Early diagnosis to enable early treatment of pre-osteoarthritis

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.

Case report: Equine metacarpophalangeal joint partial and full thickness defects treated with allogenic equine synovial membrane mesenchymal stem/stromal cell combined with umbilical cord mesenchymal stem/stromal cell conditioned medium

Here, we describe a case of a 5-year-old show-jumping stallion presented with severe lameness, swelling, and pain on palpation of the left metacarpophalangeal joint (MCj). Diagnostic imaging revealed full and partial-thickness articular defects over the lateral condyle of the third metacarpus (MC3) and the dorsolateral aspect of the first phalanx (P1). After the lesion's arthroscopic curettage, the patient was subjected to an innovative regenerative treatment consisting of two intra-articular injections of equine synovial membrane mesenchymal stem/stromal cells (eSM-MSCs) combined with umbilical cord mesenchymal stem/stromal cells conditioned medium (UC-MSC CM), 15 days apart. A 12-week rehabilitation program was accomplished, and lameness, pain, and joint effusion were remarkably reduced; however, magnetic resonance imaging (MRI) and computed tomography (CT) scan presented incomplete healing of the MC3's lesion, prompting a second round of treatment. Subsequently, the horse achieved clinical soundness and returned to a higher level of athletic performance, and imaging exams revealed the absence of lesions at P1, fulfillment of the osteochondral lesion, and cartilage-like tissue formation at MC3's lesion site. The positive outcomes suggest the effectiveness of this combination for treating full and partial cartilage defects in horses. Multipotent mesenchymal stem/stromal cells (MSCs) and their bioactive factors compose a novel therapeutic approach for tissue regeneration and organ function restoration with anti-inflammatory and pro-regenerative impact through paracrine mechanisms.

Old Before Their Time? The Impact of Osteoarthritis on Younger Adults

OBJECTIVE

Osteoarthritis (OA) is frequently perceived as a disease of the elderly and an inevitable result of aging. Because OA studies often are restricted to older adults, there is limited information on OA in younger adults. This study describes the burden of OA across a wide age range and compares younger and older adults.

METHODS

Descriptive analysis of the Survey on Living with Chronic Diseases in Canada - Arthritis Component, a nationally representative survey of Canadians ≥20 years who reported an arthritis diagnosis in the Canadian Community Health Survey, a general health population survey. Analyses were restricted to those reporting OA and no other kind of arthritis (n = 1,749).

RESULTS

In the representative group with OA, 55.4% were younger than 65 years. The mean age at diagnosis was 50 years, with 30.4% reporting being diagnosed before age 45 years. Younger adults reported similar symptom severity as their older counterparts with OA regarding the mean number of affected joint sites, severity of pain and fatigue, and activity limitations. In the youngest age group, those with OA were significantly more likely to report fair or poor overall and mental health and life dissatisfaction compared with their general counterparts; the same was not the case in the oldest age group.

CONCLUSION

OA is not uncommon among younger and middle-aged adults, and they experience OA impacts comparable with those for older adults. These findings suggest that younger adults with OA will live many years with symptoms and disability and highlight a need for effective OA management across ages.

Reproducibility of Quantitative Double-Echo Steady-State T2 Mapping of Knee Cartilage

BACKGROUND

Cartilage T2 can detect joints at risk of developing osteoarthritis. The quantitative double-echo steady state (qDESS) sequence is attractive for knee cartilage T2 mapping because of its acquisition time of under 5 minutes. Understanding the reproducibility errors associated with qDESS T2 is essential to profiling the technical performance of this biomarker.

PURPOSE

To examine the combined acquisition and segmentation reproducibility of knee cartilage qDESS T2 using two different regional analysis schemes: 1) manual segmentation of subregions loaded during common activities and 2) automatic subregional segmentation.

STUDY TYPE

Prospective.

SUBJECTS

11 uninjured participants (age: 28 ± 3 years; 8 (73%) female).

FIELD STRENGTH/SEQUENCE

3-T, qDESS.

ASSESSMENT

Test-retest T2 maps were acquired twice on the same day and with a 1-week interval between scans. For each acquisition, average cartilage T2 was calculated in four manually segmented regions encompassing tibiofemoral contact areas during common activities and 12 automatically segmented regions from the deep-learning open-source framework for musculoskeletal MRI analysis (DOSMA) encompassing medial and lateral anterior, central, and posterior tibiofemoral regions. Test-retest T2 values from matching regions were used to evaluate reproducibility.

STATISTICAL TESTS

Coefficients of variation (%CV), root-mean-square-average-CV (%RMSA-CV), and intraclass correlation coefficients (ICCs) assessed test-retest T2 reproducibility. The median of test-retest standard deviations was used for T2 precision. Bland-Altman (BA) analyses examined test-retest biases. The smallest detectable difference (SDD) was defined as the BA limit of agreement of largest magnitude. Significance was accepted for P < 0.05.

RESULTS

All cartilage regions across both segmentation schemes demonstrated intraday and interday qDESS T2 CVs and RMSA-CVs of ≤5%. T2 ICC values >0.75 were observed in the majority of regions but were more variable in interday tibial comparisons. Test-retest T2 precision was <1.3 msec. The T2 SDD was 3.8 msec.

DATA CONCLUSION

Excellent CV and RMSA-CV reproducibility may suggest that qDESS T2 increases or decreases >5% (3.8 msec) could represent changes to cartilage composition.

LEVEL OF EVIDENCE: 2

TECHNICAL EFFICACY

Stage 2.

Clinical Super-Resolution Computed Tomography of Bone Microstructure: Application in Musculoskeletal and Dental Imaging

PURPOSE

Clinical cone-beam computed tomography (CBCT) devices are limited to imaging features of half a millimeter in size and cannot quantify the tissue microstructure. We demonstrate a robust deep-learning method for enhancing clinical CT images, only requiring a limited set of easy-to-acquire training data.

METHODS

Knee tissue from five cadavers and six total knee replacement patients, and 14 teeth from eight patients were scanned using laboratory CT as training data for the developed super-resolution (SR) technique. The method was benchmarked against ex vivo test set, 52 osteochondral samples are imaged with clinical and laboratory CT. A quality assurance phantom was imaged with clinical CT to quantify the technical image quality. To visually assess the clinical image quality, musculoskeletal and maxillofacial CBCT studies were enhanced with SR and contrasted to interpolated images. A dental radiologist and surgeon reviewed the maxillofacial images.

RESULTS

The SR models predicted the bone morphological parameters on the ex vivo test set more accurately than conventional image processing. The phantom analysis confirmed higher spatial resolution on the SR images than interpolation, but image grayscales were modified. Musculoskeletal and maxillofacial CBCT images showed more details on SR than interpolation; however, artifacts were observed near the crown of the teeth. The readers assessed mediocre overall scores for both SR and interpolation. The source code and pretrained networks are publicly available.

CONCLUSION

Model training with laboratory modalities could push the resolution limit beyond state-of-the-art clinical musculoskeletal and dental CBCT. A larger maxillofacial training dataset is recommended for dental applications.

