Musculoskeletal

The Effects of Weight Loss on Imaging Outcomes in Osteoarthritis of the Hip or Knee in People who are Overweight or Obese: A Systematic Review

Copyright © 2019 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.
Osteoarthritis Cartilage. 2020 Jan;28(1):10-21. doi: 10.1016/j.joca.2019.10.013. Epub 2019 Nov 26.

Abstract

OBJECTIVE:
To evaluate the structural effects of weight loss on hip or knee osteoarthritis (OA) and to summarize which structural joint pathologies have been examined and the evidence for the outcome measurement instruments applied.
DESIGN:
Based on a pre-specified protocol (available: PROSPERO CRD42017065263), we conducted a systematic search of the bibliographic databases, Medline, Embase and Web of Science identifying longitudinal articles reporting the effects of weight loss on structural imaging outcomes in OA of the hip or knee in people who are overweight or obese.
RESULTS:
From 1625 potentially eligible records, 14 articles (from 6 cohorts) were included. 2 cohorts were derived from RCTs. Evaluated pathologies were: articular cartilage (n = 7), joint space width (n = 3), bone marrow lesions (n = 5), synovitis (n = 2), effusion (n = 1), meniscus (n = 3), bone marrow density (n = 1) and infrapatellar fat pad (IPFP; n = 2). Cartilage showed conflicting results when evaluating cartilage thickness by direct thickness measurements. Compositional dGEMRIC and T2 mapping measures in early knee OA showed trends towards reduced cartilage degeneration. Joint space width on conventional radiographs showed no change. Weight loss reduced the size of the IPFP. Synovitis and effusion were not affected. Following weight loss DXA showed bone loss at the hip.
CONCLUSION:
We did not find consistent evidence of the effects of weight loss on OA structural pathology in people who are overweight or obese. There is a need to achieve consensus on which structural pathologies and measurements to apply in weight loss and OA research.

Augmented Versus Artificial Intelligence for Stratification of Patients with Myositis

With interest we read the recent article by Pinal-Fernandez and Mammen,1 which comments on the paper by Spielmann et al2 and to a lesser extent on the contribution by Mariampillai et al3 4 and raises concerns about the artificial intelligence (AI)-driven approach used to define subgroups of patients with idiopathic inflammatory myopathy (IIM).

To illustrate this, Pinal-Fernandez and Mammen constructed a library of 1000 observations and selected the four variables using a multivariate normal distribution, thus finding a similar clustering as in the original paper by Spielmann et al.2 We share some of the concerns about unsupervised learning techniques raised by Pinal-Fernandez and Mammen.1 In this letter, we would like to highlight several aspects related to AI-driven methodologies.

Machine learning (ML) is a subset of AI that enables a computer to make decisions based on the large dataset. When applied to clustering, it will always give an ‘optimal’ solution for the number of clusters ‘present’ in a dataset. However, it is up to the human user’s discretion to determine whether those clusters exist. An ML algorithm determines a number of clusters by separating the datasets into the subgroups through a process of optimising (1) separation between each cluster to its greatest and (2) ensuring that within a cluster, the distance to the cluster centre for each point is the smallest. Such an algorithm is essentially trying to identify a number of optimal clusters that allow each cluster to be distinct from the others. The goal is to have tight individual clusters that are very distinguishable from the others. In any dataset, the algorithms will present an optimal solution to those or similar criteria, but it does not always mean those clusters are truly significant or meaningful.

Visualising the clusters using dimensionality reduction techniques such as principal component analysis or t-distributed stochastic neighbour embedding is vital for this process, in addition to more quantitative methods such as comparing intracluster variation, intercluster variation and silhouette scoring. That is why researchers using ML should ideally be ‘bilingual’ and understand both the mathematics and algorithms, as well the science and clinical meaning behind the results.

To conclude, we emphasise that, no doubt, ML has the potential to improve the stratification of patients with IIM if certain concepts of data science are followed as also pointed out by a task force of the European League Against Rheumatism for big data and AI.5 ML relies on large, standardised and curated datasets that require large patient cohorts. Due to the rarity of IIM, larger patient cohorts (such as the MyoNet/EuroMyositis)6 are required to generate quality data. Once larger and curated datasets are available, the ML approach is a powerful alternative to human judgement and can improve future classification criteria for IIM.4 7 8Today, we argue for the use of ML alongside expert decision, thus relying on augmented judgement when making the final decision on patient stratification especially when building AI-based models. Augmented intelligence has the potential for improved patient stratification in IIM.

