Andrew Barr

A systematic review of the relationship between subchondral bone features, pain and structural pathology in peripheral joint osteoarthritis

IntroductionBone is an integral part of the osteoarthritis (OA) process. We conducted a systematic literature review in order to understand the relationship between non-conventional radiographic imaging of subchondral bone, pain, structural pathology and joint replacement in peripheral joint OA.MethodsA search of the Medline, EMBASE and Cochrane library databases was performed for original articles reporting association between non-conventional radiographic imaging-assessed subchondral bone pathologies and joint replacement, pain or structural progression in knee, hip, hand, ankle and foot OA. Each association was qualitatively characterised by a synthesis of the data from each analysis based upon study design, adequacy of covariate adjustment and quality scoring.ResultsIn total 2456 abstracts were screened and 139 papers were included (70 cross-sectional, 71 longitudinal analyses; 116 knee, 15 hip, six hand, two ankle and involved 113 MRI, eight DXA, four CT, eight scintigraphic and eight 2D shape analyses). BMLs, osteophytes and bone shape were independently associated with structural progression or joint replacement. BMLs and bone shape were independently associated with longitudinal change in pain and incident frequent knee pain respectively.ConclusionSubchondral bone features have independent associations with structural progression, pain and joint replacement in peripheral OA in the hip and hand but especially in the knee. For peripheral OA sites other than the knee, there are fewer associations and independent associations of bone pathologies with these important OA outcomes which may reflect fewer studies; for example the foot and ankle were poorly studied. Subchondral OA bone appears to be a relevant therapeutic target.Systematic reviewPROSPERO registration number: CRD 42013005009

The relationship between clinical characteristics, radiographic osteoarthritis and 3D bone area: data from the Osteoarthritis Initiative

Summary Background Radiographic measures of osteoarthritis (OA) are based upon two dimensional projection images. Active appearance modelling (AAM) of knee magnetic resonance imaging (MRI) enables accurate, 3D quantification of joint structures in large cohorts. This cross-sectional study explored the relationship between clinical characteristics, radiographic measures of OA and 3D bone area (tAB). Methods Clinical data and baseline paired radiographic and MRI data, from the medial compartment of one knee of 2588 participants were obtained from the NIH Osteoarthritis Initiative (OAI). The medial femur (MF) and tibia (MT) tAB were calculated using AAM. ‘OA-attributable’ tAB (OA-tAB) was calculated using data from regression models of tAB of knees without OA. Associations between OA-tAB and radiographic measures of OA were investigated using linear regression. Results In univariable analyses, height, weight, and age in female knees without OA explained 43.1%, 32.1% and 0.1% of the MF tAB variance individually and 54.4% when included simultaneously in a multivariable model. Joint space width (JSW), osteophytes and sclerosis explained just 5.3%, 14.9% and 10.1% of the variance of MF OA-tAB individually and 17.4% when combined. Kellgren Lawrence (KL) grade explained approximately 20% of MF OA-tAB individually. Similar results were seen for MT OA-tAB. Conclusion Height explained the majority of variance in tAB, confirming an allometric relationship between body and joint size. Radiographic measures of OA, derived from a single radiographic projection, accounted for only a small amount of variation in 3D knee OA-tAB. The additional structural information provided by 3D bone area may explain the lack of a substantive relationship with these radiographic OA measures.

The relationship between three-dimensional knee MRI bone shape and total knee replacement—a case control study: data from the Osteoarthritis Initiative

Objective. There is growing understanding of the importance of bone in OA. Our aim was to determine the relationship between 3D MRI bone shape and total knee replacement (TKR). Methods. A nested case-control study within the Osteoarthritis Initiative cohort identified case knees with confirmed TKR for OA and controls that were matched using propensity scores. Active appearance modelling quantification of the bone shape of all knee bones identified vectors between knees having or not having OA. Vectors were scaled such that −1 and +1 represented the mean non-OA and mean OA shapes. Results. Compared to controls (n = 310), TKR cases (n = 310) had a more positive mean baseline 3D bone shape vector, indicating more advanced structural OA, for the femur [mean 0.98 vs −0.11; difference (95% CI) 1.10 (0.88, 1.31)], tibia [mean 0.86 vs −0.07; difference (95% CI) 0.94 (0.72, 1.16)] and patella [mean 0.95 vs 0.03; difference (95% CI) 0.92 (0.65, 1.20)]. Odds ratios (95% CI) for TKR per normalized unit of 3D bone shape vector for the femur, tibia and patella were: 1.85 (1.59, 2.16), 1.64 (1.42, 1.89) and 1.36 (1.22, 1.50), respectively, all P < 0.001. After including Kellgren–Lawrence grade in a multivariable analysis, only the femur 3D shape vector remained significantly associated with TKR [odds ratio 1.24 (1.02, 1.51)]. Conclusion. 3D bone shape was associated with the endpoint of this study, TKR, with femoral shape being most associated. This study contributes to the validation of quantitative MRI bone biomarkers for OA structure-modification trials.