Identification of diagnostic biomarkers for osteoarthritis through bioinformatics and machine learning

Osteoarthritis (OA) is a prevalent degenerative joint disease characterized by cartilage degradation, inflammatory arthritis, and joint dysfunction. Currently, there is a lack of effective early diagnostic methods and treatment strategies for OA. Bioinformatics and biomarker research provide new possibilities for early detection and personalized therapy of OA. In this study, we investigated the molecular mechanisms of OA and important signaling pathways involved in disease progression through bioinformatics analysis. Firstly, using the limma package, we analyzed the differentially expressed genes (DEGs) between normal healthy samples and OA cartilage tissue samples. These DEGs were found to be primarily involved in biological processes such as extracellular matrix (ECM) binding, immune receptor activity, and cytokine activity, as well as signaling pathways including cytokine receptors, ECM-receptor interaction, and PI3K-Akt. Gene set enrichment analysis revealed that in the OA group, signaling pathways such as AMPK, B cell receptor, IL-17, and PPAR were downregulated, while calcium signaling pathway, cell adhesion molecules, ECM-receptor interaction, TGF-β signaling pathway, and Wnt signaling pathway were upregulated. Additionally, we constructed a co-expression module network using WGCNA and identified key modules associated with OA, from which we selected 7 most predictive OA characteristic genes. Among them, ANTXR1, KCNS3, SGCD, and LIN7A were correlated with the level of immune cell infiltration. This study elucidates the mechanisms underlying the development of OA and identifies potential diagnostic markers and therapeutic targets, providing important insights for early diagnosis and treatment of OA.

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.

Identification of sulfur metabolism-related gene signature in osteoarthritis and TM9SF2's sustenance effect on M2 macrophages' phagocytic activity

BACKGROUND

Osteoarthritis (OA) is a chronic and low-grade inflammatory disease associated with metabolism disorder and multiple cell death types in the synovial tissues. Sulfur metabolism has not been studied in OA.

METHODS

First, we calculated the single sample gene set enrichment analysis score of sulfur metabolism-associated annotations (i.e., cysteine metabolism process, regulation of sulfur metabolism process, and disulfidptosis) between healthy and synovial samples from patients with OA. Sulfur metabolism-related differentially expressed genes (DEGs) were analyzed in OA. Least absolute shrinkage and selection operator COX regression were used to identify the sulfur metabolism-associated gene signature for diagnosing OA. Correlation and immune cell deconvolution analyses were used to explore the correlated functions and cell specificity of the signature gene, TM9SF2. TM9SF2's effect on the phagocytosis of macrophages M2 was analyzed by coculturing macrophages with IgG-coated beads or apoptotic Jurkat cells.

RESULTS

A diagnostic six gene signature (i.e., MTHFD1, PDK4, TM9SF2, POU4F1, HOXA2, NCKAP1) was identified based on the ten DEGs, validated using GSE12021 and GSE1919 datasets. TM9SF2 was upregulated in the synovial tissues of OA at both mRNA and protein levels. The relationship between TM9SF2 and several functional annotations, such as antigen processing and presentation, lysosome, phagosome, Fcγ-mediated phagocytosis, and tyrosine metabolism, was identified. TM9SF2 and macrophages M2 were significantly correlated. After silencing TM9SF2 in THP-1-derived macrophages M2, a significantly reduced phagocytosis and attenuated activation of PLC-γ1 were observed.

CONCLUSION

A sulfur metabolism-associated six-gene signature for OA diagnosis was constructed and upregulation of the phagocytosis-associated gene, TM9SF2, was identified. The findings are expected to deepen our understanding of the molecular mechanism underlying OA development and be used as potential therapeutic targets.

A robust NIR fluorescence-activated probe for peroxynitrite imaging in cells and mice osteoarthritis models

Osteoarthritis (OA) is the most common type of joint disease, which is difficult to treat, but early standardized diagnosis and treatment can effectively alleviate the pain and symptoms of patients. Therefore, it is important to construct an effective tool to assist in the early diagnosis and evaluation of the therapeutic effect of OA. In this work, a near-infrared (NIR) fluorescence-activated fluorescent probe, YB-1, was constructed for the evaluation of the diagnostic and therapeutic efficacy of OA via detection and imaging of the biomarker of ONOO- in inflammatory cells and mice osteoarthritis models. YB-1 exhibited high selectivity, high sensitivity, and a high ratio yield (I668/I0) fluorescence increasing (∼30 folds). Besides, YB-1 can be used effectively to image endogenous and exogenous ONOO- in living human chondrocytes cells (TC28a2), as well as to evaluate the effect of drug (Chrysosplenol D, CD) treatment in IL-1β-induced inflammatory cells model. Interestingly, YB-1 was available for OONO- imaging analysis in the collagenase-induced mice OA models and assessment of the effect of CD treatment in mice OA models, with good results. Thus, the newly constructed YB-1 is a powerful molecular tool for the diagnosis and treatment of OA-related diseases.

Using 3D MRI Bone Shape to Predict Pre-Osteoarthritis of the Knee 2 Years After Anterior Cruciate Ligament Reconstruction

BACKGROUND

Anterior cruciate ligament (ACL) injury increases risks for osteoarthritis (OA), a poorly modifiable and disabling condition. Joint changes of potentially reversible pre-OA have been described just 2 years after ACL reconstruction (ACLR) when early bone shape changes have also been reported.

PURPOSE

This study evaluates relationships between interlimb differences in tibiofemoral bone shape derived from statistical shape modeling (SSM) of magnetic resonance imaging (MRI) and participant factors on patient-reported outcomes 2 years after unilateral ACLR.

STUDY DESIGN

Cross-sectional study; Level of evidence, 3.

METHODS

SSM-derived tibiofemoral bone shape and subchondral bone area were assessed from bilateral knee MRI scans of 72 participants with unilateral ACLR (mean age, 34 ± 11 years; 32 women) and compared with a reference cohort of 398 older individuals without OA (mean age, 50 ± 3 years; 213 women). Multivariable logistic regression models examined relationships between participant and surgical factors with interlimb differences in bone shapes or subchondral bone areas. Relationships between patient-reported outcomes and the interlimb differences in bone shape and subchondral area were examined using similar models.

RESULTS

Bone shape scores and subchondral bone areas were greater (more OA-like) in ACLR knees than uninjured contralateral knees in every bone metric tested (P≤ .001). Interlimb differences in femur shape scores of participants with ACLR were 65% greater (P < .001) than those of the significantly older reference cohort. Taller height, medial meniscal tears, and decreasing age were associated with larger interlimb differences in shape scores and subchondral areas (P < .05). Bone-patellar tendon-bone (BPTB) autograft recipients demonstrated greater interlimb subchondral area differences compared with allograft recipients (P < .05). Interlimb differences for hamstring autograft recipients did not differ from those with BPTB or allograft. Greater interlimb differences in medial femur subchondral areas were associated with worse patient-reported Knee injury and Osteoarthritis Outcome Score Symptoms (R = 0.27; P = .040).

CONCLUSION

Even in the absence of radiographic OA, just 2 years after unilateral ACLR patients showed greater bone shape scores and subchondral areas consistent with pre-OA in their ACLR knees. Furthermore, greater medial femur bone areas were weakly associated with worse symptoms. Patients who are younger, are taller, have meniscal tears, or have BPTB grafts may be at increased risk for bony asymmetries 2 years after ACLR.