A Novel Amino Acid Composition Ameliorates Short-Term Muscle Disuse Atrophy in Healthy Young Men

Skeletal muscle disuse leads to atrophy, declines in muscle function, and metabolic dysfunction that are often slow to recover. Strategies to mitigate these effects would be clinically relevant. In a double-blind randomized-controlled pilot trial, we examined the safety and tolerability as well as the atrophy mitigating effect of a novel amino acid composition (AXA2678), during single limb immobilization. Twenty healthy young men were randomly assigned (10 per group) to receive AXA2678 or an excipient- and energy-matched non-amino acid containing placebo (PL) for 28d: days 1–7, pre-immobilization; days 8–15, immobilization; and days 16–28 post-immobilization recovery. Muscle biopsies were taken on d1, d8 (immobilization start), d15 (immobilization end), and d28 (post-immobilization recovery). Magnetic resonance imaging (MRI) was utilized to assess quadriceps muscle volume (Mvol), muscle cross-sectional area (CSA), and muscle fat-fraction (FF: the fraction of muscle occupied by fat). Maximal voluntary leg isometric torque was assessed by dynamometry. Administration of AXA2678 attenuated muscle disuse atrophy compared to PL (p < 0.05) with changes from d8 to d15 in PL: ΔMvol = −2.4 ± 2.3% and ΔCSA = −3.1% ± 2.1%, both p < 0.001 vs. zero; against AXA2678: ΔMvol: −0.7 ± 1.8% and ΔCSA: −0.7 ± 2.1%, both p > 0.3 vs. zero; and p < 0.05 between treatment conditions for CSA. During immobilization, muscle FF increased in PL but not in AXA2678 (PL: 12.8 ± 6.1%, AXA2678: 0.4 ± 3.1%; p < 0.05). Immobilization resulted in similar reductions in peak leg isometric torque and change in time-to-peak (TTP) torque in both groups. Recovery (d15–d28) of peak torque and TTP torque was also not different between groups, but showed a trend for better recovery in the AXA2678 group. Thrice daily consumption of AXA2678 for 28d was found to be safe and well-tolerated. Additionally, AXA2678 attenuated atrophy, and attenuated accumulation of fat during short-term disuse. Further investigations on the administration of AXA2678 in conditions of muscle disuse are warranted.

The Role of Advanced MRI in the Development of Treat-to-Target Therapeutic Strategies, Patient Stratification and Phenotyping in Rheumatoid Arthritis

In this commentary we discuss the potential of advanced imaging, particularly Dynamic Contrast Enhanced (DCE) magnetic resonance imaging (MRI) for the objective assessment of disease progression in rheumatoid arthritis (RA). We emphasise the potential DCE-MRI in advancing the field and exploring new areas of research and development in RA. We believe that different grades of bone marrow edema (BME) and synovitis in RA can be examined and monitored in a more sensitive manner with DCE-MRI. Future treatments for RA will be significantly improved by enhanced imaging of BMEs and synovitis. DCE-MRI will also facilitate enhanced stratification and phenotyping of patients enrolled in clinical trials.

A Phase IV, Multicenter, Single-Arm, Open-Label Study to Evaluate the Impact of Apremilast on Hand and Whole-Body MRI Outcomes in Patients with Psoriatic Arthritis (MOSAIC): Rationale, Design, and Methods.

Copyright © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ
Annals of the Rheumatic Diseases. 2019 June;78(2)_suppl. doi: 10.1136/annrheumdis-2019-eular.1368

Abstract

BACKGROUND:
Phase III clinical trials have shown apremilast (APR) reduced PsA signs/symptoms and improved physical function,but no study has addressed its impact on structural disease progression. MRI is a highly sensitive, validated tool to assess inflammatory and structural changes, as it can detect soft tissue inflammation, bone marrow edema (BME) lesions, bone erosion and proliferation in peripheral joints and axial skeleton. Whole-body (WB)-MRI, a relatively novel technique in musculoskeletal studies, allows assessment of all peripheral/axial joints and entheses in 1 examination. Recent, consensus-based and semi-quantitative scoring methods were developed and validated. This study is the first to systematically use new state-of-the-art MRI scoring methodologies to assess PsA inflammatory and structural changes in a global clinical trial.

OBJECTIVES:
To assess APR efficacy on inflammatory indices and imaging outcome measures associated with PsA structural progression by conventional static MRI and dynamic contrast-enhanced (DCE)-MRI of the most affected hand and WB-MRI.