OP0297 Three-Dimensional Magnetic Resonance Imaging Knee Bone Shape Predicts Total Knee Replacement: Data from the Osteoarthritis Initiative

Background MRI provides more accurate image biomarkers of structural progression than conventional radiography. Active appearance modelling (AAM) enables accurate, 3D quantification of MRIs. Changes in 3D subchondral bone shape are integral to structural progression of knee osteoarthritis (OA) and are predictive of incident radiographic knee OA. However, the association of 3D subchondral bone shape with total knee replacement (TKR) is unknown. Objectives To determine the relationship between scalar 3D bone shape and TKR. Methods This is a nested case-control analysis, within the osteoarthritis initiative (OAI) cohort. Case knees that underwent TKR were matched 1:1 with controls that “survived” the 6 years of follow up, using stratification (propensity) score matching based upon baseline age, gender, BMI category (<24.9, 25-34.9, >35), ipsilateral knee pain severity numeric rating scale, knee side and recruiting centre. Active appearance modelling of the femur, tibia and patella and linear discriminant analyses identified vectors that were best at classifying knees as having OA vs. no OA, scaled such that -1 and +1 represented the mean non-OA and mean OA shapes, respectively. Vector values were compared within matched case-control pairs using paired t-tests and the odds of TKR associated with baseline 3D bone shape were obtained using conditional logistic regression. Results Case-control pairs (n=311) of knees were well matched in terms of propensity scores. In cases of TKR the mean baseline 3D bone shape vector was more positive relative to controls, indicating more advanced OA, for the femur [mean 0.98 vs. -0.16; difference (95% CI) 1.14 (0.92,1.37)], tibia [mean 0.86 vs. -0.05; difference (95% CI) 0.90 (0.69,1.12)] and patella [mean 0.95 vs. -0.07; difference (95% CI) 1.02 (0.74,1.31)]. Unadjusted conditional odds ratios (95% CI) for the femur, tibia and patella revealed increased odds of TKR with increasingly positive 3D bone shape vector values (increasing OA structural severity) (Table 1). After adjusting for Kellgren Lawrence (KL) grade in a multivariable analysis, the femur 3D shape vector was independently associated with TKR [OR 1.21 (1.01, 1.45)] with a slight improvement in model fit (AIC) compared with KL grade.Table 1. Associations between 3D bone shape vectors or KL grade with TKR Imaging variable Univariable (unadjusted) Multivariable* OR 95% CI p value AIC OR 95% CI AIC Femur vector 1.79 1.54, 2.09 <0.001 309.51 1.21 1.01, 1.45 228.33 Tibia vector 1.64 1.42, 1.90 <0.001 334.86 1.02 0.84, 1.24 232.66 Patella vector 1.40 1.26, 1.56 <0.001 346.33 1.09 0.95, 1.26 231.24 KL grade (ref=KL zero)  1 2.42 0.75, 7.82 0.14  2 9.08 3.36,24.49 <0.001  3 31.55 11.23,88.63 <0.001  4 72.77 22.62,234.07 <0.001 230.70 * Adjusted for KL grade. Conclusions 3D bone shape predicts TKR. Femur shape has the greatest association with TKR. This provides evidence of predictive validity of 3D bone shape and its potential utility in trials of prospective disease modifying OA drugs. Disclosure of Interest None declared

The relationship between two different measures of osteoarthritis bone pathology, bone marrow lesions and 3D bone shape: data from the Osteoarthritis Initiative

