Diagnosis of osteoarthritis: imaging

Harnessing Photo-Energy Conversion in Nanomaterials for Precision Theranostics

The rapidly advancing field of theranostics aims to integrate therapeutic and diagnostic functionalities into a single platform for precision medicine, enabling the simultaneous treatment and monitoring of diseases. Photo-energy conversion-based nanomaterials have emerged as a versatile platform that utilizes the unique properties of light to activate theranostics with high spatial and temporal precision. This review provides a comprehensive overview of recent developments in photo-energy conversion using nanomaterials, highlighting their applications in disease theranostics. The discussion begins by exploring the fundamental principles of photo-energy conversion in nanomaterials, including the types of materials used and various light-triggered mechanisms, such as photoluminescence, photothermal, photoelectric, photoacoustic, photo-triggered SERS, and photodynamic processes. Following this, the review delves into the broad spectrum of applications of photo-energy conversion in nanomaterials, emphasizing their role in the diagnosis and treatment of major diseases, including cancer, neurodegenerative disorders, retinal degeneration, and osteoarthritis. Finally, the challenges and opportunities of photo-energy conversion-based technologies for precision theranostics are discussed, aiming to advance personalized medicine.

Comprehensive Multi-omics and Mendelian Randomization Reveal the Key Role of Monocytes in Aging and Osteoarthritis

There is a close connection between aging and osteoarthritis (OA), but the specific mechanisms are still unclear. This study aims to explore the potential connections and molecular mechanisms between OA and aging through multi-omics and genetics methods. Integrating single-cell RNA sequencing (scRNA-seq), bulk RNA-seq data, Mendelian randomization (MR), colocalization analysis, and cell function analysis, this study explores the correlation between OA and aging. Furthermore, it investigates the potential causal relationship between key marker genes and OA. Integrating and analyzing scRNA-seq data from OA, aging, and control groups revealed a significant increase in the proportion of the classical monocyte core subgroup. Differential expression analysis yielded 77 marker genes, and further MR analysis identified four key marker genes (DUSP6, CSTA, CD300E, and GPX1) as causally related to OA, which was confirmed in an independent validation cohort. Reverse MR and Steiger filtering indicated no evidence of reverse causality. DUSP6- and CSTA-classical monocytes may interact with other cell subgroups through the MIF-(CD74 + CD44) signaling pathway. This study revealed the heterogeneity of monocyte subgroups in OA and aging patients, identifying key marker genes with a causal relationship to OA through an integrated multi-omics approach, providing potential molecular targets for the diagnosis and treatment of OA from an aging perspective.

Genicular Artery Embolization: A Technical Review of Anatomy, Pathophysiology, Current Experiences, and Future Directions

Genicular artery embolization (GAE) is an emerging minimally invasive procedure for managing knee osteoarthritis (OA), a condition affecting 365 million individuals globally. Initially developed to treat hemarthrosis, GAE selectively embolizes abnormal genicular vasculature, targeting synovial inflammation and reducing neoangiogenesis. This process alleviates pain and improves joint function, providing an alternative for patients with mild-to-moderate OA who are not candidates for surgical interventions due to comorbidities or other factors. Current evidence supports the use of GAE for patients with mild-to-moderate OA who experience persistent symptoms despite conservative treatments such as physical therapy, weight management, or intra-articular injections. The procedure effectively reduces pain, improves functionality, and provides sustained benefits. This review highlights the anatomical principles, procedural techniques, and patient selection criteria for GAE, as well as the clinical evidence supporting its safety and efficacy. It also explores potential future directions for research, including optimizing patient selection, evaluating long-term outcomes, and integrating GAE into routine OA management pathways.

Gold Nanoparticles as a Tool to Detect Biomarkers in Osteoarthritis: New Insights

Extensive research over the years has revealed the remarkable potential of gold nanoparticles (AuNPs) for detecting biomarkers in osteoarthritis (OA). AuNPs are a promising class of nanomaterials offering a wide range of diagnostic and clinical applications. It provides an effective and robust framework for qualitative and quantitative analysis of biomarkers present in the biological fluids of OA patients. AuNPs as theranostics have gained significant attention due to their discrete physical and optical characteristics, including localized surface plasmon resonance (LSPR), fluorescence, surface-enhanced Raman scattering, and quantized charging effect. These unique properties provide AuNPs as an excellent scaffold for ligand multiplexing, allowing accrued sensitivity for biomarker detection. Several reports have delved into the LSPR properties of the kinetics of biological interactions between the ligand and analyte. Tuneable radiative properties of AuNPs coupled with surface engineering allow facile detection of biomarkers in biological fluids. Herein, we have presented a comprehensive summary of distinct biomarkers generated from different molecular pathological processes in OA. An armamentarium of diagnostic methodologies such as aptamer conjugation, antibody coupling, ligand anchoring, and peptide decoration on the surface of AuNPs facilitates the identification and quantification of biomarkers. Additionally, a diverse range of sensing strategies for biomarker spotting, along with current challenges and future perspectives, have also been well delineated in the present manuscript.

Graphical Abstract

Symptoms indicative of early knee osteoarthritis after ACL reconstruction: descriptive analysis of the SHIELD cohort

Objective

To describe the SHIELD cohort in terms of symptoms indicative of early knee osteoarthritis (OA) and to investigate associations between patient characteristics (demographics, activity/injury-related) and these symptoms at 1 (cross-sectional) and 3 years (longitudinal) post anterior cruciate ligament reconstruction (ACLR).

Method

106 participants (50 ​% women, mean [SD] age 25 [5] years) were included. Symptoms indicative of early knee OA were evaluated by the Knee injury and Osteoarthritis Outcome Score (KOOS) subscale pain, KOOS subscale pain ≤72 (KOOSpain ≤72), and ≤85 on two out of four KOOS subscales (pain, symptoms, activity of daily living, quality of life) (modified Luyten).

Results

Mean (SD) KOOS pain scores were 83.2 (15.7) and 87.3 (12.7) at 1 and 3 years, respectively. At 1 year and 3 years post ACLR, 18/101 (18 ​%) and 14/86 (16 ​%) participants met the KOOSpain ≤72 criterion, whereas 83/101 (82 ​%) and 67/86 (78 ​%) met the modified Luyten criterion. 7/15 (47 ​%) (KOOSpain ≤72) and 59/70 (84 ​%) (modified Luyten) classified as having knee OA symptoms 1 year post ACLR were still classified as having OA symptoms after 3 years. Lower activity level at 1 year was the sole variable consistently associated with all three outcomes 3 years post ACLR.

Conclusion

The proportion of participants fulfilling existing classification criteria for symptoms indicative of early OA after ACLR is highly dependent on the criteria applied and different criteria seem to capture varying aspects of early OA symptoms. Future studies will reveal if these symptoms will persist long-term or just reflect more transient issues.

Low-dose Radiation Therapy (LDRT) in Managing Osteoarthritis: A Comprehensive Review

Osteoarthritis (OA) is the most common degenerative arthropathy, impacting the quality of life for millions worldwide. It typically presents with chronic pain, stiffness, and reduced mobility in the affected joints. Nonsurgical treatments like physiotherapy or pharmacotherapy may provide limited relief and may have adverse effects and complications. Recently, low-dose radiation therapy (LDRT) has emerged as a potential alternative for managing OA, utilizing its anti-inflammatory effects. LDRT's anti-inflammatory effects involve modulating immune responses, reducing pro-inflammatory cytokines, and inducing apoptosis in inflammatory cells. Clinical studies show varying degrees of symptom relief, with some patients experiencing pain reduction and improved joint mobility while others show minimal response. The variability in LDRT treatment designs, radiation dosages, and patient populations complicates standardized treatment protocols and raises concerns about potential carcinogenic risks. Despite these issues, LDRT shows promise as an alternative to other OA treatments, especially for patients who don't respond to other treatments. This review aims to provide updated information on the effectiveness, mechanisms, and safety of LDRT in treating OA. We reviewed the literature of studies on the safety and efficacy of LDRT on affected joints by OA, its biological effects, potential therapeutic and adverse effects, application and contraindications, clinical outcomes, and clinical evidence in subjects with OA.

Medial and Lateral Meniscus Root Tear: Etiopathogenesis and Morphological Pattern in Indian Population

Objective

This study aims to enhance our understanding of the morphological pattern, causes and pathogenesis of meniscal root injuries in the Indian population.

Materials and Methods

Sixty-four patients with meniscus root tears were included in the study. The patients were categorized into two groups based on the location of the meniscus tear: Group 1 (n = 41) comprised patients with lateral meniscus root injury (LMRI), and Group 2 (n = 23) included patients with medial meniscus root injury (MMRI). Demographic and patient-specific data, such as age, gender, BMI, history of injury, and injury type, were recorded. All patients underwent surgical treatment, and intraoperative findings (chondral damage grade, type of root injury, associated ligamentous injuries) were documented. Meniscus root tears are further classified into 5 categories depending upon their morphological types. A minimum 12-month follow-up assessed functional outcomes using the Lysholm and IKDC knee scores.