Stratifying knee osteoarthritis features through multitask deep hybrid learning: Data from the osteoarthritis initiative

BACKGROUND AND OBJECTIVE

Knee osteoarthritis (OA) is a debilitating musculoskeletal disorder that causes functional disability. Automatic knee OA diagnosis has great potential of enabling timely and early intervention, that can potentially reverse the degenerative process of knee OA. Yet, it is a tedious task, concerning the heterogeneity of the disorder. Most of the proposed techniques demonstrated single OA diagnostic task widely based on Kellgren Lawrence (KL) standard, a composite score of only a few imaging features (i.e. osteophytes, joint space narrowing and subchondral bone changes). However, only one key disease pattern was tackled. The KL standard fails to represent disease pattern of individual OA features, particularly osteophytes, joint-space narrowing, and pain intensity that play a fundamental role in OA manifestation. In this study, we aim to develop a multitask model using convolutional neural network (CNN) feature extractors and machine learning classifiers to detect nine important OA features: KL grade, knee osteophytes (both knee, medial fibular: OSFM, medial tibial: OSTM, lateral fibular: OSFL, and lateral tibial: OSTL), joint-space narrowing (medial: JSM, and lateral: JSL), and patient-reported pain intensity from plain radiography.

METHODS

We proposed a new feature extraction method by replacing fully-connected layer with global average pooling (GAP) layer. A comparative analysis was conducted to compare the efficacy of 16 different convolutional neural network (CNN) feature extractors and three machine learning classifiers.

RESULTS

Experimental results revealed the potential of CNN feature extractors in conducting multitask diagnosis. Optimal model consisted of VGG16-GAP feature extractor and KNN classifier. This model not only outperformed the other tested models, it also outperformed the state-of-art methods with higher balanced accuracy, higher Cohen's kappa, higher F1, and lower mean squared error (MSE) in seven OA features prediction.

CONCLUSIONS

The proposed model demonstrates pain prediction on plain radiographs, as well as eight OA-related bony features. Future work should focus on exploring additional potential radiological manifestations of OA and their relation to therapeutic interventions.

Multidisciplinary Rehabilitation after Hyaluronic Acid Injections for Elderly with Knee, Hip, Shoulder, and Temporomandibular Joint Osteoarthritis

Osteoarthritis (OA) is a prevalent degenerative joint condition characterized by cartilage deterioration, joint inflammation, and functional limitations, particularly impacting the elderly population. Rehabilitation and hyaluronic acid (HA) injections are common therapeutic approaches routinely used in clinical practice, but their synergistic potential is far from being fully characterized. Thus, the aim of this narrative review was to elucidate the multilevel benefits and synergies of integrating these two approaches in multidisciplinary OA rehabilitation. This narrative review follows the scale for the assessment of narrative review articles (SANRA) criteria and involves a comprehensive literature search from July to August 2023. Two independent reviewers screened studies, including those involving human subjects with OA, rehabilitation strategies, and outcomes following HA injection, published in English. Results: HA injections might improve joint biomechanics, reducing friction, absorbing shocks, and potentially regulating inflammation. Rehabilitation plays a pivotal role in strengthening muscles, increasing the range of motion, and enhancing overall function. Optimizing rehabilitation following HA injection might provide additional benefits in joint health. OA management requires a multidisciplinary approach integrating HA injections, rehabilitation, and personalized care. Challenges in patient adherence and healthcare resources currently exist, but emerging technologies offer opportunities to enhance patient engagement and monitoring optimizing sustainability and outcomes of patients with knee, hip, shoulder, and temporomandibular joint OA.

Subchondral bone in knee osteoarthritis: bystander or treatment target?

The subchondral bone is an important structural component of the knee joint relevant for osteoarthritis (OA) incidence and progression once disease is established. Experimental studies have demonstrated that subchondral bone changes are not simply the result of altered biomechanics, i.e., pathologic loading. In fact, subchondral bone alterations have an impact on joint homeostasis leading to articular cartilage loss already early in the disease process. This narrative review aims to summarize the available and emerging imaging techniques used to evaluate knee OA-related subchondral bone changes and their potential role in clinical trials of disease-modifying OA drugs (DMOADs). Radiographic fractal signature analysis has been used to quantify OA-associated changes in subchondral texture and integrity. Cross-sectional modalities such as cone-beam computed tomography (CT), contrast-enhanced cone beam CT, and micro-CT can also provide high-resolution imaging of the subchondral trabecular morphometry. Magnetic resonance imaging (MRI) has been the most commonly used advanced imaging modality to evaluate OA-related subchondral bone changes such as bone marrow lesions and altered trabecular bone texture. Dual-energy X-ray absorptiometry can provide insight into OA-related changes in periarticular subchondral bone mineral density. Positron emission tomography, using physiological biomarkers of subchondral bone regeneration, has provided additional insight into OA pathogenesis. Finally, artificial intelligence algorithms have been developed to automate some of the above subchondral bone measurements. This paper will particularly focus on semiquantitative methods for assessing bone marrow lesions and their utility in identifying subjects at risk of symptomatic and structural OA progression, and evaluating treatment responses in DMOAD clinical trials.

Causal effects of walking pace on osteoarthritis: a two-sample mendelian randomization study

Background: Osteoarthritis (OA) is one of the most common joint diseases worldwide, imposing a substantial burden on individuals and society. Numerous pieces of evidence suggest that walking pace (WP) can serve as a predictive indicator for the risk of various diseases, and observational studies have also found a potential link between WP and the risk of OA. However, the causal relationship between WP and the risk of OA remains unclear. Methods: We conducted a mendelian randomization (MR) study using data from the European Genome-wide Association Study, which included WP (including 459,915 participants), OA (including 10,083 cases and 40,425 controls), knee OA (including 24,955 cases and 378,169 controls), and hip OA (including 15,704 cases and 378,169 controls). Single nucleotide polymorphisms (SNPs) associated with WP were utilized to infer causal associations with OA and its subtypes. The Inverse Variance Weighted (IVW) technique served as the primary causal analysis method. Three auxiliary MR methods - MR-Egger, weighted median, and maximum likelihood - were used to substantiate the IVW results. Sensitivity analyses were performed to examine heterogeneity and pleiotropy. In addition, multivariate MR (MVMR) analysis was used to assess causality after adjustment for three potential confounders. Results: According to the results of the IVW method, every 1 standard deviation increased in genetic WP corresponds to an 89% reduction in the risk of OA (odds ratio (OR) = 0.11; 95% confidence interval (CI), 0. 06-0.19; p = 1.57 × 10-13), an 83% reduction in the risk of knee OA (OR = 0.17; 95% CI, 0.11-0.28; p = 2.78 × 10-13), and a 76% reduction in the risk of hip OA (OR = 0.24; 95% CI, 0.14-0.43; p = 1.51 × 10-6). These results were confirmed by the three additional MR methods and validated by the sensitivity analysis. Ultimately, the MVMR analysis confirmed that the role of WP in reducing the risk of OA and its subtypes remains consistent regardless of potential confounders. Conclusion: The results of our MR study highlight a significant causal association between WP and the susceptibility to OA, including its knee and hip subtypes. These findings propose that WP could be utilized as a potential prognostic factor for OA risk.

