Knee Diseases Research Articles

A method framework of semi-automatic knee bone segmentation and reconstruction from computed tomography (CT) images.

Accurate delineation of knee bone boundaries is crucial for computer-aided diagnosis (CAD) and effective treatment planning in knee diseases. Current methods often struggle with precise segmentation due to the knee joint's complexity, which includes intricate bone structures and overlapping soft tissues. These challenges are further complicated by variations in patient anatomy and image quality, highlighting the need for improved techniques. This paper presents a novel semi-automatic segmentation method for extracting knee bones from sequential computed tomography (CT) images. Our approach integrates the fuzzy C-means (FCM) algorithm with an adaptive region-based active contour model (ACM). Initially, the FCM algorithm assigns membership degrees to each voxel, distinguishing bone regions from surrounding soft tissues based on their likelihood of belonging to specific bone regions. Subsequently, the adaptive region-based ACM utilizes these membership degrees to guide the contour evolution and refine segmentation boundaries. To ensure clinical applicability, we further enhance our method using the marching cubes algorithm to reconstruct a three-dimensional (3D) model. We evaluated the method on six randomly selected knee joints. We evaluated the method using quantitative metrics such as the Dice coefficient, sensitivity, specificity, and geometrical assessment. Our method achieved high Dice scores for the femur (98.95%), tibia (98.10%), and patella (97.14%), demonstrating superior accuracy. Remarkably low root mean square distance (RSD) values were obtained for the tibia and femur (0.5±0.14 mm) and patella (0.6±0.13 mm), indicating precise segmentation. The proposed method offers significant advancements in CAD systems for knee pathologies. Our approach demonstrates superior performance in achieving precise and accurate segmentation of knee bones, providing valuable insights for anatomical analysis, surgical planning, and patient-specific prostheses.

Toward precision and efficiency: a bibliometric study on robotic-assisted unicompartmental knee arthroplasty research and development

Aim: With the increasing prevalence of knee diseases affecting human health and quality of life, it is essential to explore more advanced surgical assistive technologies to improve the precision, safety, and success rate of unilateral knee replacement surgery. This study aims to conduct a comprehensive bibliometric analysis of robotic-assisted unicompartmental knee arthroplasty (r-UKA) to understand its current status, trends, and future directions. Methods: Retrieve articles about r-UKA in the Web of Science Core Collection (WOSCC) database. Data from 128 selected articles, including author information, publication details, citations, and evidence level, were analyzed. Statistical analyses and data visualizations explored publication and citation trends, research interests, core author groups, and cooperative networks. Results: Interest in r-UKA research has grown, particularly after 2013, which is evident from increased publications and citations. The United States is the largest contributor, followed by the United Kingdom, both of which have prominent medical research institutions and universities actively involved in r-UKA research. Frequent keywords such as “alignment”, “accuracy”, “revision”, and “survivorship” highlight the focus on surgical precision, implant longevity, and patient outcomes. Conclusion: Robotic-assisted unicompartmental knee arthroplasty has gained significant attention, promising improved surgical precision and patient outcomes. Collaboration between researchers and medical institutions globally has driven progress in this field. However, long-term outcomes and clinical efficacy compared to traditional techniques require further investigation. As robotic technology evolves, its application in knee replacement surgery holds potential for better therapeutic effects and advancements toward more accurate, safe, and efficient procedures, benefiting patients and advancing unicompartmental knee arthroplasty (UKA).

Deep learning-based automatic measurement system for patellar height: a multicenter retrospective study

BackgroundThe patellar height index is important; however, the measurement procedures are time-consuming and prone to significant variability among and within observers. We developed a deep learning-based automatic measurement system for the patellar height and evaluated its performance and generalization ability to accurately measure the patellar height index.MethodsWe developed a dataset containing 3,923 lateral knee X-ray images. Notably, all X-ray images were from three tertiary level A hospitals, and 2,341 cases were included in the analysis after screening. By manually labeling key points, the model was trained using the residual network (ResNet) and high-resolution network (HRNet) for human pose estimation architectures to measure the patellar height index. Various data enhancement techniques were used to enhance the robustness of the model. The root mean square error (RMSE), object keypoint similarity (OKS), and percentage of correct keypoint (PCK) metrics were used to evaluate the training results. In addition, we used the intraclass correlation coefficient (ICC) to assess the consistency between manual and automatic measurements.ResultsThe HRNet model performed excellently in keypoint detection tasks by comparing different deep learning models. Furthermore, the pose_hrnet_w48 model was particularly outstanding in the RMSE, OKS, and PCK metrics, and the Insall–Salvati index (ISI) automatically calculated by this model was also highly consistent with the manual measurements (intraclass correlation coefficient [ICC], 0.809–0.885). This evidence demonstrates the accuracy and generalizability of this deep learning system in practical applications.ConclusionWe successfully developed a deep learning-based automatic measurement system for the patellar height. The system demonstrated accuracy comparable to that of experienced radiologists and a strong generalizability across different datasets. It provides an essential tool for assessing and treating knee diseases early and monitoring and rehabilitation after knee surgery. Due to the potential bias in the selection of datasets in this study, different datasets should be examined in the future to optimize the model so that it can be reliably applied in clinical practice.Trial registrationThe study was registered at the Medical Research Registration and Filing Information System (medicalresearch.org.cn) MR-61-23-013065. Date of registration: May 04, 2023 (retrospectively registered).