Results

The mean age for MMRI and LMRI was 50.3 years and 29.4 years, respectively. In the MMRI group, 48% (11/23) were female compared to only 15% (6/41) in the LMRI group. The mean BMI in the MMRI and LMRI groups was 30.1 and 25.4, respectively. Nine patients in MMRI and 4 patients in LMRI group exhibited grade 3 or higher chondral damage. Type 2 meniscus root tear was most common type in both the groups (51% in MMRI vs. 74% in LMRI). Both LMRI and MMRI groups demonstrated significant improvement in functional outcomes.

Conclusions

Medial meniscus root injuries predominantly occur in the elderly without a significant history of trauma, often associated with a high grade of medial femoral chondral damage, suggesting a degenerative etiology. In contrast, lateral meniscus root injuries tend to occur in younger patients with a notable history of knee injury, indicative of a traumatic etiology for LMRI.

Investigating the Potential of Magnesium Microparticles on Cartilage and Bone Regeneration Utilizing an In Vitro Osteoarthritis Model

Osteoarthritis (OA) is a significant condition that profoundly impacts synovial joints, including cartilage and subchondral bone plate. Biomaterials that can impede OA progression are a promising alternative or supplement to anti-inflammatory and surgical interventions. Magnesium (Mg) alloys known for bone regeneration potential were assessed in the form of Mg microparticles regarding their impact on tissue regeneration and prevention of OA progression. In vitro assays based on mesenchymal stem cells (SCP-1) were applied to evaluate the Mg microparticle's compatibility and function. Biocompatibility documented through live-dead staining and lactate dehydrogenase assay revealed a 90% cell viability at a concentration below 10 mM after 3 days of exposure. An in vitro OA model based on the supplementation of the cytokines IL-1β, and TNF-α was established and disclosed the effect of Mg degradation products in differentiating SCP-1 cells. Sustained differentiation was confirmed through extracellular matrix staining and increased gene marker expression. The Mg supplementation reduced the release of inflammatory cytokines (IL-6 and IL-8) while promoting the expression of proteins such as collagen X, collagen I, and osteopontin in a time-dependent manner. The in vitro study suggests that Mg microparticles hold a therapeutic potential for OA treatment with their ability to support bone and cartilage repair mechanisms even under inflammatory conditions.

Proteomic characterization of particle-protein coronas shows differences between osteoarthritic and contralateral knees in a rat model

OBJECTIVE

When synthetic particles are injected into a biofluid, proteins nonspecifically adsorb onto the particle surface and form a protein corona. Protein coronas are known to alter how particles function in blood; however, little is known about protein corona formation in synovial fluid or how these coronas change with osteoarthritis (OA). In this study, protein coronas were characterized on particles incubated within OA-affected or healthy rat knees.

DESIGN

First, to evaluate particle collection techniques, magnetic polystyrene particles were placed in bovine synovial fluid and separated using either magnetics or centrifugation. In a second experiment, 12 male and 12 female Lewis rats received a simulated medial meniscal injury. At 2, 5, or 8 weeks post-surgery, operated and contralateral limbs were injected with clean magnetic particles (n = 8 per timepoint). After a 4-h incubation, animals were euthanized and particles were magnetically recovered. In both experiments, protein coronas were characterized using an Orbitrap fusion mass spectrometer.

RESULTS

In the first experiment, the particle separation method affected the identified proteins, likely due to centrifugation forces causing some large proteins to spin-down with the particles. In the OA model, 300-500 proteins were identified in the particle-protein coronas with 35, 59, and 13 proteins differing between the OA-affected and contralateral limbs at 2, 5, and 8 weeks, respectively. In particular, plectin, a serine (or cysteine) proteinase inhibitor, and cathepsin B were more prominent in the particle-protein coronas of OA-affected knees.

CONCLUSIONS

Synthetic particles nonspecifically adsorb proteins in synovial fluid, and these binding events differ with OA severity.

Do PROMs or Sensor-Based Monitoring Detect Improvements in Patients' Knee Function After Total-Knee Arthroplasty?-A Study Protocol for a Prospective Controlled Study

Determining whether preoperative performance-based knee function predicts postoperative performance-based knee function and whether patient-reported outcome measures (PROMs) completed by participants can detect these changes could significantly enhance the planning of postoperative rehabilitation for patients following total knee arthroplasty (TKA). This study aims to collect data on performance-based knee function using inertial measurement units (IMUs) worn by participants both preoperatively and postoperatively. PROMs will be completed by the patients before and after surgery to assess their ability to detect the same changes in performance-based knee function measured by the sensors. Additionally, the study will investigate the correlation between the degree of knee alignment correction and postoperative performance-based knee function in participants after TKA.

XGBoost-SHAP-based interpretable diagnostic framework for knee osteoarthritis: a population-based retrospective cohort study

OBJECTIVE

To use routine demographic and clinical data to develop an interpretable individual-level machine learning (ML) model to diagnose knee osteoarthritis (KOA) and to identify highly ranked features.

METHODS

In this retrospective, population-based cohort study, anonymized questionnaire data was retrieved from the Wu Chuan KOA Study, Inner Mongolia, China. After feature selections, participants were divided in a 7:3 ratio into training and test sets. Class balancing was applied to the training set for data augmentation. Four ML classifiers were compared by cross-validation within the training set and their performance was further analyzed with an unseen test set. Classifications were evaluated using sensitivity, specificity, positive predictive value, negative predictive value, accuracy, area under the curve(AUC), G-means, and F1 scores. The best model was explained using Shapley values to extract highly ranked features.

RESULTS

A total of 1188 participants were investigated in this study, among whom 26.3% were diagnosed with KOA. Comparatively, XGBoost with Boruta exhibited the highest classification performance among the four models, with an AUC of 0.758, G-means of 0.800, and F1 scores of 0.703. The SHAP method reveals the top 17 features of KOA according to the importance ranking, and the average of the experience of joint pain was recognized as the most important features.

CONCLUSIONS

Our study highlights the usefulness of machine learning in unveiling important factors that influence the diagnosis of KOA to guide new prevention strategies. Further work is needed to validate this approach.

Exploration of the Key Pathways and Genes Involved in Osteoarthritis Genesis: Evidence from Multiple Platforms and Real-World Validation

Background

Osteoarthritis (OA), a degenerative and chronic joint disease, is essential for identifying novel biomarkers for the clinical diagnosis of OA.

Methods

We collected 35 OA patients and 32 healthy controls from four clinical cohorts and 8 real-world samples from our institute. The activation status of 7530 signalling pathways was calculated via the gene set enrichment analysis (GSEA) algorithm. Ten machine learning algorithms and 101 algorithm combinations were further applied to recognize the most diagnostic genes. KDELR3 was chosen for further validation via immunohistochemical staining to determine its diagnostic value in real-world samples.

Results

Sixteen pathways, namely, the cellular respiration chain, protein transport, lysosomal and endocytosis pathways, were activated in OA patients. A total of 101 types of algorithm combinations were considered for the diagnostic model, and 58 were successfully output. The two-step model of glmBoost plus RF had the highest average AUC value of 0.95 and was composed of LY86, SORL1, KDELR3, CSK, PTGS1, and PTGS2. Preferable consistency of the diagnostic mole and real conditions was observed in all four cohorts (GSE55235: Kappa=1.000, P<0.001; GSE55457: Kappa=0.700, P<0.001; GSE82107: Kappa=0.643, P=0.004; GSE1919: Kappa=1.000, P<0.001). KDELR3 was expressed at higher levels in OA patients than were the other genes, and with the help of immunohistochemistry (IHC), we confirmed that OA patients presented high levels of KDELR3 in synovial tissues. The infiltration of immunocytes, macrophages, and natural killer T cells was high in OA patients. KDELR3 might be involved in the activation and infiltration of effector memory CD4 T cells (Rpearson = 0.58, P < 0.001) and natural killer T cells (Rpearson = 0.53, P < 0.001).

Conclusion

We constructed and validated a six-gene diagnostic model for OA patients via machine learning, and KDELR3 emerged as a novel biomarker for OA.

Automatic knee osteoarthritis severity grading based on X-ray images using a hierarchical classification method

BACKGROUND

This study aims to develop a hierarchical classification method to automatically assess the severity of knee osteoarthritis (KOA).