Visible and Near-Infrared Spectroscopy Enables Differentiation of Normal and Early Osteoarthritic Human Knee Joint Articular Cartilage

Osteoarthritis degenerates cartilage and impairs joint function. Early intervention opportunities are missed as current diagnostic methods are insensitive to early tissue degeneration. We investigated the capability of visible light-near-infrared spectroscopy (Vis-NIRS) to differentiate normal human cartilage from early osteoarthritic one. Vis-NIRS spectra, biomechanical properties and the state of osteoarthritis (OARSI grade) were quantified from osteochondral samples harvested from different anatomical sites of human cadaver knees. Two support vector machines (SVM) classifiers were developed based on the Vis-NIRS spectra and OARSI scores. The first classifier was designed to distinguish normal (OARSI: 0-1) from general osteoarthritic cartilage (OARSI: 2-5) to check the general suitability of the approach yielding an average accuracy of 75% (AUC = 0.77). Then, the second classifier was designed to distinguish normal from early osteoarthritic cartilage (OARSI: 2-3) yielding an average accuracy of 71% (AUC = 0.73). Important wavelength regions for differentiating normal from early osteoarthritic cartilage were related to collagen organization (wavelength region: 400-600 nm), collagen content (1000-1300 nm) and proteoglycan content (1600-1850 nm). The findings suggest that Vis-NIRS allows objective differentiation of normal and early osteoarthritic tissue, e.g., during arthroscopic repair surgeries.

Regenerative medicine for early osteoarthritis

The concept of early osteoarthritis (OA) is based on the expectation that if found and treated in the early stage, the progression of the disease might be arrested before affected joints are irreversibly destroyed. This notion of early OA detection can also bear meaning for regenerative medicine (RM) which is purposed to cure a disease by regenerating the damaged tissue. RM can be a category of disease-modifying osteoarthritis drugs (DMOADs) and provide an attractive treatment for OA, restoring structural damage incurred during the disease by repopulating cells and reconstituting. While cell therapy including the use of stem cells is conflated with RM, it may also comprise gene therapy, exosomes, and other cell or cell-free-derived products. Considering that not all early OA will become advanced OA and that RM has a characteristic of personalized medicine, it would be very important to foretell, even roughly, which patients will progress rapidly and who will favorably respond to regenerative treatment. Subclassification and comprehensive endotyping or phenotyping (E/P) can be very helpful in detecting the population who would benefit from RM as well as rapid progressors who need closer monitoring.

Assessment of blood flow around the knee joint in patients with knee osteoarthritis by color Doppler ultrasound

OBJECTIVE

To explore a method for early diagnosis of knee osteoarthritis (OA) by comparing vascular morphology and hemodynamic parameters between healthy controls and patients, and explore the effects of age on the blood flow of healthy subjects.

MATERIAL AND METHODS

80 healthy subjects and 106 patients with knee OA were recruited. Color Doppler ultrasound was used to measure the vascular morphology and hemodynamic parameters of 11 blood vessels around the knee joint. A general linear model was used to analyze the difference of blood flow parameters between healthy controls and patients, and to explore the effects of sex and age on the blood flow of healthy subjects.

RESULTS

Age has no significant effect on the vessel diameter of healthy subjects, and it only affect the blood flow velocity (P ＜ 0.05) and blood flow volume (P ＜0.0083) of a few blood vessels. There was no significant difference in vascular morphological parameter between healthy controls, patients with mild OA and moderate/severe OA, but there was significant difference in vascular hemodynamic parameters (P ＜ 0.0167). Specifically, in the early stage of knee OA, hemodynamic parameters of main arteries in patients did not change significantly, but those of branch vessels changed significantly (P ＜ 0.0167). With the development of knee OA, the difference of hemodynamic parameters of branch vessels in patients increased gradually.

CONCLUSION

Hemodynamic parameters of branch vessels around the knee joint have changed significantly in the early stage of knee OA, which can be treated as an important index to screening the early patients.

The Fidelity of Rheumatoid Arthritis Multivariate Diagnostic Biomarkers Using Discriminant Analysis and Binary Logistic Regression

Rheumatoid arthritis (RA) is an autoimmune inflammatory disease that causes multi-articular synovitis. The illness is characterized by worsening inflammatory synovitis, which causes joint swelling and pain. Synovitis erodes articular cartilage and marginal bone, resulting in joint deterioration. This bone injury is expected to be permanent. Cytokines play a prominent role in the etiology of RA and could be useful as early diagnostic biomarkers. This research was carried out at Riyadh's King Khalid University Hospital (KKUH). Patients were enrolled from the Rheumatology unit. Seventy-eight RA patients were recruited (67 (85.9%) females and 11 (14.1%) males). Patients were selected for participation by convenience sampling. Demographic data were collected, and disease activity measurements at 28 joints were recorded using the disease activity score (DAS-28). Age- and sex-matched controls from the general population were included in the study. A panel of 27 cytokines, chemokines, and growth factors was determined in patient and control sera. Binary logistic regression (BLR) and discriminant analysis (DA) were used to analyze the data. We show that multiple cytokine biomarker profiles successfully distinguished RA patients from healthy controls. IL-17, IL-4, and RANTES were among the most predictive variables and were the only biomarkers incorporated into both BLR and DA predictive models for pooled participants (men and women). In the women-only models, the significant cytokines incorporated in the model were IL-4, IL-17, MIP-1b, and RANTES for the BLR model and IL-4, IL-1Ra, GM-CSF, IL-17, and eotaxin for the DA model. The BLR and DA men-only models contained one cytokine each, eotaxin for BLR and platelet-derived growth factor-bb (PDGF-BB) for DA. We show that BLR has a higher fidelity in identifying RA patients than DA. We also found that the use of gender-specific models marginally improves detection fidelity, indicating a possible benefit in clinical diagnosis. More research is needed to determine whether this conclusion will hold true in various and larger patient populations.

Evaluation of mechanistic serum and urine biomarkers for secondary osteoarthritis associated with developmental dysplasia of the hip

Objective

Determine measurable differences for mechanistic urine and serum biomarkers in patients with developmental dysplasia of the hip (DDH) prior to, and following, secondary hip osteoarthritis (OA) when compared to controls.

Design

Urine and serum were collected from individuals with developmental dysplasia of the hip (n = 39), prior to (Pre-OA DDH, n = 32) and following diagnosis of secondary hip OA (Post-OA DDH, n = 7), age-matched Pre-OA controls (n = 35), and age-matched Post-OA controls (n = 12). Samples were analyzed for protein biomarkers with potential for differentiation of hip status through a Mann-Whitney U test with a Benjamini-Hochberg correction.

Results

Several interleukin and degradation related proteins were found to be differentially expressed when comparing DDH-related hip status prior to and following diagnosis of hip OA. In addition, MCP-1 and TIMP-1 were significantly different between younger and older patients in the control cohorts.

Conclusion

These results provide initial evidence for serum and urine protein biomarkers that define clinically relevant stages of symptomatic DDH and its progression to secondary hip osteoarthritis categorized by known mechanisms of disease.

Level of evidence

III.

