for both sexes. This suggests that the etiological process for osteophyte development is at least partly independent from the processes that influence cartilage damage and BMLs. In conclusion, these results suggest that different etiological processes in knee OA do lead to differences in structural degradation, which is probably modulated by biomechanical loads in the different compartments of the knee.

Prediction model for knee osteoarthritis incidence, including clinical, genetic and biochemical risk factors

ObjectiveTo develop and validate a prognostic model for incident knee osteoarthritis (KOA) in a general population and determine the value of different risk factor groups to prediction.MethodsThe prognostic model was...

OP0130 Prediction model for knee osteoarthritis including clinical, genetic and biochemical risk factors

BackgroundIdentification of subjects at high risk for knee osteoarthritis (OA) is warranted for biochemical/pharmaceutical research and for prevention/monitoring in the general practice.ObjectivesThe objective of this study was to create and...

OP0140 Circulating Carboxy-Terminal Type X Collagen Fragments (C-Col10), a Measure of Skeletal Hypertrophy, are Elevated in Patients with Osteoarthritis and Ankylosing Spondylitis

BackgroundAnkylosing Spondylitis (AS) is a chronic inflammatory disease of the spine and sacroiliac joints, whereas osteoarthritis (OA) is generally considered as a non-inflammatory condition of the synovial joints, predominantly knee...

Changes in MR relaxation times of the meniscal body with loading: an in vivo pilot study in knee osteoarthritis

Purpose: The meniscus, a fibrocartilaginous tissue found within the knee joint, is responsible for joint congruity, shock dissipation, load transmission, lubrication, and stability of the joint. The meniscus is increasingly being recognized as an important tissue in knee osteoarthritis (OA). Recent studies have shown the potential of magnetic resonance (MR) relaxation times (T1r and T2) in studying biochemical composition of meniscus and therefore they may play a role in quantifying early meniscal degeneration and injury. One central function of themenisci is load transmission and studying the effect of acute loading on the meniscal T1r and T2 values may provide insight into the development of joint degeneration. Thus the purpose of this study is to prospectively compare changes in T1r and T2 in the meniscal body with acute loading in knees with OA and with those of age-matched healthy control menisci. Methods: Female subjects (age: 40-70 years, BMI: 20-35 kg/m2) with (KL score of 2 or 3, n 1⁄420) and without (KL score of 0, n1⁄410) radiographic evidence of knee OA, were imaged on a 3T GEMR scanner using a custommade loading device. MR images (Coronal SPGR and T1r and T2 mapping sequences) were acquired with the knee flexed at 20 with and without a compressive load of 50% of the subject's bodyweight (Figure 1) using established pulse sequences. The regions of interest (ROIs) for quantifying T1r and T2 values in the meniscus body were defined on the coronal SPGR images and superimposed over relaxation time maps. Anterior and posterior horns were not evaluated due to substantial partial volume effects in coronal images. Three different zones (outer, middle, and inner) of meniscus were defined by dividing the meniscus ROIs into three different parts with each part occupying one-third the width of the meniscus (Figure 2). After adjusting for age and BMI in the general linear regression model, repeated measures ANOVAwas used to detect significant differences in T1r and T2 with and without loading. Results: The average T1r and T2 values in all zones were significantly higher in OA patients compared with controls in unloaded condition, but not in loaded condition (Figure 3 and Figure 4). ΔT1r and ΔT2 in the outer zone of the medial meniscus in controls was significantly higher than the OA subjects (14.8% vs. 6.6%, P1⁄40.046 for ΔT1r, and 15.7% vs. 5.8%, P1⁄40.027 for ΔT2). In other zones (middle and inner), the same trend was observed but did not reach significance. Pooled data showed, significant increase in T1r of the outer zone of both medial (9.1%, P<0.0001) and lateral (6.8%, P1⁄40.014) meniscus body was observed with loading. Whereas, significant increase in T2 was observed in the outer zone of the medial meniscus (8.4%, P1⁄4 0.0003) only with minimal changes in the lateral meniscus (2.6%, P1⁄40.221). Conclusions: Elevated T1r and T2 in subjects with OA in the unloaded condition agree with literature and suggest that relaxation times of the menisci may have value in monitoring early disease. Significant relaxation time elevations in the outer portion of the meniscus with acute loading in both groupsmay reflect tissue hydration changes as the inner and middle portions of the meniscus bear load. The observation that Abstracts / Osteoarthritis an

An oral preparation containing hylauronic acid (Oralvisc®) can normalize the turnover of hyaluronic acid in synovial fluid of osteoarthritic knee patients

An oral preparation containing hylauronic acid (Oralvisc®) can normalize the turnover of hyaluronic acid in synovial fluid of osteoarthritic knee patients

Prediction model for knee osteoarthritis including clinical, genetic and biochemical risk factors

Purpose: Identification of subjects at high risk for knee osteoarthritis (OA) is warranted for biochemical /pharmaceutical research and for prevention/monitoring in the general practice. It is unknown if we are able to distinguish persons who develop knee OA from those who remain free of OA. The objective of this study was to create and compare different risk prediction models including clinical, genetic and/or biochemical risk factors, for knee OA in an elderly population and assess the discriminative value of these models in 4 independent studies. Methods: The prediction model was created in the Rotterdam Study-I (474 incident knee OA cases, 2154 controls of subjects aged 55 years and over) including “questionnaire” and easily obtainable data (for example age, gender, BMI, pain and general health), x-ray data (knee baseline KL score, hand OA, hip OA) and genetic markers. The SNPs chosen to create a genetic risk score are 9 SNPs which were found consistently associated to knee OA in large-scale meta-analyses, including the GDF5, MCF2L and chr7q22 loci. Univariate and multivariate regression models were applied to assess the relationship between the risk factors and incident knee OA. Validation of the model was done in RS-II. Results: The multivariate analysis showed the strongest association(s) with gender (OR 1.69), BMI (OR per sd increase 1.28), hand OA (OR 1.45), knee pain (OR 1.62) and baseline KL score of 1 (OR 6.97). The area-under-the-curve (AUC) is a measure of discrimination between cases and controls with a range from 0.50 (tossing a coin) to 1.00 (perfect prediction). In RS-II (external validation) the AUC for gender, age and BMI in prediction for knee OA was 0.59. Addition of the questionnaire variables or questionnaire variables + genetic score did not change the AUC (AUCs of 0.61 for both models). However, when adding the knee baseline KL score of 0 or 1 to the model the AUC increased to 0.86 (full model). Similar results were observed in the Rotterdam Study-I (internal validation). For uCTXII levels similar results as for the genetic risk score were obtained in a subset of the Rotterdam Study with AUCs of 0.63 (age, gender, BMI + questionnaire), 0.64 (age, gender, BMI, questionnaire, uCTXII) and 0.85 (full model) in RS-II. Validation in Chingford, TwinsUK and the Osteoarthritis Initiative will be assessed in the near future. Conclusions: We showed that the baseline KL score for the knee is the best predictor of future knee OA, next to age, gender and BMI, in an elderly population. We would therefore recommend that radiologists report such findings to general practioners, which is currently not done regularly. “Questionnaire” variables, genetic markers, uCTXII levels and OA at other joint sites do not add much predictive value to age, gender and BMI, at least not in an elderly population.