METHODS

This retrospective study recruited 4074 patients. Clinical diagnostic indicators and clinical diagnostic processes were applied to develop a hierarchical classification method that involved four sub-task classifications. These four sub-task classifications were the classification of Kellgren-Lawrence (KL) grade 0-2 and KL grade 3-4, KL grade 3 and KL grade 4, KL grade 0 and KL grade 1-2, and KL grade 1 and KL grade 2, respectively. To extract the features of clinical diagnostic indicators, four U-Net models were first used to segment the total joint space (TJS), the lateral joint space (LJS), the medial joint space (MJS), and osteophytes, respectively. Based on the segmentation result of TJS, the region of knee subchondral bone was generated. Then, geometric features were extracted based on segmentation results of the LJS, MJS, TJS, and osteophytes, while radiomic features were extracted from the knee subchondral bone. Finally, the geometric features, radiomic features, and combination of geometric features and radiomic features were used to construct the geometric model, radiomic model, and combined model in KL grading, respectively. A strict decision strategy was used to evaluate the performance of the hierarchical classification method in all X-ray images of testing cohort.

RESULTS

The U-Net models achieved relatively satisfying performances in the segmentation of the TJS, the LJS, the MJS, and the osteophytes with the dice similarity coefficient of 0.88, 0.86, 0.88, and 0.64 respectively. The combined models achieved the best performance in KL grading. The accuracy of combined models was 98.50%, 81.65%, 82.07%, and 74.10% in the classification of KL grade 0-2 and KL grade 3-4, KL grade 3 and KL grade 4, KL grade 0 and KL grade 1-2, and KL grade 1 and KL grade 2, respectively. For all X-ray images of the testing cohort, the accuracy of the hierarchical classification method was 65.98%.

CONCLUSION

The hierarchical classification method developed in the current study is a feasible approach to assess the severity of KOA.

Should We Wait for Bone-on-Bone Arthritis? Equivalent Clinical Outcomes in Patients Requiring Advanced Imaging Before Primary Total Hip Arthroplasty

BACKGROUND

Plain radiographs remain the standard for diagnosing osteoarthritis (OA). Total hip arthroplasty (THA) is generally offered only for advanced OA by plain radiographs. Advanced imaging is used as an adjunct to assess OA severity in cases of progressive symptoms with less advanced OA by plain radiographs. The objective of this study was to compare outcomes following THA in patients who have advanced OA visualized by plain radiographs to patients who have less severe OA visualized by plain radiographs.

METHODS

From February 2016 to February 2020, 93 patients who had Kellgren-Lawrence (KL) grade 0 to 2 OA and underwent THA were identified. The median age was 65 years, and 55% were women. They were matched 1:3 to patients who underwent THA for KL 4 OA based on age, sex, body mass index, and Charlson Comorbidity Index. The primary outcome was achievement of the Hip Injury and Osteoarthritis Outcome Score for Joint Replacement (HOOS JR) minimum clinically important difference, substantial clinical benefit, and patient-acceptable symptom state at 1 year postoperatively.

RESULTS

There was no difference between the KL 0 to 2 and KL 4 cohorts in the achievement of HOOS JR minimum clinically important difference (86 versus 85.6%, P = .922), substantial clinical benefit (81.7 versus 80.2%, P = .751), or patient-acceptable symptom state (89.2 versus 85.6%, P = .374). The KL 0 to 2 cohort had a similar improvement in their 2-year HOOS JR (42.5 versus 38.6, P = .019).

CONCLUSIONS

In this series, there was no difference in outcomes following primary THA between patients who have severe OA on plain radiographs (KL 4) compared to those who have less severe OA (KL 0 to 2). In the setting of severe symptoms and the absence of advanced OA on radiographs, advanced imaging can be used to guide treatment and select patients who could benefit from THA.

Etodolac utility in osteoarthritis: drug delivery challenges, topical nanotherapeutic strategies and potential synergies

Osteoarthritis (OSA) is a prevalent joint disorder characterized by losing articular cartilage, primarily affecting the hip, knee and spine joints. The impact of OSA offers a major challenge to health systems globally. Therapeutic approaches encompass surgical interventions, non-pharmacological therapies (exercise, rehabilitation, behavioral interventions) and pharmacological treatments. Inflammatory processes within OSA joints are regulated by pro-inflammatory and anti-inflammatory cytokines. Etodolac, a COX-2-selective inhibitor, is the gold standard for OSA management and uniquely does not inhibit gastric prostaglandins. This comprehensive review offers insights into OSA's pathophysiology, genetic factors and biological determinants influencing disease progression. Emphasis is placed on the pivotal role of etodolac in OSA management, supported by both preclinical and clinical evidences in topical drug delivery. Notably, in-silico docking studies suggested potential synergies between etodolac and baicalein, considering ADAMTS-4, COX-2, MMP-3 and MMP-13 as essential therapeutic targets. Integration of artificial neural network (ANN) techniques with nanotechnology approaches emerges as a promising strategy for optimizing and personalizing topical etodolac delivery. Furthermore, the synergistic potential of etodolac and baicalein warrants in-depth exploration. Hence, by embracing cutting-edge technologies like ANN and nanomedicine, the optimization of topical etodolac delivery could guide a new era of OSA treatment.

High-Field MRI Advantages and Applications in Rheumatology

Imaging of rheumatologic diseases has historically been performed using conventional radiography. MRI offers an opportunity for detection of altered marrow signal in early disease that is not visible on other imaging modalities such as radiography, computed tomography, or sonography. This review describes the advantages of current MRI techniques in the diagnosis and treatment monitoring of rheumatologic diseases. In addition, this review discusses novel MRI techniques at high-field magnetic strength which may be deployed in the future to allow for improved imaging resolution and quantitative assessment of both axial and peripheral joints.

Influence of Health Insurance Coverage on the Survival Rate for Primary Total Knee Arthroplasty: Minimum 5-Year Follow-Up Analysis

This study investigated whether differences in survival rates and clinical outcomes exist in patients undergoing TKA by insurance type: National Health Insurance (NHI) vs. Medical Aid Program (MAP). This study conducted a retrospective analysis of 762 TKAs (NHI, n = 505; MAP, n = 257) with a mean follow-up of 8.4 ± 1.8 years. Patient-reported outcomes (PROMs) were evaluated using the American Knee Society's (AKS) score at the final follow-up. The survival rate of each group was analyzed using Kaplan-Meier survival analysis. Any postoperative complications and readmissions within 90 days of discharge were recorded and compared between the groups. There were no between-group differences in pre- to postoperative improvement in AKS scores. The estimated 10-year survival rates were 98.5% in the NHI group and 96.9% in the MAP group, respectively, with no significant differences (p = 0.48). However, the length of hospital stay (LOS) was significantly longer in the MAP group than in the NHI group (13.4 days vs. 13.1 days, p = 0.03), and the transfer rate to other departments was significantly higher in the MAP group than in the NHI group (3.9% vs. 1.4%, p = 0.04). Readmission rates for orthopedic complications for 90 days were 3.0% in the NHI group and 3.5% in the MAP group, respectively (p = 0.67). Patients' insurance type showed similar survival rates and clinical outcomes to those of primary TKA at a mean follow-up of 8.4 years, but the LOS and rate of transfer to other departments during hospitalization were influenced by insurance type.

Effectiveness of extracorporeal shock wave therapy on functional ability in grade IV knee osteoarthritis - a randomized controlled trial

Extracorporeal shockwave therapy (ESWT) is a non-invasive physical therapy intervention that has emerged in the recent past to address the upswing of osteoarthritis (OA). However, insufficient evidence is present to prove the efficacy of ESWT on grade IV knee osteoarthritis (KOA). The present study aimed to examine the effects of ESWT on functional ability in patients suffering from grade IV KOA. Thirty volunteers aged 45-60 years with grade IV primary KOA diagnosed by an orthopaedic surgeon based on the Kellgren-Lawrence score participated in the study. The participants were equally and randomly divided into two groups (i.e. experimental and control), with 15 participants in each group. The participants in the control group performed conventional physiotherapy (CPT) that included ultrasound therapy, isometric quadriceps, SLR and isometric hip adductor strengthening exercises. The participants in the experimental group received ESWT in addition to CPT. Lower extremity functional scale (LEFS) score was measured before and after the four weeks of intervention. In both groups, a statistically significant (p = 0.001) improvement in LEFS was observed. In the experimental groups, it improved by 81.92% and in the control groups by 48.15%. A statistically significant (p < 0.001) difference was observed in LEFS post-intervention values between both groups. As demonstrated by our trial results, the addition of ESWT to the CPT program will yield beneficial results in ameliorating the functional disability in patients with primary KOA (grade IV). Further studies are needed to confirm and apply these findings to a larger cohort.

Diagnostic value of ultrasonography in knee osteoarthritis: A systematic review

Background

Knee osteoarthritis (KOA) is the most expected diagnosis for an arthropathy that causes discomfort and disability in older adults. Radiography is frequently used to assess patients with KOA and there have been few prior research evaluating the diagnostic efficacy of ultrasonography (US). The current study sought to assess the diagnostic efficacy of the US in identifying various characteristics of KOA in the scientific literature.

Materials and Methods

This study was conducted following the Preferred Reporting Items for Systematic Reviews and Meta Analyses statement. A systematic search in PubMed, Web of Science, Scopus, and Embase databases was completed in March 2023. This study focused on the diagnostic value of US in KOA, including sensitivity, specificity, positive predictive value, and negative predictive value. The quality assessment was conducted using the Joanna Briggs Institute critical appraisal tools.