Circulating miR-146b and miR-27b are efficient biomarkers for early diagnosis of Equidae osteoarthritis

One of the most orthopedic problems seen in the equine is osteoarthritis (OA). The present study tracks some biochemical, epigenetic, and transcriptomic factors along different stages of monoiodoacetate (MIA) induced OA in donkeys in serum and synovial fluid. The aim of the study was the detection of sensitive noninvasive early biomarkers. OA was induced by a single intra-articular injection of 25 mg of MIA into the left radiocarpal joint of nine donkeys. Serum and synovial samples were taken at zero-day and different intervals for assessment of total GAGs and CS levels as well as miR-146b, miR-27b, TRAF-6, and COL10A1 gene expression. The results showed that the total GAGs and CS levels increased in different stages of OA. The level of expression of both miR-146b and miR-27b were upregulated as OA progressed and then downregulated at late stages. TRAF-6 gene was upregulated at the late stage while synovial fluid COL10A1 was over-expressed at the early stage of OA and then decreased at the late stages (P < 0.05). In conclusion, both miR-146b and miR-27b together with COL10A1 could be used as promising noninvasive biomarkers for the very early diagnosis of OA.

Preoperative diagnosis of knee cartilage, meniscal, and ligament injuries by magnetic resonance imaging

PURPOSE

The purpose of the study was to report on the current accuracy measures specific to 1.5-Tesla MRI of the knee in the patient population prone to injuries of the anterior cruciate ligament (ACL), the menisci, and the articular cartilage.

METHODS

We accrued patients between January 2018 through August 2021 who underwent a preoperative MRI and were diagnosed with an articular cartilage injury either due to unevenness of articular cartilage in T2-weighted sequences or due to the irregularity of subchondral bone in T1-weighted sequences. All patients were treated arthroscopically. Sensitivity, specificity, and accuracy were calculated for the detection of ACL, meniscus, and cartilage injuries. A P-value of < 0.05 represented statistical significance.

RESULTS

One-hundred and forty-seven cases which included 150 knee joints were enrolled in this study. The mean age at the time of surgery was 42.9 years-old. The sensitivity in the diagnosis of ACL injuries was significantly greater than that in the diagnosis of cartilage injuries (P = 0.0083). The ratios of the equality of operative indication in 6 recipient sites were found to be between 90.0% and 96.0%. The diagnostic critical point was within a 1 cm in diameter.

CONCLUSION

The diagnostic sensitivity in cartilage injuries was significantly lower than ones of ACL and meniscal injuries. The ratios of the equality of operative indication was determined to be between 90.0% and 96.0%, if we consider the unevenness of articular cartilage or the irregularity of subchondral bone.

LEVEL OF EVIDENCE

Level III, Prospective diagnostic cohort study.

Label-free, multi-parametric assessments of cell metabolism and matrix remodeling within human and early-stage murine osteoarthritic articular cartilage

Osteoarthritis (OA) is characterized by the progressive deterioration of articular cartilage, involving complicated cell-matrix interactions. Systematic investigations of dynamic cellular and matrix changes during OA progression are lacking. In this study, we use label-free two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) imaging to assess cellular and extracellular matrix features of murine articular cartilage during several time points at early stages of OA development following destabilization of medial meniscus surgery. We detect significant changes in the organization of collagen fibers and crosslink-associated fluorescence of the superficial zone as early as one week following surgery. Such changes become significant within the deeper transitional and radial zones at later time-points, highlighting the importance of high spatial resolution. Cellular metabolic changes exhibit a highly dynamic behavior, and indicate metabolic reprogramming from enhanced oxidative phosphorylation to enhanced glycolysis or fatty acid oxidation over the ten-week observation period. The optical metabolic and matrix changes detected within this mouse model are consistent with differences identified in excised human cartilage specimens from OA and healthy cartilage specimens. Thus, our studies reveal important cell-matrix interactions at the onset of OA that may enable improved understanding of OA development and identification of new potential treatment targets.

Early Osteoarthritis Questionnaire (EOAQ): a tool to assess knee osteoarthritis at initial stage

Background

Early stage of osteoarthritis (OA) is characterized by joint stiffness and pain as well as by subclinical structural changes that may affect cartilage, synovium, and bone. At the moment, the lack of a validated definition of early osteoarthritis (EOA) does not allow to make an early diagnosis and adopt a therapeutic strategy to slow disease progression. Also, no questionnaires are available to evaluate the early stage, and therefore this remains an unmet need.

Objective

Therefore, the purpose of the technical experts panel (TEP) of 'International Symposium of intra-articular treatment' (ISIAT) was to create a specific questionnaire to evaluate and monitor the follow-up and clinical progress of patients affected by early knee OA.

Design

The items for the Early Osteoarthritis Questionnaire (EOAQ) were identified according to the following steps: items generation, items reduction, and pre-test submission.

Methods

During the first step, literature has been reviewed and a comprehensive list of items about pain and function in knee EOA was drafted. Then, during the ISIAT (5th edition 2019), the draft has been discussed by the board, which reformulated, deleted, or subdivided some of the items. After the ISIAT symposium, the draft was submitted to 24 subjects affected by knee OA. A score based on the importance and the frequency was created and the items with a score ⩾0.75 were selected. After intermediate evaluation made by a sample of patients, the second and final version of the questionnaire EOAQ was submitted to the whole board for final analysis and acceptance in a second meeting (29 January 2021).

Results

After an exhaustive elaboration, the final version of the questionnaire contains two domains (Clinical Features and Patients Reported Outcome) with respectively 2 and 9 questions, for a total of 11 questions. Questions mainly explored the fields of early symptoms and patients reported outcomes. Marginally, the need of the symptoms treatment and the use of painkillers were investigated.

Conclusions

Adoption of diagnostic criteria of early OA is strongly encouraged and a specific questionnaire for the whole management of the clinical features and patients' outcome might really improve the evolution of OA in the early stages of the disease, when the treatment is expected to be more effective.

Making the current non-surgical treatments for knee osteoarthritis more effective: Solutions from a diverse patient group

OBJECTIVE

To examine patient perceived solutions to barriers to effective non-surgical knee osteoarthritis (OA) treatments in a diverse racial/ethnic group.

METHODS

Nominal groups were conducted with consecutive patients with knee OA at a medical center clinic, oversampling for African Americans with knee OA. Participants discussed potential solutions and rank-ordered their concerns.

RESULTS

Thirteen nominal groups with 46 knee OA patients were conducted with mean age, 60.8 years (standard deviation [sd], 10.0) and knee OA duration, 8.1 years (sd, 5.4); 22% were men, and 56% were African American. The following solutions were in the top three ranked solutions in 13 NGTs: (A) more research, effective and/or safer new medications/treatments, and joint cartilage restoration (8 groups; 15% votes [43/276]); (B) early diagnosis (2 groups; 7% votes [20/276]); (C) better and more effective communication (5 groups; 10% votes [29/276]); (D) public and patient education (4 groups; 8% votes [22/276]); (E) motivation and behavioral modification (4 groups; 9% votes [26/276]); (F) team approach (1 group; 1% votes [2/276]); (G) personalized medicine (6 groups; 8% votes [24/276]); (H) cheaper and more affordable medications and treatments (3 groups; 5% votes [15/276]).

CONCLUSIONS

A diverse group of participants with knee OA identified several solutions to barriers to the effectiveness of current knee OA treatments. This new knowledge can inform the development and implementation of future interventions to improve the outcomes of people with knee OA.