Investigation of Bio-materials Used in Knee İmplant

Knee joint is formed one of the most serious parts of his body for human beings throughout history. An increase in young people, traffic accidents, walking, running, and other similar movements have led to increased proliferation of the knee orthopedic disorders. Rapid growth and diversification of knee diseases as well an accurate recognition of this region has created a need for treatment. Human knee in case of encountered pain, functional limitation and wear, in total knee arthroplasty due to knee replacement surgery performed on the initiative of medically normal and comfortable walking recovered. In our country is like all over the world, degradation of the knee joint against deficiencies that adversely affect the daily life applications are made with increasing frequency. With the advancement of technological development, researches on this area have been continuing today as a result of producing implants more suitable for bone structure and connective tissue.

Early outcomes of the Oxford unicompartmental knee arthroplasty: 140 cases from a single institute in Taiwan.

The clinical and radiologic outcomes of the Oxford unicompartmental knee arthroplasty utilizing Microplasty® instrumentation have not been extensively investigated in Taiwanese patients. Despite the efficacy of this treatment for unicompartmental knee diseases, its specific impact on this population remains unknown. We retrospectively analyzed prospectively collected data of patients who underwent OUKA with MP between 2018 and 2021, including demographic information, component position, preoperative and postoperative knee range of motion (ROM), numeric rating scale (NRS), and 2011 Knee Society Score-functional activity score (2011 KSS-FAS). We compared preoperative and postoperative data and analyzed the correlation between clinical and radiographic outcomes. Among 140 patients with an average age of 66.8 years, predominantly female, the majority exhibited components that fell within the radiographically acceptable tolerance ranges. The mean 2.5-year follow-up revealed significant improvements in knee ROM from 102.6° ± 12.9° to 127.3° ± 9.8° ( p < 0.05), pain reduction from 7.7 ± 0.8 to 0.4 ± 0.7 ( p < 0.001), and KSS-FAS from 30.7 ± 10.5 to 94.3 ± 5.2 ( p < 0.001). Notably, a tibial component medial overhang within tolerance predicted shorter hospital stays, and a higher preoperative KSS correlated with lower postoperative NRS. No independent variables were identified as predictors of a higher postoperative KSS. Our study on OUKA with MP in Taiwanese patients reveals promising early clinical and radiographic outcomes. Tibial component medial overhang <3 mm is associated with shorter hospital stays, and a higher preoperative KSS predicts lower NRS at 1 year postoperatively.

Automated personalization of biomechanical knee model.

Patient-specific biomechanical models of the knee joint can effectively aid in understanding the reasons for pathologies and improve diagnostic methods and treatment procedures. For deeper research of knee diseases, the development of biomechanical models with appropriate configurations is essential. In this study, we mainly focus on the development of a personalized biomechanical model for the investigation of knee joint pathologies related to patellar motion using automated methods. This study presents a biomechanical model created for patellar motion pathologies research and some techniques for automating the generation of the biomechanical model. To generate geometric models of bones, the U-Net neural network was adapted for 3D input datasets. The method uses the same neural network for segmentation of femur, tibia, patella and fibula. The total size of the train/validation (75/25%) dataset is 18,183 3D volumes of size voxels. The configuration of the biomechanical knee model proposed in the paper includes six degrees of freedom for the tibiofemoral and patellofemoral joints, lateral and medial contact surfaces for femur and tibia, and ligaments, representing, among other things, the medial and lateral stabilizers of the knee cap. The development of the personalized biomechanical model was carried out using the OpenSim software system. The automated model generation was implemented using OpenSim Python scripting commands. The neural network for bones segmentation achieves mean DICE 0.9838. A biomechanical model for realistic simulation of patellar movement within the trochlear groove was proposed. Generation of personalized biomechanical models was automated. In this paper, we have implemented a neural network for the segmentation of 3D CT scans of the knee joint to produce a biomechanical model for the study of knee cap motion pathologies. Most stages of the generation process have been automated and can be used to generate patient-specific models.