METHODS:
The study aims to enroll 120 biologic-naïve adults with PsA for ≥3 mos to ≤5 yrs and prior treatment with ≤2 conventional DMARDs. Subjects must have ≥3 swollen and ≥3 tender joints, hand involvement (≥1 swollen joint or ≥1 dactylitis) and ≥1 active enthesitis site. After 4-wk screening, all eligible patients will receive APR 30 mg twice daily (titrated during the first 5 days) as monotherapy or in combination with methotrexate for 48 wks, with a 4-wk observational follow-up. Conventional MRI and optional DCE-MRI of the most affected hand and WB-MRI of the entire body will be performed at Wks 0, 24 and 48. The primary endpoint is change from BL to Wk 24 in OMERACT PsA MRI (PsAMRIS) composite score of BME + synovitis + tenosynovitis. Other imaging endpoints include change from BL to Wk 48 in PsAMRIS composite score (BME + synovitis + tenosynovitis) and change from BL to Wks 24 and 48 in PsAMRIS composite score (BME + synovitis), PsAMRIS composite inflammation score (BME + synovitis + tenosynovitis + periarticular inflammation), PsAMRIS total damage score (erosion + bone proliferation), WB-MRI indices (including peripheral joint inflammation index and peripheral enthesis inflammation index), hip and knee inflammation MRI scores (HIMRISS, KIMRISS), OMERACT heel enthesitis MRI indices, axial inflammation indices (SPARCC, CanDen), DEMRIQ-Volume and DEMRIQ-Inflammation and other DCE-MRI–derived parameters. Clinical parameters will include SJC/TJC, cDAPSA, SPARCC Enthesitis Index, Leeds Enthesitis Index, Leeds Dactylitis Index, PASDAS, PtGA, PhGA, Patient’s Assessment of Pain, HAQ-DI, and BASDAI and impact of disease (PsAID12). Safety and tolerability also will be assessed.

RESULTS:
The study protocol was approved by an independent ethics committee and is now enrolling in the USA. Selected countries in Europe and Russia will also participate. MRI, clinical and patient-reported outcomes will be analyzed.

CONCLUSION:
This study will provide important evidence of APR’s impact on inflammatory/structural changes by assessing all PsA musculoskeletal domains (peripheral arthritis, enthesitis, dactylitis and axial disease). Furthermore, it will yield information on use of conventional MRI–, WB-MRI– and DCE-MRI–driven outcome measures in PsA clinical trials.

Less Severe Synovitis in Patients with Knee Osteoarthritis is Associated with Higher Self-Reported Pain Intensity 12 Months After Total Knee Arthroplasty- An Exploratory Cohort Study.

Copyright © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ
Annals of the Rheumatic Diseases. 2019 June;78(2)_suppl. doi: 10.1136/annrheumdis-2019-eular.5695

Abstract

BACKGROUND:
Synovitis is a pain generator in patients with osteoarthritis and associated with upregulation of pro-inflammatory cytokines, which have been found to lead to pain sensitivity and worse self-reported pain(1).

OBJECTIVES:
This study aimed to investigate the association between pre- and perioperative synovitis from imaging and histology and self-reported pain 12 months after total knee arthroplasty (TKA).

METHODS:
Preoperative synovitis was assessed from MRI data of the knee by 11 point synovitis score a.m Guermazi (2) using contrast enhanced MRI (CE-synovitis) and heuristic time intensity curve analysis of the dynamic contrast enhanced MRI (DCE-MRI) data using the DYNAMIKA® software (Image Analysis group, London) providing Dynamic Enhanced MR Quantification (DEMRIQ) Indices (3). Perioperative synovitis was also assessed from biopsies of the synovium in 6 predefined places graded histologically a.m Krenn (4). Worst pain within the last 24-hours (visual analog scale, VAS, 0-100) was assessed before and 12 months after TKA. Patients were divided into a low-pain (VAS≤30) and a high-pain (VAS>30) group based on 12-months postoperative VAS.

RESULTS:
Twenty-six patients had full pre- and postoperative data and were analysed. The high-pain group had significantly lower CE-synovitis (P=0.03), DCE-MRI inflammation indices (DEMRIQ-inflammation) (P<0.03) and a trend towards lower histologically assessed synovitis grades (P=0.077) compared to the low-pain group at baseline. Preoperative synovitis scores were also inversely correlated with pain 12-months after TKA, CE-synovitis (R = – 0.455, P = 0.022) and DCE-MRI inflammation (R = -0.528, P = 0.007), indicating that more severe preoperative synovitis is associated with less severe pain at 12-months.

CONCLUSION:
Higher preoperative synovitis scores are associated with less postoperative pain 12-months after TKA. Further, correlation analysis revealed that less severe preoperative synovitis was associated with worse pain 12-months after TKA, suggesting that CE and DCE-MRI synovitis quantification could be used as imaging markers for prediction of good surgical outcomes.

