Knee osteoarthritis (OA) is the most common musculoskeletal disorder. OA diagnosis is currently conducted by assessing symptoms and evaluating plain radiographs, but this process suffers from subjectivity. In this study, we present a new transparent computer-aided diagnosis method based on the Deep Siamese Convolutional Neural Network to automatically score knee OA severity according to the Kellgren-Lawrence grading scale. We trained our method using the data solely from the Multicenter Osteoarthritis Study and validated it on randomly selected 3,000 subjects (5,960 knees) from Osteoarthritis Initiative dataset. Our method yielded a quadratic Kappa coefficient of 0.83 and average multiclass accuracy of 66.71% compared to the annotations given by a committee of clinical experts. Here, we also report a radiological OA diagnosis area under the ROC curve of 0.93. Besides this, we present attention maps highlighting the radiological features affecting the network decision. Such information makes the decision process transparent for the practitioner, which builds better trust toward automatic methods. We believe that our model is useful for clinical decision making and for OA research; therefore, we openly release our training codes and the data set created in this study.

/pdf/automatic-knee-osteoarthritis-diagnosis-from-plain-1njnhsp9im.pdf

Automatic Knee Osteoarthritis Diagnosis from Plain Radiographs: A Deep Learning-Based Approach

Knee osteoarthritis (OA) is the most common musculoskeletal disorder. OA diagnosis is currently conducted by assessing symptoms and evaluating plain radiographs, but this process suffers from subjectivity. In this study, we present a new transparent computer-aided diagnosis method based on the Deep Siamese Convolutional Neural Network to automatically score knee OA severity according to the Kellgren-Lawrence grading scale. We trained our method using the data solely from the Multicenter Osteoarthritis Study and validated it on randomly selected 3,000 subjects (5,960 knees) from Osteoarthritis Initiative dataset. Our method yielded a quadratic Kappa coefficient of 0.83 and average multiclass accuracy of 66.71\% compared to the annotations given by a committee of clinical experts. Here, we also report a radiological OA diagnosis area under the ROC curve of 0.93. We also present attention maps -- given as a class probability distribution -- highlighting the radiological features affecting the network decision. This information makes the decision process transparent for the practitioner, which builds better trust toward automatic methods. We believe that our model is useful for clinical decision making and for OA research; therefore, we openly release our training codes and the data set created in this study.

Osteoarthritis is a debilitating disease that has increased in prevalence across the world due to the aging population. Currently, physicians use a plethora of treatment strategies to try and slow down the progression of the disease, but none have been shown to ubiquitously treat and cure the disease. One of the strategies uses the high molecular weight molecule hyaluronic acid as either an injectable or oral supplement for treatment. Hyaluronic acid (HA) is a relatively new treatment that has shown varied results through several clinical trials. It can be used as a scaffold for engineering new treatments and several new preparations have just been added to the market. A comprehensive search was conducted through several search databases according our inclusion and exclusion criteria. This review included 44 prospective clinical trial investigating the feasibility and efficacy of HA injection for knee, hip, and ankle osteoarthritis. This review will take a closer look at hyaluronic acid and its properties, as well clinical effectiveness and future options.

/pdf/recent-advances-in-hyaluronic-acid-based-therapy-for-1s5v4s8eko.pdf

Recent advances in hyaluronic acid based therapy for osteoarthritis

Objective To investigate the efficacy and safety of dietary supplements for patients with osteoarthritis. Design An intervention systematic review with random effects meta-analysis and meta-regression. Data sources MEDLINE, EMBASE, Cochrane Register of Controlled Trials, Allied and Complementary Medicine and Cumulative Index to Nursing and Allied Health Literature were searched from inception to April 2017. Study eligibility criteria Randomised controlled trials comparing oral supplements with placebo for hand, hip or knee osteoarthritis. Results Of 20 supplements investigated in 69 eligible studies, 7 (collagen hydrolysate, passion fruit peel extract, Curcuma longa extract, Boswellia serrata extract, curcumin, pycnogenol and L-carnitine) demonstrated large (effect size >0.80) and clinically important effects for pain reduction at short term. Another six (undenatured type II collagen, avocado soybean unsaponifiables, methylsulfonylmethane, diacerein, glucosamine and chondroitin) revealed statistically significant improvements on pain, but were of unclear clinical importance. Only green-lipped mussel extract and undenatured type II collagen had clinically important effects on pain at medium term. No supplements were identified with clinically important effects on pain reduction at long term. Similar results were found for physical function. Chondroitin demonstrated statistically significant, but not clinically important structural improvement (effect size −0.30, –0.42 to −0.17). There were no differences between supplements and placebo for safety outcomes, except for diacerein. The Grading of Recommendations Assessment, Development and Evaluation suggested a wide range of quality evidence from very low to high. Conclusions The overall analysis including all trials showed that supplements provided moderate and clinically meaningful treatment effects on pain and function in patients with hand, hip or knee osteoarthritis at short term, although the quality of evidence was very low. Some supplements with a limited number of studies and participants suggested large treatment effects, while widely used supplements such as glucosamine and chondroitin were either ineffective or showed small and arguably clinically unimportant treatment effects. Supplements had no clinically important effects on pain and function at medium-term and long-term follow-ups.

https://bjsm.bmj.com/content/bjsports/52/3/167.full.pdf

Dietary supplements for treating osteoarthritis: a systematic review and meta-analysis

Degenerative disorders of joints, especially osteoarthritis (OA), result in persistent pain and disability and high costs to society. Nevertheless, the molecular mechanisms of OA have not yet been fully explained. OA is characterized by destruction of cartilage and loss of extracellular matrix (ECM). It is generally agreed that there is an association between pro-inflammatory cytokines and the development of OA. There is increased expression of matrix metalloproteinase (MMP) and “a disintegrin and metalloproteinase with thrombospondin motifs” (ADAMTS). Mesenchymal stem cells (MSCs) have been explored as a new treatment for OA during the last decade. It has been suggested that paracrine secretion of trophic factors, in which exosomes have a crucial role, contributes to the mechanism of MSC-based treatment of OA. The paracrine secretion of exosomes may play a role in the repair of joint tissue as well as MSC-based treatments for other disorders. Exosomes isolated from various stem cells may contribute to tissue regeneration in the heart, limbs, skin, and other tissues. Recent studies have indicated that exosomes (or similar particles) derived from MSCs may suppress OA development. Herein, for first time, we summarize the recent findings of studies on various exosomes derived from MSCs and their effectiveness in the treatment of OA. Moreover, we highlight the likely mechanisms of actions of exosomes in OA.

/pdf/mesenchymal-stem-cell-derived-exosomes-a-new-therapeutic-1ga6qazuy2.pdf

Alba Ruiz Zamora

Papers

Socio-economic costs of osteoarthritis: A systematic review of cost-of-illness studies