Heat therapy for different knee diseases: expert opinion.

Musculoskeletal pain is a major burden in our society. Management of musculoskeletal pain or injuries includes both pharmacological and non-pharmacological approaches, including heat therapy (HT). HT is a well-established treatment option due to its ability to promote muscle relaxation, enhance blood circulation, and modulate nociceptors with a good safety profile. The main focus of this paper is to review the available literature about HT in knee pathologies (i.e., arthrosis, arthritis, traumatic pathologies in the subacute phase, muscle and tendon pathologies linked to fatigue, muscle tension and distractions) and to provide an expert opinion in case of lack of data.

Research on Diagnosis Method of Common Knee Diseases Based on Subjective Symptoms and Random Forest Algorithm

Research on Diagnosis Method of Common Knee Diseases Based on Subjective Symptoms and Random Forest Algorithm

Prevalence of Knee Pain Pathologies Diagnosed By Musculoskeletal Ultrasound In Nepal Police Hospital

Introduction: One of the most frequent cause of orthopedic consultancy in Nepal Police Hospital is acute and chronic knee pain. The purpose of this study was to demonstrate how musculoskeletal ultrasonography aids in the low-cost identification of knee diseases and using ultrasound to compare with the contra lateral knee can be quite beneficial when developing a treatment plan.&#x0D; Methods: A cross sectional study was conducted on 260 patients with clinically confirmed knee pain. All patients were examined by using Sonasite ultrasound machine with linear probe (7-11MHz). The ultrasound examination of the knee started with examination of anterior aspect, followed by medial aspect, lateral aspect in supine position and then in prone position for examination of posterior aspects. The data were collected, tabulated and statistically analyzed using SPSS11.1. Categorical variables were presented in number and percentage, and continuous variables were presented as mean ± SD.&#x0D; Results: In our study, among the 260 cases there were 164 male patients (63.07%) and 96 females (36.93%) with their age ranged between 25-55 years with the mean age of 40 years. Among 260 cases, 103 patients (39.61%) with knee pain had normal finding and 157 patients (60.39%) had knee pathologies. We found joint effusion (8.91%), quadriceps tendinopathy (3.82%), patellar tendinopathy (1.91%), medial meniscal tear (11.46%), lateral meniscal tear (4.45%), synovial hyperplasia (5.73%), medial collateral ligament tear (10.82%), lateral collateral ligament tear (7%), baker,s cyst(2.54%) and osteophytes(43.31%).&#x0D; Conclusions: An efficient imaging technique that may be used as a screening tool for individuals experiencing knee pain is musculoskeletal ultrasound.

SDMT: Spatial Dependence Multi-Task Transformer Network for 3D Knee MRI Segmentation and Landmark Localization

Knee segmentation and landmark localization from 3D MRI are two significant tasks for diagnosis and treatment of knee diseases. With the development of deep learning, Convolutional Neural Network (CNN) based methods have become the mainstream. However, the existing CNN methods are mostly single-task methods. Due to the complex structure of bone, cartilage and ligament in the knee, it is challenging to complete the segmentation or landmark localization alone. And establishing independent models for all tasks will bring difficulties for surgeon's clinical using. In this paper, a Spatial Dependence Multi-task Transformer (SDMT) network is proposed for 3D knee MRI segmentation and landmark localization. We use a shared encoder for feature extraction, then SDMT utilizes the spatial dependence of segmentation results and landmark position to mutually promote the two tasks. Specifically, SDMT adds spatial encoding to the features, and a task hybrided multi-head attention mechanism is designed, in which the attention heads are divided into the inter-task attention head and the intra-task attention head. The two attention head deal with the spatial dependence between two tasks and correlation within the single task, respectively. Finally, we design a dynamic weight multi-task loss function to balance the training process of two task. The proposed method is validated on our 3D knee MRI multi-task datasets. Dice can reach 83.91% in the segmentation task, and MRE can reach 2.12 mm in the landmark localization task, it is competitive and superior over other state-of-the-art single-task methods.