Results

Out of 552 records of database searches, finally, two studies met this systematic review's eligibility criteria and were included in the study. Both of the included studies were cross sectional studies. US demonstrated remarkable sensitivity with adequate specificity for the detection of radiographic knee OA; however, it was found not to be an appropriate method for the detection of early KOA.

Conclusion

This study as the first systematic review aims to evaluate the diagnostic performance of US in detecting KOA. These findings shed light on the importance of investigating the different US features in the evaluation of KOA to reach appropriate sensitivity and specificity in the diagnosis.

Holistic vibrational spectromics assessment of human cartilage for osteoarthritis diagnosis

Osteoarthritis (OA) is the most common degenerative joint disease, presented as wearing down of articular cartilage and resulting in pain and limited mobility for 1 in 10 adults in the UK [Osteoarthr. Cartil.28(6), 792 (2020)10.1016/j.joca.2020.03.004]. There is an unmet need for patient friendly paradigms for clinical assessment that do not use ionizing radiation (CT), exogenous contrast enhancing dyes (MRI), and biopsy. Hence, techniques that use non-destructive, near- and shortwave infrared light (NIR, SWIR) may be ideal for providing label-free, deep tissue interrogation. This study demonstrates multimodal "spectromics", low-level abstraction data fusion of non-destructive NIR Raman scattering spectroscopy and NIR-SWIR absorption spectroscopy, providing an enhanced, interpretable "fingerprint" for diagnosis of OA in human cartilage. This is proposed as method level innovation applicable to both arthro- or endoscopic (minimally invasive) or potential exoscopic (non-invasive) optical approaches. Samples were excised from femoral heads post hip arthroplasty from OA patients (n = 13) and age-matched control (osteoporosis) patients (n = 14). Under multivariate statistical analysis and supervised machine learning, tissue was classified to high precision: 100% segregation of tissue classes (using 10 principal components), and a classification accuracy of 95% (control) and 80% (OA), using the combined vibrational data. There was a marked performance improvement (5 to 6-fold for multivariate analysis) using the spectromics fingerprint compared to results obtained from solely Raman or NIR-SWIR data. Furthermore, clinically relevant tissue components were identified through discriminatory spectral features - spectromics biomarkers - allowing interpretable feedback from the enhanced fingerprint. In summary, spectromics provides comprehensive information for early OA detection and disease stratification, imperative for effective intervention in treating the degenerative onset disease for an aging demographic. This novel and elegant approach for data fusion is compatible with various NIR-SWIR optical devices that will allow deep non-destructive penetration.

Topical Diclofenac Reduces Joint Synovitis in Hand Osteoarthritis: A Pilot Investigation Using Fluorescent Optical Imaging

Purpose

Synovitis, the inflammation of joint synovia, is a prominent feature of osteoarthritis (OA) manifested by enhanced synovial vascularity, endothelial leakage, and perivascular oedema. In this pilot study, we assessed the effect of topical diclofenac in hand OA (HOA) using the established semi-quantitative methods Magnetic Resonance Imaging (MRI) and Ultrasonography (US), and compared them with Fluorescent Optical Imaging (FOI), an emerging imaging modality.

Patients and Methods

Ten patients with symptomatic and diagnosed HOA used topical diclofenac for 14 days, with FOI, MRI, US, and subjective pain assessed at Baseline and after 7 (Day 8), and 14 (Day 15) days of treatment. Changes in synovitis were assessed for all 10 joints of the hand (via sum scores), and separately for the two joints most affected by synovitis. A new, fully quantitative approach for objective synovitis assessment based on the FOI images was also developed and applied.

Results

The semi-quantitative analysis of the sum scores showed a small decrease in synovitis throughout the treatment duration across the different imaging modalities. The effect of the treatment was more prominent on the two most affected joints, with a synovitis reduction vs Baseline of 21.1% and 34.2% on Day 8 and Day 15, respectively, in the FOI. The quantitative FOI pixel analysis further strengthened the evidence for this effect, with observed reduction of 17.8% and 42.4% for Days 8 and 15, respectively. A similar trend was observed for subjective pain perception, with a reduction of 7.2 and 13.3 mm on Days 8 and 15.

Conclusion

This pilot study evidenced the effect of topical diclofenac on reducing synovitis in hand OA in semi- and fully quantitative analyses, with the effect being stronger in the most affected joints. Further, supporting studies are needed to probe the accuracy of the quantitative pixel analysis of FOI images.

Time-efficient combined morphologic and quantitative joint MRI: an in situ study of standardized knee cartilage defects in human cadaveric specimens

BACKGROUND

Quantitative techniques such as T2 and T1ρ mapping allow evaluating the cartilage and meniscus. We evaluated multi-interleaved X-prepared turbo-spin echo with intuitive relaxometry (MIXTURE) sequences with turbo spin-echo (TSE) contrast and additional parameter maps versus reference TSE sequences in an in situ model of human cartilage defects.

METHODS

Standardized cartilage defects of 8, 5, and 3 mm in diameter were created in the lateral femora of ten human cadaveric knee specimens (81 ± 10 years old; nine males, one female). MIXTURE sequences providing proton density-weighted fat-saturated images and T2 maps or T1-weighted images and T1ρ maps as well as the corresponding two- and three-dimensional TSE reference sequences were acquired before and after defect creation (3-T scanner; knee coil). Defect delineability, bone texture, and cartilage relaxation times were quantified. Appropriate parametric or non-parametric tests were used.

RESULTS

Overall, defect delineability and texture features were not significantly different between the MIXTURE and reference sequences (p ≤ 0.47). After defect creation, relaxation times significantly increased in the central femur (T2pre = 51 ± 4 ms [mean ± standard deviation] versus T2post = 56 ± 4 ms; p = 0.002) and all regions combined (T1ρpre = 40 ± 4 ms versus T1ρpost = 43 ± 4 ms; p = 0.004).

CONCLUSIONS

MIXTURE permitted time-efficient simultaneous morphologic and quantitative joint assessment based on clinical image contrasts. While providing T2 or T1ρ maps in clinically feasible scan time, morphologic image features, i.e., cartilage defects and bone texture, were comparable between MIXTURE and reference sequences.

RELEVANCE STATEMENT

Equally time-efficient and versatile, the MIXTURE sequence platform combines morphologic imaging using familiar contrasts, excellent image correspondence versus corresponding reference sequences and quantitative mapping information, thereby increasing the diagnostic value beyond mere morphology.

KEY POINTS

• Combined morphologic and quantitative MIXTURE sequences are based on three-dimensional TSE contrasts. • MIXTURE sequences were studied in an in situ human cartilage defect model. • Morphologic image features, i.e., defect delineabilty and bone texture, were investigated. • Morphologic image features were similar between MIXTURE and reference sequences. • MIXTURE allowed time-efficient simultaneous morphologic and quantitative knee joint assessment.

Laser-irradiating infrared attenuated total reflection spectroscopy of articular cartilage: Potential and challenges for diagnosing osteoarthritis

Objective

A prototype infrared attenuated total reflection (IR-ATR) laser spectroscopic system designed for in vivo classification of human cartilage tissue according to its histological health status during arthroscopic surgery is presented. Prior to real-world in vivo applications, this so-called osteoarthritis (OA) scanner has been tested at in vitro conditions revealing the challenges associated with complex sample matrices and the accordingly obtained sparse spectral datasets.

Methods

In vitro studies on human knee cartilage samples at different contact pressures (i.e., 0.2-0.5 ​MPa) allowed recording cartilage degeneration characteristic IR signatures comparable to in vivo conditions with high temporal resolution. Afterwards, the cartilage samples were assessed based on the clinically acknowledged osteoarthritis cartilage histopathology assessment (OARSI) system and correlated with the obtained sparse IR data.

Results

Amide and carbohydrate signal behavior was observed to be almost identical between the obtained sparse IR data and previously measured FTIR data used for sparse partial least squares discriminant analysis (SPLSDA) to identify the spectral regions relevant to cartilage condition. Contact pressures between 0.3 and 0.4 ​MPa seem to provide the best sparse IR spectra for cylindrical (d ​= ​3 ​mm) probe tips.

Conclusion

Laser-irradiating IR-ATR spectroscopy is a promising analytical technique for future arthroscopic applications to differentiate healthy and osteoarthritic cartilage tissue. However, this study also revealed that the flexible connection between the laser-based analyzer and the arthroscopic ATR-probe via IR-transparent fiberoptic cables may affect the robustness of the obtained IR data and requires further improvements.