Summary Objective Bone shape and bone marrow lesions (BMLs) represent different features of Magnetic resonance imaging (MRI)-detected subchondral pathology in osteoarthritis (OA). The aim of this study was to determine how these features are related and how they change in OA progression. Methods 600 participants from the Osteoarthritis Initiative (OAI) FNIH Biomarkers Initiative were included, having Kellgren–Lawrence grade 1–3, at baseline and MRI data at baseline and 24 months. The associations between 3D quantitative bone shape vectors and presence of (MRI Osteoarthritis Knee Score) MOAKS semi-quantitative BMLs (total BML size ≥1) were analysed for femurs and tibias using linear regression. Responsiveness over 24 months was calculated for both features in four pre-defined progression groups and reported as standardised response means (SRMs). Multilevel models investigated the longitudinal relationship between change in BML size and change in bone shape. Results Mean age was 61.5, 59% female and mean body mass index (BMI) 30.7. Correlation between baseline femur vector and BML was r = 0.28, P < 0.001. The presence of BMLs was associated with higher bone shape vector; coefficient (95% CI) 0.75 (0.54, 0.96) and 0.57 (0.38, 0.77) for femur and tibia respectively, both P < 0.001. After covariate adjustment, only the femur remained significant [coefficient 0.49, (95% CI 0.30, 0.68)]. Longitudinally bone vector demonstrated more responsiveness to change than BMLs (SRM 0.89 vs 0.13) while multilevel models revealed that increase in BML size was related to a more positive bone shape vector (representing worsening OA). Conclusion There is a relationship between bone shape and BMLs, with prevalence of BMLs associated with increasing OA bone shape. Bone shape demonstrated greater responsiveness than semi-quantitative BMLs.

What imaging detected pathologies are associated with shoulder symptoms and their persistence? A systematic literature review

Shoulder symptoms are common, and imaging is being increasingly used to help with management. However, the relationship between imaging and symptoms remains unclear. This review aims to understand the relationship between imaging‐detected pathologies, symptoms, and their persistence.

A5.01 The relationship between total knee replacement and 3D MRI knee bone shape: Data from the osteoarthritis initiative

Background and objectives Imaging biomarkers of osteoarthritis (OA) structural progression are more accurate when derived from MRI than conventional radiography. Accurate 3D quantification of MRIs is achieved using active appearance modelling (AAM). Subchondral bone shape changes are integral to OA structural progression and are predictive of incident radiographic knee OA. We aimed to determine the relationship between scalar 3D bone shape and total knee replacement (TKR). Materials and methods This case-control analysis, nested within the osteoarthritis initiative (OAI) cohort, matched 1:1 control knees that “survived” 6 years of follow up with case knees undergoing TKR, using stratification (propensity) score matching based upon baseline age, BMI, gender, knee side, ipsilateral knee pain severity and recruiting centre. AAM of the patella, tibia and femur were used to identify vectors that best classified knees as having OA vs. no OA, scaled such that -1 and +1 represented the mean non-OA and mean OA shapes, respectively. Within matched case-control pairs, the vector values were compared using paired t-tests and using conditional logistic regression, the odds of TKR per unit of 3D bone shape were obtained. Results Case-control pairs (n = 311) of knees were well matched based upon propensity scores. Amongst the 311 well matched pairs, mean baseline 3D bone shape vector of TKR cases was more positive (more advanced OA) relative to controls, for the femur [mean 0.98 vs. -0.16; difference (95% CI) 1.14 (0.92, 1.37)], tibia [mean 0.86 vs. -0.05; difference (95% CI) 0.90 (0.69, 1.12)] and patella [mean 0.95 vs. -0.07; difference (95% CI) 1.02 (0.74, 1.31)]. Unadjusted conditional odds ratios (95% CI) for the femur, tibia and patella revealed increased odds of TKR with increasingly positive 3D bone shape vector values (increasing OA structural severity). After Kellgren Lawrence (KL) grade adjustment in a multivariable analysis, femoral 3D shape vector was independently associated with TKR [OR 1.21 (1.01, 1.45)] with an improvement in model fit (AIC) compared with KL grade. Conclusions 3D bone shape is associated with TKR. Femur shape has the greatest association with TKR. This provides evidence of predictive validity of 3D bone shape and its potential utility in trials of prospective disease modifying OA drugs.