Skeletal maturity as a biomarker for determining indications for regenerative interventional technologies in adolescent patients with hip and knee diseases

Skeletal maturity as a biomarker for determining indications for regenerative interventional technologies in adolescent patients with hip and knee diseases

An AI-Based Image Quality Control Framework for Knee Radiographs

Image quality control (QC) is crucial for the accurate diagnosis of knee diseases using radiographs. However, the manual QC process is subjective, labor intensive, and time-consuming. In this study, we aimed to develop an artificial intelligence (AI) model to automate the QC procedure typically performed by clinicians. We proposed an AI-based fully automatic QC model for knee radiographs using high-resolution net (HR-Net) to identify predefined key points in images. We then performed geometric calculations to transform the identified key points into three QC criteria, namely, anteroposterior (AP)/lateral (LAT) overlap ratios and LAT flexion angle. The proposed model was trained and validated using 2212 knee plain radiographs from 1208 patients and an additional 1572 knee radiographs from 753 patients collected from six external centers for further external validation. For the internal validation cohort, the proposed AI model and clinicians showed high intraclass consistency coefficients (ICCs) for AP/LAT fibular head overlap and LAT knee flexion angle of 0.952, 0.895, and 0.993, respectively. For the external validation cohort, the ICCs were also high, with values of 0.934, 0.856, and 0.991, respectively. There were no significant differences between the AI model and clinicians in any of the three QC criteria, and the AI model required significantly less measurement time than clinicians. The experimental results demonstrated that the AI model performed comparably to clinicians and required less time. Therefore, the proposed AI-based model has great potential as a convenient tool for clinical practice by automating the QC procedure for knee radiographs.

Analysis of Inertia Effect on Axisymmetric Squeeze Flow of Slightly Viscoelastic Fluid Film between Two Disks by Recursive Approach

In this study, we analyzed the inertia effect on the axisymmetric squeeze flow of slightly viscoelastic fluid film between two disks. A system of nonlinear partial differential equations (PDEs) in cylindrical coordinates, along with nonhomogenous boundary conditions, illustrates the phenomenon of fluid flow caused by squeezing with the inertia effect. The Langlois recursive approach was applied to obtain the analytical solution of the system having a stream function, axial and radial velocities, pressure distribution, normal and tangential stresses and normal squeeze force. These flow variables are also portrayed graphically to describe the effects of the Reynolds number and slightly viscoelastic parameter. The results show that by increasing the Reynolds number, the velocity profile decreases, and both the pressure distribution and shear stresses increase. Moreover, there is a small increase in normal squeeze force. When the slightly viscoelastic parameter approaches zero, the obtained solution of flow variables matches with the classical results. This study can be applied to understand the mechanism of load-bearing features in thrust bearings and in arthrodial human joint (knee and hip) diseases.

Magnetic Resonance Imaging of Synovial Diseases of Knee

A specialized tissue called synovium lines the body’s tendons, bursae, and synovial joints. It is affected by various localized or systemic disorders. These are classified into inflammatory, infectious, degenerative, traumatic, hemorrhagic, and neoplastic. Synovial damage leads to irreversible joint destruction. Imaging plays an important role in the early detection of the disease entity and enables for proper treatment. This article focuses on magnetic resonance imaging of synovial diseases pertaining to knee – (1) infective synovitis; (2) rheumatoid synovitis; (3) pigmented villonodular synovitis; (4) lipoma arborescens; (5) synovial hemangioma; and (6) synovial sarcoma.

Generalized joint hypermobility subjects without knee hyperextension have greater walking anterior tibial translation and flexion angle than those with knee hyperextension

BackgroundThe walking knee kinematic results of generalized joint hypermobility (GJH) subjects were controversial in previous studies. We proposed that this could be related to the knee statuses of GJH subjects with/without knee hyperextension (KH) and assumed that there are significant sagittal knee kinematic differences between GJH subjects with/without KH during gait. Research questionDo GJH subjects with KH exhibit significantly different kinematic characteristics than those without KH during walking? Methods35 GJH subjects without KH, 34 GJH subjects with KH, and 30 healthy controls were recruited in this study. A three–dimensional gait analysis system was used to record and compare the knee kinematics of the participants. ResultsSignificant walking knee kinematics differences were found between GJH subjects with/without KH during walking. GJH subjects without KH had greater flexion angles (4.7–6.0°, 24–53 % gait cycle (GC), p < 0.001; 5.1–6.1°, 65–77 % GC, p = 0.008) and anterior tibial translation (ATT) (3.3–4.1 mm, 0–4 % GC, p = 0.015; 3.8–4.3 mm, 91–100 % GC, p = 0.01) than those with KH. Compared to controls, GJH without KH exhibited increased ATT (4.0–5.7 mm, 0–26 % GC, p < 0.001; 5.1–6.7 mm, 78–100 % GC, p < 0.001), and range of motion of ATT (3.3 mm, p = 0.028) whereas GJH with KH only exhibited increased extension angle (6.9–7.3°, 62–66 % GC, p = 0.015) during walking. SignificanceThe findings confirmed the hypothesis and suggested that GJH subjects without KH had more walking ATT and flexion angle asymmetries than those with KH. This may raise concerns about the differences in knee health and risk of knee diseases between GJH subjects with/without KH. However, further investigations should be done to explore the exact influence of walking ATT and flexion angle asymmetries in GJH subjects without KH.