Two for One-Combined Morphologic and Quantitative Knee Joint MRI Using a Versatile Turbo Spin-Echo Platform

Quantitative MRI techniques such as T2 and T1ρ mapping are beneficial in evaluating knee joint pathologies; however, long acquisition times limit their clinical adoption. MIXTURE (Multi-Interleaved X-prepared Turbo Spin-Echo with IntUitive RElaxometry) provides a versatile turbo spin-echo (TSE) platform for simultaneous morphologic and quantitative joint imaging. Two MIXTURE sequences were designed along clinical requirements: "MIX1", combining proton density (PD)-weighted fat-saturated (FS) images and T2 mapping (acquisition time: 4:59 min), and "MIX2", combining T1-weighted images and T1ρ mapping (6:38 min). MIXTURE sequences and their reference 2D and 3D TSE counterparts were acquired from ten human cadaveric knee joints at 3.0 T. Contrast, contrast-to-noise ratios, and coefficients of variation were comparatively evaluated using parametric tests. Clinical radiologists (n = 3) assessed diagnostic quality as a function of sequence and anatomic structure using five-point Likert scales and ordinal regression, with a significance level of α = 0.01. MIX1 and MIX2 had at least equal diagnostic quality compared to reference sequences of the same image weighting. Contrast, contrast-to-noise ratios, and coefficients of variation were largely similar for the PD-weighted FS and T1-weighted images. In clinically feasible scan times, MIXTURE sequences yield morphologic, TSE-based images of diagnostic quality and quantitative parameter maps with additional insights on soft tissue composition and ultrastructure.

Pain Management Strategies in Osteoarthritis

Pain is the major symptom of osteoarthritis (OA) and is an important factor in strategies to manage this disease. However, the current standard of care does not provide satisfactory pain relief for many patients. The pathophysiology of OA is complex, and its presentation as a clinical syndrome is associated with the pathologies of multiple joint tissues. Treatment options are generally classified as pharmacologic, nonpharmacologic, surgical, and complementary and/or alternative, typically used in combination to achieve optimal results. The goals of treatment are the alleviation of symptoms and improvement in functional status. Several studies are exploring various directions for OA pain management, including tissue regeneration techniques, personalized medicine, and targeted drug therapies. The aim of the present narrative review is to extensively describe all the treatments available in the current practice, further describing the most important innovative therapies. Advancements in understanding the molecular and genetic aspects of osteoarthritis may lead to more effective and tailored treatment approaches in the future.

[Current MR imaging of cartilage in the context of knee osteoarthritis (part 1) : Principles and sequences]

Magnetic resonance imaging (MRI) is the clinical method of choice for cartilage imaging in the context of degenerative and nondegenerative joint diseases. The MRI-based definitions of osteoarthritis rely on the detection of osteophytes, cartilage pathologies, bone marrow edema and meniscal lesions but currently a scientific consensus is lacking. In the clinical routine proton density-weighted, fat-suppressed 2D turbo spin echo sequences with echo times of 30-40 ms are predominantly used, which are sufficiently sensitive and specific for the assessment of cartilage. The additionally acquired T1-weighted sequences are primarily used for evaluating other intra-articular and periarticular structures. Diagnostically relevant artifacts include magic angle and chemical shift artifacts, which can lead to artificial signal enhancement in cartilage or incorrect representations of the subchondral lamina and its thickness. Although scientifically validated, high-resolution 3D gradient echo sequences (for cartilage segmentation) and compositional MR sequences (for quantification of physical tissue parameters) are currently reserved for scientific research questions. The future integration of artificial intelligence techniques in areas such as image reconstruction (to reduce scan times while maintaining image quality), image analysis (for automated identification of cartilage defects), and image postprocessing (for automated segmentation of cartilage in terms of volume and thickness) will significantly improve the diagnostic workflow and advance the field further.

Retrospective study of synovial chondromatosis of the temporomandibular joint: clinical and histopathologic analysis and the early-stage imaging features

OBJECTIVE

Herein, we aimed to study the clinical, radiographical, and histopathologic features of synovial chondromatosis in the temporomandibular joint (SC in TMJ) and provide references for early diagnosis and treatment prognosis.

STUDY DESIGN

The medical records and imaging examinations of patients with SC in TMJ, diagnosed using postoperative histopathologic examination, were reviewed and analyzed. Among them, 18 cases who lacked calcified loose bodies on spiral computed tomography or cone beam computed tomography (SCT/CBCT) were selected for further study. Descriptive statistical methods were used to analyze the clinical characteristics of patients.

RESULTS

The study included 100 patients with SC in TMJ, who were predominantly female (male to female: 1:3), and were aged from 21 to 77 years (median, 47). Radiopaque calcified lesions on SCT/CBCT were missing in 18 cases, but cartilaginous nodules were observed during surgery. The cases lacking calcification had a relatively shorter disease course, suggesting they were in the early stages of SC.

CONCLUSION

In the early stage of SC, although calcified loose bodies cannot be detected on SCT/CBCT, attention should be paid to the widening of the posterior superior joint space and sclerosis or slight erosion of the joint fossa. Magnetic resonance imaging would be helpful to detect the early-stage SC in TMJ.

A rapid VEGF-gene-sequence photoluminescence detector for osteoarthritis

Osteoarthritis (OA) has become a serious problem to the human society for years due to its high economic burden, disability, pain, and severe impact on the patient's lifestyle. The importance of current clinical imaging modalities in the assessment of the onset and progression of OA is well recognized by clinicians, but these modalities can only detect OA in the II stage with significant structural deterioration and clinical symptoms. Blood vessel formation induced by vascular endothelial growth factor (VEGF) occurs in the early stage and throughout the entire course of OA, enables VEGF relating gene sequence to act as a biomarker in the field of early diagnosis and monitoring of the disease. Here in, a facile rapid detection of VEGF relating ssDNA sequence was developed, in which manganese-based zeolitic imidazolate framework nanoparticles (Mn-ZIF-NPs) were synthesized by a simple coprecipitation strategy, followed by the introduction and surficial absorption of probe ssDNAs and the CRISPR/Cas12a system components. Furthermore, fluorescence experiments demonstrated that the biosensor displayed a low detection limit of 2.49 nM, a good linear response to the target ssDNA ranging from 10 nM to 500 nM, and the ability of distinguishing single nucleotide polymorphism. This finding opens a new window for the feasible and rapid detection of ssDNA molecules for the early diagnose of OA.

A proposed modification to the Kellgren and Lawrence classification for knee osteoarthritis using a compartment-specific approach

Purpose

Since Kellgren and Lawrence (KL) originally classified knee osteoarthritis, several authors have reported varying levels of reliability and a lack of uniformity in the use of this classification system. We propose several modifications to the KL classification including the use of a compartment-specific approach that we hypothesize will lead to a better understanding of knee OA while maintaining an adequate interobserver and intraobserver reliability.

Methods

We propose the addition of the lateral and skyline-view radiographs to the standard anteroposterior (AP) and lateral projections in the evaluation. Also suggest a more precise definition of the evaluated parameters; the addition of the subchondral cancellous bone as parameter of evaluation; and the assessment of medial tibiofemoral compartment (MTFC), lateral tibiofemoral compartment (LTFC) and patellofemoral compartment (PFC) separately resulting in a compartment-specific KL staging score rather than a single overall KL score. Six evaluators (two knee surgeons, two radiologists and two knee fellows) used the modified KL classification to classify 230 randomly selected knees on two separate occasions. Reliabilities were assessed by calculating Krippendorff's ⍺ coefficients.

Results

Two hundred and ten knees were included for final evaluation and analyses (53% left knees; 65% females; mean age 56 years old). Average interobserver reliability was moderate for all compartments (0.51 for the MTFC; 0.51 for the LTFC; and 0.56 for the PFC). Average intraobserver reliability was substantial for all compartments (0.63 for the MTFC; 0.65 for the LTFC; and 0.7 for the PFC). Experienced evaluators showed a higher intraobserver reliability than less-experienced evaluators.

Conclusions

A modified compartment-specific KL classification enables a practical and detailed description of knee OA involvement and demonstrates acceptable interobserver and intraobserver reliability. Level of Evidence: Level III.

Recent advances in polymeric microparticle-based drug delivery systems for knee osteoarthritis treatment

Due to the poor bioavailability and high joint clearance of drugs, sustained delivery of therapeutic agents has proven difficult in the treatment of osteoarthritis (OA). Intra-articular (IA) drug delivery strategy is an attractive option for enhancing OA patients' prognosis, for which various polymer materials have been used as drug carriers due to their attractive delivery properties, to slow or even reverse the progress of OA by prolonging the duration of therapeutic agent residence in the joint. This article focuses on the recent developments in natural and synthetic polymer-based microsphere drug delivery systems for treating knee osteoarthritis. It evaluates the translational potential of some novel formulations for clinical application.