Magnetic Resonance Imaging Tenosynovitis and Osteitis are Independent Predictors of Radiographic and MRI Damage Progression in Rheumatoid Arthritis Patients In Clincial Remission

Copyright © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ
Annals of the Rheumatic Diseases. 2019 June;78(2)_suppl. doi: 10.1136/annrheumdis-2019-eular.2006

Abstract

BACKGROUND:
Progression of structural joint damage occurs in 20-30 % of patients with rheumatoid arthritis (RA) in clinical remission1. Magnetic resonance imaging (MRI)-detected synovitis and in particular osteitis/bone marrow edema (BME) are known predictors of structural progression in both active RA and in remission, but the predictive value of adding MRI tenosynovitis assessment as potential predictor in patients in clinical remission has not been investigated.

OBJECTIVES:
To investigate the predictive value of baseline MRI inflammatory and damage parameters on 2 year MRI and X-ray damage progression in an RA cohort in clinical remission, following MRI and conventional treat-to-target (T2T) strategies.

METHODS:
200 RA patients in clinical remission (DAS28-CRP<3.2 and no swollen joints) on conventional DMARDs, included in the randomized IMAGINE-RA trial2 (conventional DAS28 + MRI-guided T2T strategy targeting absence of BME vs conventional DAS28 guided T2T strategy) had baseline and 2 years contrast-enhanced MRIs of the dominant wrist and 2nd-5th MCP joints and X-rays of hands and feet performed, which were evaluated with known chronology by two experienced readers according to the OMERACT RAMRIS scoring system and Sharp/van der Heijde method, respectively.

The following potentially predictive baseline variables: MRI BME, synovitis, tenosynovitis, MRI and X-ray erosion and joint space narrowing (JSN) score, CRP, DAS28, smoking status, gender, age and patient group were tested in univariate logistic regression analyses with 2-year progression in MRI combined damage score, Total Sharp Score (TSS), and MRI and X-ray JSN and erosion scores as dependent variables. Variables with p<0.1, age, gender and patient group were included in multivariable logistic regression analyses with backward selection.

RESULTS:
Based on univariate analyses MRI BME, synovitis, tenosynovitis, x-ray erosion and JSN, gender and age were included in subsequent multivariable analyses. Independent MRI predictors of structural progression were BME (MRI progression) and tenosynovitis (MRI and X-ray progression), MRI combined damage score: sum score of MRI erosion and JSN scores.

CONCLUSION:
This trial is the first to report that MRI tenosynovitis independently predicts both X-ray and MRI damage progression in RA patients in clinical remission. Further studies are needed to confirm MRI-determined tenosynovitis as predictor of progressive joint destruction in RA clinical remission.

Effect of Liraglutide on Body Weight and Pain in Patients with Overweight and Knee Osteoarthritis: Protocol for a Randomised, Double-Blind, Placebo-Controlled, Parallel-Group, Single-Centre Trial

Copyright © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ
BMJ Open. 2019 May;9(5) doi: 10.1136/bmjopen-2018-024065

Abstract

INTRODUCTION:
With an increasing prevalence of citizens of older age and with overweight, the health issues related to knee osteoarthritis (OA) will intensify. Weight loss is considered a primary management strategy in patients with concomitant overweight and knee OA. However, there are no widely available and feasible methods to sustain weight loss in patients with overweight and knee OA. The present protocol describes a randomised controlled trial evaluating the efficacy and safety of the glucagon-like peptide-1 receptor agonist liraglutide in a 3 mg/day dosing in patients with overweight and knee OA.

METHODS AND ANALYSIS:
150 volunteer adult patients with overweight or obesity and knee OA will participate in a randomised, double-blind, placebo-controlled, parallel-group and single-centre trial. The participants will partake in a run-in diet intervention phase (week −8 to 0) including a low calorie diet and dietetic counselling. At week 0, patients will be randomised to either liraglutide 3 mg/day or liraglutide placebo 3 mg/day for 52 weeks as an add-on to dietetic guidance on re-introducing regular foods and a focus on continued motivation to engage in a healthy lifestyle. The co-primary outcomes are changes in body weight and the Knee Injury and Osteoarthritis Outcome Score pain subscale from week 0 to week 52.

ETHICS AND DISSEMINATION:
The trial has been approved by the regional ethics committee in the Capital Region of Denmark, the Danish Medicines Agency and the Danish Data Protection Agency. An external monitoring committee (The Good Clinical Practice Unit at Copenhagen University Hospitals) will oversee the trial. The results will be presented at international scientific meetings and through publications in peer-reviewed journals.