Making the invisible visible-ultrashort echo time magnetic resonance imaging: Technical developments and applications

Magnetic resonance imaging (MRI) uses a large magnetic field and radio waves to generate images of tissues in the body. Conventional MRI techniques have been developed to image and quantify tissues and fluids with long transverse relaxation times (T2s), such as muscle, cartilage, liver, white matter, gray matter, spinal cord, and cerebrospinal fluid. However, the body also contains many tissues and tissue components such as the osteochondral junction, menisci, ligaments, tendons, bone, lung parenchyma, and myelin, which have short or ultrashort T2s. After radio frequency excitation, their transverse magnetizations typically decay to zero or near zero before the receiving mode is enabled for spatial encoding with conventional MR imaging. As a result, these tissues appear dark, and their MR properties are inaccessible. However, when ultrashort echo times (UTEs) are used, signals can be detected from these tissues before they decay to zero. This review summarizes recent technical developments in UTE MRI of tissues with short and ultrashort T2 relaxation times. A series of UTE MRI techniques for high-resolution morphological and quantitative imaging of these short-T2 tissues are discussed. Applications of UTE imaging in the musculoskeletal, nervous, respiratory, gastrointestinal, and cardiovascular systems of the body are included.

Current and Future Advanced Imaging Modalities for the Diagnosis of Early Osteoarthritis of the Hip

Hip osteoarthritis (OA) can be idiopathic or develop secondary to structural joint abnormalities of the hip joint (alteration of normal anatomy) and/or due to a systemic condition with joint involvement. Early osteoarthritic changes to the hip can be completely asymptomatic or may cause the development hip symptomatology without evidence of OA on radiographs. Delaying the progression of hip OA is critical due to the significant impact of this condition on the patient’s quality of life. Pre-OA of the hip is a newly established term that is often described as the development of signs and symptoms of degenerative hip disease but no radiographic evidence of OA. Advanced imaging methods can help to diagnose pre-OA of the hip in patients with hip pain and normal radiographs or aid in the surveillance of asymptomatic patients with an underlying hip diagnosis that is known to increase the risk of early OA of the hip. These methods include the delayed gadolinium-enhanced magnetic resonance imaging (MRI) of cartilage (dGEMRIC), quantitative magnetic resonance imaging (qMRI- T1rho, T2, and T2* relaxation time mapping), 7-Tesla MRI, computed tomography (CT), and optical coherence tomography (OCT). dGEMRIC proved to be a reliable and accurate modality though it is limited by the significant time necessary for contrast washout between scans. This disadvantage is potentially overcome by T2 weighted MRIs, which do not require contrast. 7-Tesla MRI is a promising development for enhanced imaging resolution compared to 1.5 and 3T MRIs. This technique does require additional optimization and development prior to widespread clinical use. The purpose of this review was to summarize the results of translational and clinical studies investigating the utilization of the above-mentioned imaging modalities to diagnose hip pre-OA, with special focus on recent research evaluating their implementation into clinical practice.

ATF3 as a potential diagnostic marker of early-stage osteoarthritis and its correlation with immune infiltration through bioinformatics analysis

AIMS

This study aimed, through bioinformatics analysis, to identify the potential diagnostic markers of osteoarthritis, and analyze the role of immune infiltration in synovial tissue.

METHODS

The gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by R software. Functional enrichment analyses were performed and protein-protein interaction networks (PPI) were constructed. Then the hub genes were screened. Biomarkers with high value for the diagnosis of early osteoarthritis (OA) were validated by GEO datasets. Finally, the CIBERSORT algorithm was used to evaluate the immune infiltration between early-stage OA and end-stage OA, and the correlation between the diagnostic marker and infiltrating immune cells was analyzed.

RESULTS

A total of 88 DEGs were identified. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that DEGs were significantly enriched in leucocyte migration and interleukin (IL)-17 signalling pathways. Disease ontology (DO) indicated that DEGs were mostly enriched in rheumatoid arthritis. Six hub genes including FosB proto-oncogene, AP-1 transcription factor subunit (FOSB); C-X-C motif chemokine ligand 2 (CXCL2); CXCL8; IL-6; Jun proto-oncogene, AP-1 transcription factor subunit (JUN); and Activating transcription factor 3 (ATF3) were identified and verified by GEO datasets. ATF3 (area under the curve = 0.975) turned out to be a potential biomarker for the diagnosis of early OA. Several infiltrating immune cells varied significantly between early-stage OA and end-stage OA, such as resting NK cells (p = 0.016), resting dendritic cells (p = 0.043), and plasma cells (p = 0.043). Additionally, ATF3 was significantly correlated with resting NK cells (p = 0.034), resting dendritic cells (p = 0.026), and regulatory T cells (Tregs, p = 0.018).

CONCLUSION

ATF3 may be a potential diagnostic marker for early diagnosis and treatment of OA, and immune cell infiltration provides new perspectives for understanding the mechanism during OA progression.Cite this article: Bone Joint Res 2022;11(9):679-689.

Phenotype-Genotype analysis of caucasian patients with high risk of osteoarthritis

Background: Osteoarthritis (OA) is a common cause of disability and pain around the world. Epidemiologic studies of family history have revealed evidence of genetic influence on OA. Although many efforts have been devoted to exploring genetic biomarkers, the mechanism behind this complex disease remains unclear. The identified genetic risk variants only explain a small proportion of the disease phenotype. Traditional genome-wide association study (GWAS) focuses on radiographic evidence of OA and excludes sex chromosome information in the analysis. However, gender differences in OA are multifactorial, with a higher frequency in women, indicating that the chromosome X plays an essential role in OA pathology. Furthermore, the prevalence of comorbidities among patients with OA is high, indicating multiple diseases share a similar genetic susceptibility to OA. Methods: In this study, we performed GWAS of OA and OA-associated key comorbidities on 3366 OA patient data obtained from the Osteoarthritis Initiative (OAI). We performed Mendelian randomization to identify the possible causal relationship between OA and OA-related clinical features. Results: One significant OA-associated locus rs2305570 was identified through sex-specific genome-wide association. By calculating the LD score, we found OA is positively correlated with heart disease and stroke. A strong genetic correlation was observed between knee OA and inflammatory disease, including eczema, multiple sclerosis, and Crohn's disease. Our study also found that knee alignment is one of the major risk factors in OA development, and we surprisingly found knee pain is not a causative factor of OA, although it was the most common symptom of OA. Conclusion: We investigated several significant positive/negative genetic correlations between OA and common chronic diseases, suggesting substantial genetic overlaps between OA and these traits. The sex-specific association analysis supports the critical role of chromosome X in OA development in females.

Treatment-Monitoring Capabilities of Serum and Urine Biomarkers for Meniscal Allograft Transplantation in a Preclinical Canine Model

BACKGROUND

Meniscal allograft transplantation (MAT) has been developed as a treatment for meniscal deficiency. Despite promising outcomes, there are no real-time methods to evaluate graft survivorship and predict functional outcomes.

HYPOTHESIS

Assessment of serum and urine biomarkers could be used to develop biomarker panels-prognostic (1- and 3-month postsurgical time points) and diagnostic (6-month time point)-based on strong associations with clinically relevant outcome metrics obtained 6 months after surgery.

STUDY DESIGN

Descriptive laboratory study.