Improving Image Classification of Knee Radiographs: An Automated Image Labeling Approach

Large numbers of radiographic images are available in musculoskeletal radiology practices which could be used for training of deep learning models for diagnosis of knee abnormalities. However, those images do not typically contain readily available labels due to limitations of human annotations. The purpose of our study was to develop an automated labeling approach that improves the image classification model to distinguish normal knee images from those with abnormalities or prior arthroplasty. The automated labeler was trained on a small set of labeled data to automatically label a much larger set of unlabeled data, further improving the image classification performance for knee radiographic diagnosis. We used BioBERT and EfficientNet as the feature extraction backbone of the labeler and imaging model, respectively. We developed our approach using 7382 patients and validated it on a separate set of 637 patients. The final image classification model, trained using both manually labeled and pseudo-labeled data, had the higher weighted average AUC (WA-AUC 0.903) value and higher AUC values among all classes (normal AUC 0.894; abnormal AUC 0.896, arthroplasty AUC 0.990) compared to the baseline model (WA-AUC = 0.857; normal AUC 0.842; abnormal AUC 0.848, arthroplasty AUC 0.987), trained using only manually labeled data. Statistical tests show that the improvement is significant on normal (p value < 0.002), abnormal (p value < 0.001), and WA-AUC (p value = 0.001). Our findings demonstrated that the proposed automated labeling approach significantly improves the performance of image classification for radiographic knee diagnosis, allowing for facilitating patient care and curation of large knee datasets.

Identification of key genes and their correlation with immune infiltration in osteoarthritis using integrative bioinformatics approaches and machine-learning strategies

Osteoarthritis (OA) is a common degenerative joint disease and is closely associated with chronic, low-grade inflammation. Regulating ferroptosis by targeting ferroptosis-related genes may be a fast and effective way to delay the degeneration of OA. However, the molecular mechanisms and gene targets related to ferroptosis in OA are still unclear. Data of OA samples from 3 gene expression omnibus (GEO) datasets were combined to identify differentially expressed genes (DEGs). Ferroptosis-related genes (FRGs) retrieved by the Ferroptosis database were intersected with DEGs, and the intersected hub genes were used for functional enrichment analysis. The feature genes were obtained from the least absolute shrinkage and selection operator (LASSO) algorithm, support vector machine recursive feature elimination (SVM-RFE) algorithm, and random forest (RF) algorithm. Single sample gene set enrichment analysis (ssGSEA) was used to compare immune infiltration between OA patients and normal controls, and the correlation between feature genes and immune cells was analyzed. The expression levels of feature genes were confirmed by RT-PCR. In addition, to explore the applicability of these genes, we extended the bioinformatics analysis of these feature genes to cancer. Finally, 4 feature genes, GABARAPL1, TNFAIP3, ARNTL, and JUN, were confirmed in OA. Theirs expression level were validated by RT-PCR. ROC curves of the 4 genes exhibit excellent diagnostic efficiency for OA, suggesting that the 4 genes were associated with the pathogenesis of OA. Another GEO dataset validated this result. Further analysis revealed that the 4 feature genes were all closely related to the immune infiltration cells in OA. Additionally, results of prognosis analysis indicated that JUN might be a promising therapeutic target for cancer. GABARAPL1, TNFAIP3, ARNTL, and JUN may be predicted biomarkers for OA. The feature genes and association between feature genes and immune infiltration may provide potential biomarkers for OA prediction along with the better assessment of the disease.

MRI overestimates articular cartilage thickness and volume compared to synchrotron radiation phase-contrast imaging

Accurate evaluation of morphological changes in articular cartilage are necessary for early detection of osteoarthritis (OA). 3T magnetic resonance imaging (MRI) has highly sensitive contrast resolution and is widely used clinically to detect OA. However, synchrotron radiation phase-contrast imaging computed tomography (SR-PCI) can also provide contrast to tissue interfaces that do not have sufficient absorption differences, with the added benefit of very high spatial resolution. Here, MRI was compared with SR-PCI for quantitative evaluation of human articular cartilage. Medial tibial condyles were harvested from non-OA donors and from OA patients receiving knee replacement surgery. Both imaging methods revealed that average cartilage thickness and cartilage volume were significantly reduced in the OA group, compared to the non-OA group. When comparing modalities, the superior resolution of SR-PCI enabled more precise mapping of the cartilage surface relative to MRI. As a result, MRI showed significantly higher average cartilage thickness and cartilage volume, compared to SR-PCI. These data highlight the potential for high-resolution imaging of articular cartilage using SR-PCI as a solution for early OA diagnosis. Recognizing current limitations of using a synchrotron for clinical imaging, we discuss its nascent utility for preclinical models, particularly longitudinal studies of live animal models of OA.

Clinical Outcome of Minimally Manipulated, Mechanically Isolated Autologous Adipose Tissue-Derived Stromal Vascular Fraction (Sahaj Therapy®) in Knee Osteoarthritis-Randomized Controlled Trial

Introduction

Regenerative therapy has shown promising results in the treatment of osteoarthritis (OA) knee with Kellgren-Lawrence (KL) Grades I-III. We compared the safety, efficacy, functional, and clinical outcomes of intra-articular implantation of autologous adipose tissue-derived stromal vascular fraction (SVF) isolated using direct ultrasonic cavitation (Sahaj therapy-Cell Innovation Patented Technology) and saline injection in knee osteoarthritis.

Materials and Methods

The present prospective observational study was conducted over 3 years. We enrolled 120 patients in our study, where four patients got excluded as they did not meet the inclusion criteria. The remaining 116 patients were randomized into two groups, one with autologous adipose tissue-derived SVF and the other group with saline injection. A comparison of mean KOOS and VAS scores at different follow-ups was done using Paired 't' test. A p value of < 0.05 was considered significant.

Results

The results show that the SVF group had significantly higher KOOS scores (78.49 ± 6.54 in the SVF group vs 59.19 ± 5.14 in the saline group), respectively (p < 0.001). Similarly, the SVF group had significantly lesser VAS scores (3.17 ± 0.94 in the SVF group vs 3.89 ± 1.04 in the saline group), respectively (p < 0.001).

Conclusions

Autologous adipose tissue-derived SVF is a better choice for treating knee osteoarthritis. For individuals with degenerative osteoarthritis, autologous SVF grafting in the same surgical procedure is an innovative and promising treatment modality. Even after 3 years of follow-up, the study participants with OA knee have shown a good clinical and functional outcome.

Charcot Neuroarthropathy of the Foot and Ankle in the Acute Setting: An Illustrative Case Report and Targeted Review

Charcot neuroarthropathy (CN) is a rare but serious sequela of diabetes and other diseases that cause peripheral neuropathy. It is most commonly characterized by degeneration of the foot and/or ankle joints leading to progressive deformity and altered weight-bearing. If left untreated, the deformities of CN lead to ulceration, infection, amputation, and even death. Because of the associated peripheral neuropathy and proprioception deficits that accompany CN, patients typically do not perceive the onset of joint destruction. Moreover, in the hands of the untrained clinician, the initial presentation of CN can easily be mistaken for infection, osteoarthritis, gout, or inflammatory arthropathy. Misdiagnosis can lead to the aforementioned serious sequelae of CN. Thus, an early accurate diagnosis and off-loading of the involved extremity, followed by prompt referral to a specialist trained in the care of CN are crucial to prevent the late-term sequelae of the disease. The purpose of this article was to create an opportunity for enhanced understanding between orthopedic surgeons and emergency physicians, to improve patient care through the optimization of diagnosis and early management of CN in the emergent setting.

A Novel Tool for Collaborative and Blinded Orthopedic Image Analysis

Image analysis plays a central role in orthopedics and research but comes with many challenges, including anonymization, bias, and achieving efficient analyses using multiple independent observers. Appropriate software is still lacking. Tyche is a free online tool that displays images in a random order without showing any metadata. Additionally, when using Tyche, observers can store results in the same window, and the final results are immediately visible to the project manager. In this study, we compared results from Tyche with those from a validated tool. One hundred pelvic radiographs were analyzed separately by five orthopedic surgeons using both Tyche and the validated software. Common orthopedic measurement modalities and scores were determined. The methods were compared using intra-class correlations and Fleiss' kappa coefficients as well as Bland-Altman plots. Significant correlations ranging from r = 0.17 (Kallgren and Lawrence Score) to r = 0.99 (area measurements) were calculated for inter- and intraobserver agreements between the two tools for all measurements. The Bland-Altman plots indicated the non-inferiority of either tool. The images were analyzed significantly faster when Tyche was used. We conclude that Tyche is a valid tool for use in orthopedic image analysis. Tyche could be utilized for determining inter- and intraobserver agreements, in multicenter studies and for score validations.

