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A parallel double blinded randomized controlled clinical trial (RCT) with a 1:1:1 allocation will be conducted in an orthopedic clinic in Cairo and Giza Governments - Egypt.
This RCT will evaluate the pain reduction, self-reported functional improvement, physical functional and anatomical improvement following the application of phonophoresis using chitosan-nanoparticles gel, ECSW therapy and traditional exercises compared to each other.
The treatment period will last for 4 weeks with a total of (12 sessions/ 3 sessions per week for the application of phonophoresis using chitosan-nanoparticles gel and traditional exercises program) and (5 sessions/ 1 every week for the application of ECSWT). The participants will be assessed at two different time-points (before-after treatment) with a sample size of 40 patients in each group (3 groups)
Full description
Osteoarthritis (OA) is a common degenerative disease that is ranked as the 10th largest contributor to disabilities that has a link to higher comorbidity and excess mortality. One of most common degenerative diseases is knee osteoarthritis (KOA). KOA is a progressive, chronic degenerative condition that places a heavy socioeconomic burden on healthcare systems and society. The prevalence of knee OA has sharply increased to more than the double in the last 10 years as result of steady state in life expectancy.
KOA is a well-known as a cartilage disease that involves degradation and loss of articular cartilage. However, OA is usually accompanied by changes in the subchondral bone, with sclerosis, bone cyst, and osteophyte formation.
Recent studies reported that subchondral bone remodeling plays a very important role in KOA, mediating and preceding cartilage damage. The increase in subchondral bone stiffness decreases the ability to scatter the loading forces within the knee joint, which then increases the force loaded on articular cartilage. Therefore, the cartilage damage and progress of OA accelerated over time. The focus of treatment in early KOA have shifted from the articular cartilage to the subchondral bone and become a potential therapeutic target of various therapeutic methods.
Regarding KOA pain, accumulating evidence suggests that bottom-up vascularization from subchondral bone plays a larger role than top-down vessel invasion originating from synovial tissue or synovium during cartilage erosion in OA. As a result, it is a common complaint of orthopedists that osteoarthritis pain is not associated with the radiographic presentation. Recent work revealed a relatively weak relationship between cartilage loss and OA joint pain.
As different approaches aimed at articular cartilage or synovial components had inefficient results and the mechanism of bone cartilage crosstalk is gradually becoming clear, this study will try to confirm the critical role of subchondral bone in knee osteoarthritis and that subchondral bone could be an ideal outcome measure of osteoarthritis treatment.
Low-intensity pulsed ultrasound (LIPUS) and extracorporeal shockwave therapy (ECSWT) are effective as a non-invasive method in histopathological recovery with more intense sight, ECSWT has shown effectiveness in the regression of early KOA associated with improving the subchondral bone remodeling, decrease the number of osteophytes and it can also increase osteocytes activity. Besides, ECSWT could alleviate chronic inflammatory activities in the whole joint through down-regulating inflammatory cytokines. Additionally, it was reported that application of ESWT to the subchondral bone of the knee significantly increased bone volume and trabecular number and reduced bone porosity. Overall, ESWT could reverse the pathology of OA progression to some extent.
Low-intensity US might influence the subchondral bone unit under joint disuse. LIUS with its associated acoustic radiation force can alleviate subchondral bone sclerosis during OA progression under normal joint use. In addition, if US technology combined with bioactive compounds materials as chitosan (CS), could improve the encapsulation efficiency of bioactive compounds whereas not only reduced the nanoparticle size but also narrowed their size distribution, this makes US as an effective delivery of biomaterials such as chitosan. In this context, inclusion of mixed interventions with US could improve its effect. Therefore, this study will couple the use of US therapy with a new green environmentally friendly material called chitosan in the form of a topical gel.
Chitosan appears as proteoglycan in the extracellular matrix (shells) of some species of cephalopods. Chitosan's biocompatibility, gradual degradability, non-toxicity, biological activity, anti-inflammatory properties, and antibacterial action, makes chitosan regarded as the best material for hydrogel. Some studies used CS as intra-articular injection for KOA and concluded that CS can promote chondrocyte proliferation, block inflammatory and catabolic mediators. Therefore, Phonophoresis using chitosan could reduce inflammation, limit cartilage degeneration and improve subchondral bone remodeling process.
Additionally, it is well known that confirming diagnosis of KOA is based on assessing joint space width and this is carried out through radiography which depends on the Kellgren-Lawrence grade (K-LG) scale. Despite K-LG scale is considered the most used classical diagnostic tool for KO, it has several drawbacks, including its application to the progression of diseases, its insensitivity to change, or inconsistencies in the authors' initial descriptions. Furthermore, it is limited in how it evaluates treatment efficacy because it mostly uses pain scores.
By looking to the adverse effects of conventional radiology, many studies had reported the possibility of an allergic reaction, expensive costs, lengthy inspection times, and difficulties in scanning patients with specific conditions.
Taking this into account, artificial intelligence (AI)-based approaches are starting to be used to solve these issues as image identification, pre-operative risk assessment, clinical decision- making, and analysis of large data sets, diagnosis, monitor, prognosis of rheumatological diseases, identifying risk factors for complications and has the unique ability to anticipate outcomes using patient-specific algorithms. AI plays a vital role in the appraisal of treatment, in which key progress in the clinical practice of rheumatology is the innovation of advanced imaging modalities.
The use of AI in orthopedics has mostly concentrated on the development of Machine learning (ML) and deep learning (DL) on these pictures. Deep learning, which is a subset of ML, can assist in automatic interpretation of medical images, which may increase diagnostic accuracy and speed, flag the most urgent and critical patients for immediate attention, reduce the amount of human error caused by fatigue and/or inexperience, lessen the strain on medical professionals by reducing their workload, and, in general, improve orthopedic care.
Subchondral bone-remodeling process was reported previously as an important pathophysiology of KO whereas subchondral bone sclerosis is widely considered to be the hallmark of OA. Texture analysis (TA) algorithm is used to detect changes in the subchondral bone density during remodeling process. It was demonstrated encouraging findings and the potential of automated texture analysis employing an AI algorithm as a diagnostic tool for OA in comparison to traditional TA techniques. Bone structure value (BSV) is considered as a maximum-likelihood estimator of OA as automated TA depends on it in the analysis and assessment process that measures the micro-structure of the tibial subchondral bone depends on area of interest (ROI). Consequently, the purpose of this study is to explore the difference between ECSWT, LIUS and traditional exercises regarding the pain reduction, functional improvement (self-reported and physical function) and anatomical improvement of subchondral bone (trabecular tibial bone) micro-structural changes.
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120 participants in 3 patient groups, including a placebo group
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Hamdy Mamdouh Amir; Athar Tarek Mohamed Fahmy Azab, Master
Data sourced from clinicaltrials.gov
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