Lipoma arborescence of knee joint in an adolescent male patient: a case report

&lt;p&gt;A very uncommon benign synovial membrane tumor is called lipoma arborescens. It often affects a single articulation, the knee. Despite a conventional imaging assessment, the lesion&amp;rsquo;s histological analysis is still required for the ultimate diagnosis. A 15-year-old boy attended the outpatient clinic of the Lahore General Hospital Lahore, Pakistan with pain and swelling in his left knee that had been steadily worsening over the previous 4 years. There were no concomitant prodromal symptoms, and the swelling was soft and non-tender while also inhibiting knee flexion. Soft tissue shadows were observed on radiographs. A large amount of subarticular erosion in the nearby tibial and femoral condyle was caused by the frond-like proliferation of fatty synovium, according to magnetic resonance imaging. Only the left knee joint showed focused areas of unusually elevated radionuclide uptake during the Technetium (Tc99m) bone scan. After an open synovectomy, the specimen underwent histological analysis, which revealed villiform fatty tissue, a hallmark of Lipoma arborescens coated by somewhat thicker synovium. Although infrequent, open synovectomy is currently the preferred course of treatment for lipoma arborescens, which should be taken into account when making a differential diagnosis of knee diseases. Approximately 3 months after surgery, the patient underwent his most recent follow-up and was asymptomatic with a small amount of joint effusion.&lt;/p&gt;

Effects of Press Needle Intervention on Knee Flexion and Extension Movements: A Randomized Trial

Objective: Knee flexion exercise is a type of exercise therapy for improving knee-joint muscle strength. Among the knee extensors, the vastus medialis muscle is less active and prone to disuse atrophy. The effects of press needle acupuncture include vasodilation, which may affect blood flow in the vastus medialis. This study examined the effects of exercise stimulation + press needle stimulation on muscle blood flow. Materials and Methods: Conducted in Teikyo Heisei University, Tokyo, Japan, this randomized controlled trial involved 30 healthy adults in 3 groups (10 who did not receive stimulation, 10 who received exercise stimulation only, and 10 who received press needle stimulation + exercise stimulation). The stimulations were applied once per week, for 3 weeks. After resting for 10 minutes, the nonstimulated group rested for 2 additional minutes, and the other 2 groups performed knee flexion and extension exercises considered to be “very very hard on the Borg rating.” After this activity, the 2 stimulation groups rested for 10 minutes. Press needle stimulation was applied on the vastus medialis muscles of both thighs in the combination stimulation group. Results: The combination group had a smaller decrease in muscle tissue oxygen saturation and an increase in total hemoglobin, compared to the exercise only stimulation group. Conclusions: Press needle stimulation during exercise may dilate muscle blood vessels. Future studies should examine the effectiveness of this stimulation for age-specific and knee diseases.

Evaluation of the effect of injectionsof both platelet-rich plasma and hyaluronic acid in patients with early knee osteoarthritis via the concentration of interleukin-1β in serum