Platelet-Rich Plasma Power-Mix Gel (ppm)-An Orthobiologic Optimization Protocol Rich in Growth Factors and Fibrin

Platelet- and fibrin-rich orthobiologic products, such as autologous platelet concentrates, have been extensively studied and appreciated for their beneficial effects on multiple conditions. Platelet-rich plasma (PRP) and its derivatives, including platelet-rich fibrin (PRF), have demonstrated encouraging outcomes in clinical and laboratory settings, particularly in the treatment of musculoskeletal disorders such as osteoarthritis (OA). Although PRP and PRF have distinct characteristics, they share similar properties. The relative abundance of platelets, peripheral blood cells, and molecular components in these orthobiologic products stimulates numerous biological pathways. These include inflammatory modulation, augmented neovascularization, and the delivery of pro-anabolic stimuli that regulate cell recruitment, proliferation, and differentiation. Furthermore, the fibrinolytic system, which is sometimes overlooked, plays a crucial role in musculoskeletal regenerative medicine by regulating proteolytic activity and promoting the recruitment of inflammatory cells and mesenchymal stem cells (MSCs) in areas of tissue regeneration, such as bone, cartilage, and muscle. PRP acts as a potent signaling agent; however, it diffuses easily, while the fibrin from PRF offers a durable scaffolding effect that promotes cell activity. The combination of fibrin with hyaluronic acid (HA), another well-studied orthobiologic product, has been shown to improve its scaffolding properties, leading to more robust fibrin polymerization. This supports cell survival, attachment, migration, and proliferation. Therefore, the administration of the "power mix" containing HA and autologous PRP + PRF may prove to be a safe and cost-effective approach in regenerative medicine.

Proteoglycans in Articular Cartilage and Their Contribution to Chondral Injury and Repair Mechanisms

Proteoglycans are vital components of the extracellular matrix in articular cartilage, providing biomechanical properties crucial for its proper functioning. They are key players in chondral diseases, specifically in the degradation of the extracellular matrix. Evaluating proteoglycan molecules can serve as a biomarker for joint degradation in osteoarthritis patients, as well as assessing the quality of repaired tissue following different treatment strategies for chondral injuries. Despite ongoing research, understanding osteoarthritis and cartilage repair remains unclear, making the identification of key molecules essential for early diagnosis and effective treatment. This review offers an overview of proteoglycans as primary molecules in articular cartilage. It describes the various types of proteoglycans present in both healthy and damaged cartilage, highlighting their roles. Additionally, the review emphasizes the importance of assessing proteoglycans to evaluate the quality of repaired articular tissue. It concludes by providing a visual and narrative description of aggrecan distribution and presence in healthy cartilage. Proteoglycans, such as aggrecan, biglycan, decorin, perlecan, and versican, significantly contribute to maintaining the health of articular cartilage and the cartilage repair process. Therefore, studying these proteoglycans is vital for early diagnosis, evaluating the quality of repaired cartilage, and assessing treatment effectiveness.

Histological features of knee osteoarthritis treated with triamcinolone acetonide and hyaluronic acid

Osteoarthritis (OA) is one of the most common degenerative joint diseases leading to disability in the end stage. Although intra-articular triamcinolone acetonide (TA) is one of the OA treatments that have been widely used, the side effects of such corticosteroids are still controversial. Intra-articular hyaluronic acid (HA) injection is another therapeutic option for patients with OA who do not want to use corticosteroids because of their side effects. However, the difference between the histological features associated with TA and HA in the treatment of OA remains unclear. Thus, the present study aimed to compare the histological effects of TA and HA on the cartilage of patients with knee OA. In the current study, 31 patients diagnosed with grade 3-4 knee OA on the Kellgren-Lawrence radiographic grading scale were separated into three groups: TA (n=12); HA (n=7) and untreated group (n=12). Histological examination of the whole articular cartilages of the patients was performed with hematoxylin and eosin and Alcian staining, as well as using a TUNEL assay. Clinical data such as cartilage thickness, structural and component deterioration, proteoglycan levels, apoptosis and empty lacunae were compared between the three groups. The results showed a high level of deterioration in both TA and HA groups but not in the untreated group, although the thickness of cartilage in the HA group was lower compared with that in the TA and untreated groups. The proteoglycan levels in the TA group were lower compared with those in the HA group. Moreover, the number of empty lacunae in the HA group was higher compared with that in the TA group, while no difference in apoptosis was found between TA and HA groups. A significant difference was not found in the histological staining between TA and HA groups. On the other hand, a significant difference was found in cartilage deterioration between the medial and lateral sides in these groups. TA and HA groups showed comparable histological results. TA injection is cheaper and easier but has more adverse effects for patients with knee OA than HA injection. Therefore, orthopaedists should select TA or HA based on the economic and specific needs of patients.

The role of imaging in osteoarthritis

Osteoarthritis is a complex whole-organ disorder that involves molecular, anatomic, and physiologic derangement. Advances in imaging techniques have expanded the role of imaging in evaluating osteoarthritis and functional changes. Radiography, magnetic resonance imaging, computed tomography (CT), and ultrasonography are commonly used imaging modalities, each with advantages and limitations in evaluating osteoarthritis. Radiography comprehensively analyses alignment and osseous features, while MRI provides detailed information about cartilage damage, bone marrow edema, synovitis, and soft tissue abnormalities. Compositional imaging derives quantitative data for detecting cartilage and tendon degeneration before structural damage occurs. Ultrasonography permits real-time scanning and dynamic joint evaluation, whereas CT is useful for assessing final osseous detail. Imaging plays an essential role in the diagnosis, management, and research of osteoarthritis. The use of imaging can help differentiate osteoarthritis from other diseases with similar symptoms, and recent advances in deep learning have made the acquisition, management, and interpretation of imaging data more efficient and accurate. Imaging is useful in monitoring and predicting the prognosis of osteoarthritis, expanding our understanding of its pathophysiology. Ultimately, this enables early detection and personalized medicine for patients with osteoarthritis. This article reviews the current state of imaging in osteoarthritis, focusing on the strengths and limitations of various imaging modalities, and introduces advanced techniques, including deep learning, applied in clinical practice.

Clinical aspects and outcomes in osteoarthritis

Osteoarthritis (OA) is the most prevalent type of arthritis worldwide, and its incidence significantly increases with age. It commonly affects the knees, hips, spine, big toes, and hands. OA can be identified through clinical examination, symptoms, and imaging methods. Its main symptoms include pain, stiffness, and limitations in joint movement. Examinations may reveal coarse crepitus, bony enlargement, and tenderness at the joint line. In severe cases of OA, rest pain, night pain, and deformity may occur. OA can lead to decreased physical activity, function, and quality of life due to symptoms such as pain and stiffness. To evaluate these impacts, patient-reported outcome measures (PROMs) are necessary. Various generic, disease-specific, and joint-specific PROMs have been developed and used in clinical practice to assess the outcomes of OA.

Indications of musculoskeletal health in deceased male individuals with lower-limb amputations: comparison to non-amputee and diabetic controls

Individuals with lower-limb amputations, many of whom have type 2 diabetes, experience impaired musculoskeletal health. This study: (1) compared residual and intact limbs of diabetic and non-diabetic post-mortem individuals with amputation to identify structures vulnerable to injury, and (2) compared findings to diabetic and healthy control groups to differentiate influences of amputation and diabetes on musculoskeletal health. Postmortem CT scans of three groups, ten individuals each, were included: (1) individuals with transtibial or transfemoral amputations, half with diabetes (2) diabetic controls, and (3) healthy controls. Hip and knee joint spaces, cross-sectional thigh muscle and fat areas, and cross-sectional bone properties (e.g. area, thickness, geometry) were measured. Wilcoxon Signed-Rank and Kruskal-Wallis tests assessed statistical significance. Asymmetry percentages between limbs assessed clinical significance. Residual limbs of individuals with amputation, particularly those with diabetes, had significantly less thigh muscle area and thinner distal femoral cortical bone compared to intact limbs. Compared to control groups, individuals with amputation had significantly narrower joint spaces, less thigh muscle area bilaterally, and thinner proximal femoral cortical bone in the residual limb. Diabetic individuals with amputation had the most clinically significant asymmetry. Findings tended to align with those of living individuals. However, lack of available medical information and small sample sizes reduced the anticipated clinical utility. Larger sample sizes of living individuals are needed to assess generalizability of findings. Quantifying musculoskeletal properties and differentiating influences of amputation and diabetes could eventually help direct rehabilitation techniques.

Point-of-Care Testing of the MTF1 Osteoarthritis Biomarker Using Phenolphthalein-Soaked Swabs

Osteoarthritis (OA) is the most common joint disease, which accompanies pain and inconvenience in daily life owing to degradation of cartilage and adjacent tissues. In this study, we propose a simple point-of-care testing (POCT) kit for the detection of the MTF1 OA biomarker to achieve on-site clinical diagnosis of OA. The kit contains an FTA card for patient sample treatments, a sample tube for loop-mediated isothermal amplification (LAMP), and a phenolphthalein-soaked swab for naked eye detection. The MTF1 gene was isolated from synovial fluids using an FTA card and amplified using the LAMP method at 65 °C for 35 min. A test part of the phenolphthalein-soaked swab was decolorized in the presence of the MTF1 gene due to the pH change after the LAMP, but the color remained pink in the absence of the MTF1 gene. The control part of the swab served as a reference color in relation to the test part. When real-time LAMP (RT-LAMP), gel electrophoresis, and colorimetric detection of the MTF1 gene were performed, the limit of detection (LOD) was confirmed at 10 fg/μL, and the overall processes were completed in 1 h. The detection of an OA biomarker in the form of POCT was reported for the first time in this study. The introduced method is expected to serve as a POCT platform directly applicable by clinicians for easy and rapid identification of OA.