METHODS

Twelve adult purpose-bred research hounds were included and underwent medial meniscal release to induce meniscal deficiency. Three months after meniscal release surgery, medial menisci were replaced with fresh-frozen meniscus (n = 4), fresh meniscus (n = 4), or fresh meniscotibial osteochondral allograft (n = 4) such that a spectrum of pain and functional outcomes could be anticipated. Serum and urine from all dogs were collected preoperatively and at 1, 3, and 6 months after MAT surgery. Dogs were assessed for pain-related and functional outcomes at the same time points. To develop a prognostic panel of biomarkers, biomarker data from the 1- and 3-month post-MAT surgery time points were used to model 6-month clinical outcomes. A diagnostic panel of biomarkers was developed using data from the 6-month post-MAT surgery to model 6-month clinical outcomes. Primary outcomes for pain and function were visual analog scale (VAS) and operated limb percentage total pressure index (%TPI), respectively. Using random subject effects, linear mixed models were used to develop prognostic biomarker panels, and linear fixed-effect models were used to develop diagnostic biomarker panels, with variance explained for each panel reported (R²) along with individual biomarker relationships.

RESULTS

Across prognostic biomarker panels, a panel including serum IL-6, IL-8, IL-10, and IL-18 was fit for the primary functional outcome, operated limb %TPI (R² = 0.450), whereas a panel including serum CTX-II and OPG was fit for the primary pain-related outcome, VAS (R² = 0.516). Across diagnostic biomarker panels, a panel including serum MMP-1 and MMP-3 and urine PINP and TIMP-1 was fit for %TPI (R² = 0.863). Separately, a panel including urine CTX-I, CTX-II, IL-8, MMP-2, and TIMP-1 was fit as diagnostic biomarkers for the VAS for pain (R² = 0.438).

CONCLUSION

Biomarker panels of selected serum and/or urine proteins can model clinically relevant metrics for function and pain in a preclinical model of MAT.

CLINICAL RELEVANCE

Biomarker panels could be used to provide real-time diagnostic and prognostic data regarding outcomes after MAT.

Quantitative Ultrasound Assessment of Early Osteoarthritis in Human Articular Cartilage Using a High-Frequency Linear Array Transducer

Quantitative ultrasound (QUS) assessment of osteoarthritis (OA) using high-frequency, research-grade single-element ultrasound systems has been reported. The objective of this ex vivo study was to assess the performance of QUS in detecting early OA using a high-frequency linear array transducer. Osteochondral plugs (n = 26) of human articular cartilage were scanned with ExactVu Micro-Ultrasound using an EV29L side-fire transducer. For comparison, the samples were also imaged with SAM200Ex, a custom 40-MHz scanning acoustic microscope with a single-element, focused transducer. Thirteen QUS parameters were derived from the ultrasound data. Magnetic resonance imaging (MRI) data, with T1 and T2 extracted as the quantitative parameters, were also acquired for comparison. Cartilage degeneration was graded from histology and correlated to all quantitative parameters. A maximum Spearman rank correlation coefficient (ρ) of 0.75 was achieved using a combination of ExactVu QUS parameters, while a maximum ρ of 0.62 was achieved using a combination of parameters from SAM200Ex. A maximum ρ of 0.75 was achieved using the T1 and T2 MRI parameters. This study illustrates the potential of a high-frequency linear array transducer to provide a convenient method for early OA screening with results comparable to those of research-grade single-element ultrasound and MRI.

Macroscopic Synovial Inflammation Correlates with Symptoms and Cartilage Lesions in Patients Undergoing Arthroscopic Partial Meniscectomy: A Clinical Study

Background: The aim of the study was to examine the relationship among patients’ characteristics, intraoperative pathology and pre/post-operative symptoms in a cohort of patients undergoing arthroscopic partial meniscectomy for symptomatic meniscal tears. Methods: Clinical data were collected (age, sex, body mass index, time to surgery, trauma). Intraoperative cartilage pathology was assessed with Outerbridge score. Meniscal tears were graded with the ISAKOS classification. Synovial inflammation was scored using the Macro-score. Patient symptoms were assessed pre/post-operatively using the KOOS instrument. Results: In the series of 109 patients (median age 47 years), 50% of the meniscal tears were traumatic; 85% of patients showed mild to moderate synovitis; 52 (47.7%) patients had multiple cartilage defects and 31 (28.4%) exhibited a single focal chondral lesion. Outerbridge scores significantly correlated with patient age, BMI and synovial inflammation. There was a correlation between severity of chondral pathology and high-grade synovial hyperplasia. Pre-operative KOOS correlated with BMI, meniscal degenerative changes and symptom duration. Obesity, time to surgery, presence of high-grade synovial hyperplasia and high-grade cartilage lesions were independent predictors of worse post-operative pain and function. Conclusion: We demonstrated that pre-operative symptoms and post-operative outcomes correlate with synovitis severity and cartilage pathology, particularly in old and obese patients that underwent arthroscopic partial meniscectomy. Importantly, patients with a degenerative meniscal pattern and with longer time to surgery experienced more severe cartilage damage and, consequentially, pain and dysfunction. These findings are fundamental to identify patients suitable for earlier interventions.

The Application of circRNA-016901 in Improving the Diagnostic Accuracy of Osteoarthritis

In clinical practice, osteoarthritis (OA) is frequently misdiagnosed as rheumatoid arthritis (RA) and osteonecrosis (ON), leading to wrong treatment and disease progression. Circular RNA- (circRNA-) 016901 affects the recovery of irradiation-induced injury in the bone, while its role in OA is unclear. This study is aimed at exploring the role of circRNA-016901 in improving the diagnostic accuracy of OA. The present study included patients with OA (n = 80), patients with RA (n = 80), patients with ON (n = 80), and healthy controls (HCs, n = 80) to collect plasma samples before and after treatment. RT-qPCR was performed to detect RNA accumulation of circRNA-016901 in plasma samples from all participants. The role of plasma expression of circRNA-016901 in predicting OA was studied with ROC curve analysis. Association between plasma expression of circRNA-016901 and patients' clinical features was analyzed with the chi-squared test. Compared to HCs, increased accumulation of circRNA-016901 was only observed in the OA group, but not in the RA and ON groups before treatment. OA patients were effectively separated from the RA, ON, and HC groups using plasma expression of circRNA-016901 before treatment as a biomarker. Plasma expression of circRNA-016901 was closely associated with OA patients' disease severity. After treatment, decreased plasma expression levels of circRNA-016901 were only observed in OA patients, while no alteration in plasma circRNA-016901 accumulation was observed in the RA and ON groups. In conclusion, circRNA-016901 is accumulated to high levels in OA and may be applied to improve the diagnostic accuracy of OA.

Is interleukin-17 implicated in early knee osteoarthritis pathogenesis as in rheumatoid arthritis?

Background

Interleukin-17 (IL-17) is a cytokine that promotes activation of multiple catabolic pathways resulting in cartilage and tissue damage. It has features making it increasingly attractive as a biological marker, especially in rheumatoid arthritis (RA) and osteoarthritis (OA). However, its expression is heterogeneous; not all patients’ exhibit high IL-17 levels, and its level along the disease course is still challenging to predict.

Aim of the work

The objectives of this study were to compare serum IL-17 levels in patients with early knee OA and in RA patients, to determine its correlation with disease activity in RA and to determine if it is correlated with functional scores in both RA and OA.