THU0452 The Relationship Between 3D MRI Knee Bone Shape and Prevalent and Incident Knee Pain: Data from the Osteoarthritis Initiative

Background Incident frequent knee symptoms may represent early knee OA. MRI-detected OA bone pathology is associated with prevalent frequent knee OA symptoms (PFKS) and incident frequent knee OA symptoms (IFKS) in pre-radiographic knee OA. Active appearance modelling (AAM) enables accurate, 3D quantification of MRIs. Changes in 3D subchondral bone shape derived from AAMs are predictive of incident radiographic knee OA. However, the association of 3D subchondral bone shape with onset of knee symptoms is unknown. Objectives To determine the relationship between scalar 3D bone shape and PFKS and IFKS in individuals at increased risk of knee OA. Methods AAMs of the femur, tibia and patella and linear discriminant analysis identified vectors best classifying knees having OA vs. no OA. Vectors were scaled such that -1 and +1 represented the mean non-OA and mean OA shapes, respectively. Using a subcohort of 1114 persons with Kellgren Lawrence (KL) zero in both knees at the 12 month visit from the osteoarthritis initiative (OAI) we assessed whether 3D bone shape vector was associated with PFKS or IFKS. We defined PFKS as (pain, aching or stiffness) or medication use for knee symptoms most days of 1 month in the past 12 months. IFKS was defined as those lacking PFKS at baseline but reporting PFKS at any two consecutive annual OAI visits between the 12 and 60-month visits. Logistic regression, using one knee per individual, was used to evaluate the association between 3D bone shape vectors of the femur, tibia and patella and each of PFKS at the 12 month visit and IFKS. All models were adjusted for age, sex, BMI, previous knee injury and previous surgery. Results The 3D bone shape vectors of the femur, tibia and patella were not associated with PFKS in the univariable models at the 12 month visit. Adjusted odds ratios (95% CI) for the femur, tibia and patella were; 1.00 (0.71, 1.26), 1.12 (0.90, 1.41), 0.84 (0.66, 1.08) respectively, all p>0.05. The 3D bone shape vector was significantly associated with IFKS in the univariable model for the tibia only. The 3D bone shape vectors of the femur, tibia and patella were not associated with IFKS after adjustment for covariates (Table 1). However BMI, previous knee surgery and knee injury were significantly associated with PFKS and IFKS. Table 1. The association between 3D bone vector measures at the 12 month visit and risk of incident frequent knee symptoms by the 60-month visit Variable Univariable Multivariable¶ OR 95% CI p value OR 95%CI Femur 0.91 0.66, 1.26 0.58 0.88 0.58,1.33§ Tibia 1.42 1.04,1.95 0.03* 1.35 0.98,1.88§ Patella 0.95 0.68,1.31 0.75 1.02 0.71,1.47§¶ Adjusted for Age, BMI, gender, previous surgery, previous injury.* Ttibia significantly associated in univariable model.§ BMI, previous injury and previous surgery significant. Conclusions 3D bone shape is not associated with prevalent or incident frequent knee pain in individuals without radiographic OA but at increased risk of knee OA. Disclosure of Interest None declared

Osteoarthritis: recent advances in diagnosis and management: DRUG REVIEW

Osteoarthritis represents a failure of joint tissue repair and can be diagnosed accurately by symptoms and clinical findings. Our Drug review discusses diagnosis and management, including holistic assessment and pharmacological and nonpharmacological treatment, followed by sources of further information and an analysis of the prescription data.Osteoarthritis represents a failure of joint tissue repair and can be diagnosed accurately by symptoms and clinical findings. Our Drug review discusses diagnosis and management, including holistic assessment and pharmacological and nonpharmacological treatment, followed by sources of further information and an analysis of the prescription data.

Osteoarthritis: recent advances in diagnosis and management.

Osteoarthritis represents a failure of joint tissue repair and can be diagnosed accurately by symptoms and clinical findings. Our Drug review discusses diagnosis and management, including holistic assessment and pharmacological and nonpharmacological treatment, followed by sources of further information and an analysis of the prescription data.Osteoarthritis represents a failure of joint tissue repair and can be diagnosed accurately by symptoms and clinical findings. Our Drug review discusses diagnosis and management, including holistic assessment and pharmacological and nonpharmacological treatment, followed by sources of further information and an analysis of the prescription data.