The prevalence of hip osteoarthritis: a systematic review and meta-analysis

OBJECTIVE

To estimate the global prevalence of hip osteoarthritis (HOA) through a systematic review and meta-analysis, and to determine by regression analysis the respective relationships between age and sex, and sex and prevalence.

METHODS

EMBASE, PubMed, Web of science, CINAHL, and SCOPUS were searched from inception until August 2022. Two authors independently extracted data and assessed the quality of the retrieved literature. Random-effects meta-analysis was performed to derive the pooled prevalence. Variations in the prevalence estimate in different subgroups, including diagnostic methods, region, and patient sex, were examined by subgroup meta-analysis. Meta-regression was used to construct the age-specific prevalence of HOA.

RESULTS

A total of 31 studies were included in our analysis, involving 326,463 participants. Quality evaluation showed that all studies included in the analysis had a Quality Score of at least 4. The most frequently used method for diagnosing HOA was the Kellgren-Lawrence (K-L) grade classification, accounting for 19/31 (61.3%) studies. The pooled prevalence of HOA diagnosed based on the K-L grade ≥ 2 criterion was 8.55% (95% CI 4.85-13.18) worldwide. The prevalence of HOA was lowest in Africa at 1.20% (95% CI: 0.40-2.38), followed by Asia at 4.26% (95% CI 0.02-14.93) and North America at 7.95% (95% CI 1.98-17.36), and highest in Europe at 12.59% (95% CI 7.17-19.25). There was no statistically significant difference in HOA prevalence between men (9.42%, 95% CI:4.81-15.34) and women at (7.94%, 95% CI: 3.57-13.81). The regression model showed a correlation between age and the prevalence of HOA.

CONCLUSION

HOA has high prevalence worldwide and increases with age. The prevalence varies significantly by region but not by patient sex. High-quality epidemiological studies are warranted to more accurately estimate the prevalence of HOA.

Construction of a Diagnostic m7G Regulator-Mediated Scoring Model for Identifying the Characteristics and Immune Landscapes of Osteoarthritis

With the increasingly serious burden of osteoarthritis (OA) on modern society, it is urgent to propose novel diagnostic biomarkers and differentiation models for OA. 7-methylguanosine (m7G), as one of the most common base modification forms in post transcriptional regulation, through which the seventh position N of guanine (G) of messenger RNA is modified by methyl under the action of methyltransferase; it has been found that it plays a crucial role in different diseases. Therefore, we explored the relationship between OA and m7G. Based on the expression level of 18 m7G-related regulators, we identified nine significant regulators. Then, via a series of methods of machine learning, such as support vector machine recursive feature elimination, random forest and lasso-cox regression analysis, a total of four significant regulators were further identified (DCP2, EIF4E2, LARP1 and SNUPN). Additionally, according to the expression level of the above four regulators, two different m7G-related clusters were divided via consensus cluster analysis. Furthermore, via immune infiltration, differential expression analysis and enrichment analysis, we explored the characteristic of the above two different clusters. An m7G-related scoring model was constructed via the PCA algorithm. Meanwhile, there was a different immune status and correlation for immune checkpoint inhibitors between the above two clusters. The expression difference of the above four regulators was verified via real-time quantitative polymerase chain reaction. Overall, a total of four biomarkers were identified and two different m7G-related subsets of OA with different immune microenvironment were obtained. Meanwhile, the construction of m7G-related Scoring model may provide some new strategies and insights for the therapy and diagnosis of OA patients.

Localized Multi-Site Knee Bioimpedance as a Predictor for Knee Osteoarthritis Associated Pain Within Older Adults During Free-Living

The drastic increase in the aging population has increased the prevalence of osteoarthritis in the United States. The ability to monitor symptoms of osteoarthritis (such as pain) within a free-living environment could improve understanding of each person's experiences with this disease and provide opportunities to personalize treatments specific to each person and their experience. In this work, localized knee tissue bioimpedance and self-reports of knee pain were collected from older adults ([Formula: see text]) with and without knee osteoarthritis over 7 days of free-living to evaluate if knee tissue bioimpedance is associated with persons' knee pain experience. Within the group of persons' with knee osteoarthritis increases in 128 kHz per-length resistance and decreases in 40 kHz per-length reactance were associated with increased probability of persons having active knee pain ([Formula: see text] and [Formula: see text]).

Getting Cartilage Thickness Measurements Right: A Systematic Inter-Method Comparison Using MRI Data from the Osteoarthritis Initiative

OBJECTIVE

Magnetic resonance imaging is the standard imaging modality to assess articular cartilage. As the imaging surrogate of degenerative joint disease, cartilage thickness is commonly quantified after tissue segmentation. In lack of a standard method, this study systematically compared five methods for automatic cartilage thickness measurements across the knee joint and as a function of region and sub-region: 3D mesh normals (3D-MN), 3D nearest neighbors (3D-NN), 3D ray tracing (3D-RT), 2D centerline normals (2D-CN), and 2D surface normals (2D-SN).

DESIGN

Based on the manually segmented femoral and tibial cartilage of 507 human knee joints, mean cartilage thickness was computed for the entire femorotibial joint, 4 joint regions, and 20 subregions using these methods. Inter-method comparisons of mean cartilage thickness and computation times were performed by one-way analysis of variance (ANOVA), Bland-Altman analyses and Lin's concordance correlation coefficient (CCC).

RESULTS

Mean inter-method differences in cartilage thickness were significant in nearly all subregions (P < 0.001). By trend, mean differences were smallest between 3D-MN and 2D-SN in most (sub)regions, which is also reflected by highest quantitative inter-method agreement and CCCs. 3D-RT was prone to severe overestimation of up to 2.5 mm. 3D-MN, 3D-NN, and 2D-SN required mean processing times of ≤5.3 s per joint and were thus similarly efficient, whereas the time demand of 2D-CN and 3D-RT was much larger at 133 ± 29 and 351 ± 10 s per joint (P < 0.001).

CONCLUSIONS

In automatic cartilage thickness determination, quantification accuracy and computational burden are largely affected by the underlying method. Mesh and surface normals or nearest neighbor searches should be used because they accurately capture variable geometries while being time-efficient.

ssDNA-Modified Gold Nanoparticles as a Tool to Detect miRNA Biomarkers in Osteoarthritis

Recently, miRNAs have been established as promising, specific biomarkers for the diagnosis of many diseases, including osteoarthritis. Herein, we report a ssDNA-based detection method for miRNAs implicated in osteoarthritis, specifically, miR-93 and miR-223. In this study, gold nanoparticles (AuNPs) were modified with oligonucleotide ssDNA to detect miRNAs circulating in the blood in healthy subjects and patients suffering from osteoarthritis. The detection method was based on the colorimetric and spectrophotometric assessment of biofunctionalized AuNPs upon interaction with the target and their subsequent aggregation. Results showed that these methods could be used to detect easily and rapidly miR-93 but not miR-223 in osteoarthritic patients, and they could potentially be used as a diagnostic tool for blood biomarkers. Visual-based detection as well as spectroscopic methods are simple, rapid, and label-free, due to which they can be used as a diagnostic tool.

Sustained release resolvin D1 liposomes are effective in the treatment of osteoarthritis in obese mice

Osteoarthritis (OA) is the most common joint disorder and currently affects >500 million patients worldwide, with ~60% of them also suffering from obesity. There is no drug approved for human use that changes the course of OA progression. OA is one of the most common comorbidities of obesity, and obesity-related OA (ObOA) is a serious health concern because it shows heightened severity of tissue damage and also predominantly affects the working population. Unresolved inflammation is a major driver of ObOA, thus, resolving disease-associated inflammation is a viable strategy to treat ObOA. Resolvins are highly potent molecules that play a role in the resolution of inflammation and promote tissue healing. However, small molecules (like Resolvin D1; RvD1) have to be administered frequently or prior to injury because they lose their in vivo activity rapidly either by lymphatic clearance, or oxidation-mediated deactivation. In this study, we have encapsulated RvD1 in liposomes and established its efficacy in the mouse model of ObOA at much lower dosages than freely administered RvD1. Liposomal RvD1 (lipo-RvD1) acted as a source of the RvD1 molecules for ~11 days in vitro in synovial fluid derived from patients. When administered prophylactically or therapeutically, lipo-RvD1 suppressed cartilage damage in male C57BL/6 mice compared to untreated and free RvD1 treatments. This efficacy was achieved by increasing the proportion of the proresolution M2 macrophages over proinflammatory M1 macrophages in the synovial membrane. These results show the potential of lipo-RvD1 as an anti-OA agent.