Background Early knee osteoarthritis, which causes the degeneration of articular cartilage and subchondral bone, is a disease that worsens with time and is a major contributor to physical disability. Several inflammatory cy- tokines released by chondrocytes work in concert to trigger the production of enzymes that break down cartilage. A pro-inflammatory cytokine called interleukin-1β (IL-1 β ) accelerates cartilage breakdown after trauma, re- duces matrix production, and results in chondrocyte death. Dendritic cells and macrophages are the main sources of IL-1β. On the other hand, os- teoblasts, periodontal ligament cells, and gingival fibroblasts have the abil- ity to release IL-1β. Treatment pure- platelet rich plasma (P-PRP) effec- tiveness of transforming growth factor, platelet-derived growth factor, type I insulin-like growth factor, and the vascular endothelial growth factor is thought to be related to their release. Because of their capacity to increase matrix formation, growth factors have been widely researched for OA and cartilage regeneration. Hyaluronic acid (HA) is a glycosaminoglycan poly- mer composed of N-acetyl glucosamine and D-glucuronic acid disaccharide molecules. Early embryonic development, inflammatory, wound repair, cell differentiation, and viscoelasticity are all affected by HA, and other biologi- cal processes. Materials and Methods Elabscience kits were used to assess the serum IL-1β level. The experimental investigation included 18 control groups, 10 HA injections, and 21 pure PRP injections. age ranged from 30 to 80. The study was excluded all individuals with advanced osteoarthritis in the knee, COVID-19, diabetes, and autoimmune diseases. the time frame running from November 2021 until June 2022. Other variables in our research were age, gender, family history, use of antihypertensive medications or medica- tions for other disorders, and body mass index (BMI). Results The findings of this study demonstrate elevated IL-1β levels in patients with early KOA before treatments injection compared with the healthy control. After treatments injection, the level of IL-1β was decreased compared with before injection. Conclusions IL-1β could be one of the prognostic signs of early KOA

How to improve the rehabilitation outcome after total knee replacement?

Abstract Background Even if total knee replacement has revolutionized the treatment of degenerative knee diseases, the definition of an ideal rehabilitation protocol is still in progress. The aim of this study is to identify the factors that influence the outcomes after early, intensive, hospitalized treatment. Methods A retrospective study was conducted in 2019 on 545 patients admitted to a northern Italy private clinic specialized in post-surgery rehabilitation, which applies a bio-psycho-social-environmental model and individual rehabilitation plans. Data regarding each patient were collected from medical records: age, numeric pain rating scale (NPRS) at admission, days between surgery and the beginning of rehabilitation (DBS). The outcomes were measured as the difference (Δ) between the values at discharge and admission of the Barthel scale (ΔBS), Tinetti scale (ΔTS), passive flexion (ΔPF) and active flexion (ΔAF). We performed a univariate linear regression through STATA, to determine which factors influence the outcomes. A p &amp;lt; 0.05 was considered statistically significant. Results Our sample (69.17% female) was 69.8 ± 9.4 years old. ΔBS was significantly influenced by age (Coef. 0.270, CI [0.173 - 0.367]) and NPRS (Coef. 1.434, CI [0.979 - 1.890]). ΔTS was significantly influenced by age (Coef. 0.024, CI [0.011 - 0.037]) and NPRS (Coef. 0.130, CI [0.067 - 0.191]). ΔPF was significantly influenced by age (Coef. - 0.158, CI [- 0.266 - - 0.050]), DBS (Coef. - 1.047, CI [- 1.401 - - 0.687]) and NPRS (Coef. 1.825, CI [1.333 - 2.318]). ΔAF was significantly influenced by age (Coef. - 0.171, CI [- 0.300 - - 0.042]), DBS (Coef. - 1.150, CI [- 1.580 - - 0.721]) and NPRS (Coef. 2.504, CI [1.928 - 3.080]). Conclusions Older patients obtain a higher functional outcome (ΔBS, ΔTS) but lower improvement in range of motion (ΔPF, ΔAF). Patients with higher NPRS at admission obtain an overall better outcome. Higher DBS is associated to lower articular outcomes (ΔPF, ΔAF). Key messages • A better outcome can be achieved if rehabilitation is started immediately after knee replacement. • Pain and age are not factors that impede effective rehabilitation.

Virtual Reality as Treatment Method for Knee Osteoarthritis - Short Review

Virtual reality is computer-generated technology for therapeutic uses and rapidly growing in popularity. This review focused on the outcomes of the study show that virtual reality as treatment approach is a safe and acceptable therapy providing participants with satisfaction and motivation to exercise. Therapists are using VR to help people rehabilitate from osteoarthritis, strokes and injuries. The efficiency of Virtual Reality treatment was observed in patient with OA knee and many other diseases. Virtual reality approach Physical rehabilitation focuses on pain treatment, gait re-education, body balance improvement, increased mobility, and muscular strength development. Because of VR and modern technology, this activity should be done quickly and safely under the supervision of the therapist. Virtual reality is cost-effective of VR headsets and the expansion of Virtual reality apps. Using virtual reality to create fascinating and demanding settings can help you active and interested in your rehab.