Subjects and methods

Twenty early knee OA patients (32.7 ± 3.7) years were included. Diagnosis of early OA was based on Luyten et al. 2012 early knee OA classification (early OA 2012). This study also included 25 RA patients aged 32.8 ± 5.1 years, and the diagnosis was according to 2010 ACR-EULAR classification criteria for RA. The current work also included a control group of 20 healthy volunteers aged 31.9 ± 3.2 years. The serum IL-17 level was assessed by using the ELISA technique.

Results

Serum IL-17 level was significantly high in early knee OA patients (5.2 pg/ml) and was significantly higher in RA patients (5.9 pg/ml) compared to the control group (4.9 pg/ml) (P < 0.001).

Conclusions

The increased serum IL-17 level in patients with early knee OA suggests its pathogenic role in the disease. Serum IL-17 positive correlation with the severity of knee OA-related pain proposes that it may be a potential marker to target for early treatment of knee OA-related pain.

Evaluation of enzymatic proteoglycan loss and collagen degradation in human articular cartilage using ultrashort echo time-based biomarkers: A feasibility study

The objective of the current study was to investigate the feasibility of quantitative 3D ultrashort echo time (UTE)-based biomarkers in detecting proteoglycan (PG) loss and collagen degradation in human cartilage. A total of 104 cartilage samples were harvested for a trypsin digestion study (n = 44), and a sequential trypsin and collagenase digestion study (n = 60), respectively. Forty-four cartilage samples were randomly divided into a trypsin digestion group (tryp group) and a control group (phosphate-buffered saline [PBS] group) (n = 22 for each group) for the trypsin digestion experiment. The remaining 60 cartilage samples were divided equally into four groups (n = 15 for each group) for sequential trypsin and collagenase digestion, including PBS + Tris (incubated in PBS, then Tris buffer solution), PBS + 30 U col (incubated in PBS, then 30 U/ml collagenase [30 U col] with Tris buffer solution), tryp + 30 U col (incubated in trypsin solution, then 30 U/ml collagenase with Tris buffer solution), and tryp + Tris (incubated in trypsin solution, then Tris buffer solution). The 3D UTE-based MRI biomarkers included T₁ , multiecho T₂ *, adiabatic T_1ρ (AdiabT_1ρ ), magnetization transfer ratio (MTR), and modeling of macromolecular proton fraction (MMF). For each cartilage sample, UTE-based biomarkers (T₁ , T₂ *, AdiabT_1ρ , MTR, and MMF) and sample weight were evaluated before and after treatment. PG and hydroxyproline assays were performed. Differences between groups and correlations were assessed. All the evaluated biomarkers were able to differentiate between healthy and degenerated cartilage in the trypsin digestion experiment, but only T₁ and AdiabT_1ρ were significantly correlated with the PG concentration in the digestion solution (p = 0.004 and p = 0.0001, respectively). In the sequential digestion experiment, no significant differences were found for T₁ and AdiabT_1ρ values between the PBS + Tris and PBS + 30 U col groups (p = 0.627 and p = 0.877, respectively), but T₁ and AdiabT_1ρ values increased significantly in the tryp + Tris (p = 0.031 and p = 0.024, respectively) and tryp + 30 U col groups (both p < 0.0001). Significant decreases in MMF and MTR were found in the tryp + 30 U col group compared with the PBS + Tris group (p = 0.002 and p = 0.001, respectively). It was concluded that AdiabT_1ρ and T₁ have the potential for detecting PG loss, while MMF and MTR are promising for the detection of collagen degradation in articular cartilage, which could facilitate earlier, noninvasive diagnosis of osteoarthritis.

The Concept of Early Osteoarthritis and Its Significance in Regenerative Medicine

Osteoarthritis (OA) has been investigated as one of important target diseases for regenerative medicine. The concept of early OA has recently emerged under the assumption that if OA is detected and intervened early, progression of OA might be arrested or delayed before irreversible destruction of the joint occurs. This concept also matters in regenerative medicine for OA because new regenerative technologies can work better when joint damage is minimal. Diagnostic criteria for early OA have been suggested in this background to find a group of patients who have a higher possibility of developing full-blown OA. However, as currently suggested criteria of early OA are mostly expert opinions lacking higher level of evidence, clinical validations are necessary to prove their value in patient care. While new treatment methods that can suppress or prevent symptoms at an early stage of OA before progressive and irreversible changes occur are being developed, detailed definition and classification of early OA agreed upon by major stakeholders in OA field and validated by prospective studies are necessary to prove the efficacy of these methods. As clinical outcome of regenerative treatment is related to patient characteristics and the status of the whole joint, it is of critical significance to predict which patient will progress and who will be responsive to regenerative treatment. While diagnostic criteria for early OA should be highly sensitive and applicable without employing biomarkers or magnetic resonance imaging, a subclassification and comprehensive endotyping /phenotyping using these techniques might be needed to detect the population who would be responsive to regenerative medicine.

Prevalence of Early Knee Osteoarthritis Illness Among Various Patient-Reported Classification Criteria After Anterior Cruciate Ligament Reconstruction

OBJECTIVE

To compare the prevalence of participants meeting different patient-reported criteria for early osteoarthritis (OA) illness after anterior cruciate ligament reconstruction (ACLR).

METHODS

Participants completed the Knee Injury and Osteoarthritis Outcomes Score (KOOS) at a single time point 5.0-7.9 months post-ACLR. We used established KOOS subscale criteria (i.e., Luyten original and Englund original) to define patient-reported early OA illness. A two-by-two contingency table and McNemar's test were used to compare the prevalence of participants who met the Luyten original versus Englund original KOOS criteria for early OA illness. These analyses were repeated using KOOS subscale thresholds based on established population-specific patient acceptable symptom state (PASS) within the Luyten and Englund KOOS criteria (i.e., Luyten PASS and Englund PASS).

RESULTS

A greater prevalence of participants with ACLR met the Luyten original criteria (n = 165 [54%]) compared to those who met the Englund original criteria (n = 128 [42%]; χ2  = 19.3, P < 0.001). When using the KOOS subscale PASS as thresholds, a significantly greater prevalence of participants with ACLR met the Luyten PASS criteria (n = 133 [43%]) compared to those who met the Englund PASS criteria (n = 85 [28%]; χ2  = 48.0, P < 0.001). When combining the Luyten and Englund KOOS criteria and using the original/PASS subscale thresholds, respectively, 40%/57% of participants met neither, 24%/15% met only 1, and 36%/28% met both KOOS criteria.

CONCLUSION

Regardless of the classification criteria used to define early OA illness, it is concerning that 28-54% of patients report considerable symptoms ~6 months post-ACLR. Our findings will improve the classification criteria to define early OA illness, which may raise awareness for the need of population-specific criteria.

Discovering Knee Osteoarthritis Imaging Features for Diagnosis and Prognosis: Review of Manual Imaging Grading and Machine Learning Approaches

Knee osteoarthritis (OA) is a deliberating joint disorder characterized by cartilage loss that can be captured by imaging modalities and translated into imaging features. Observing imaging features is a well-known objective assessment for knee OA disorder. However, the variety of imaging features is rarely discussed. This study reviews knee OA imaging features with respect to different imaging modalities for traditional OA diagnosis and updates recent image-based machine learning approaches for knee OA diagnosis and prognosis. Although most studies recognized X-ray as standard imaging option for knee OA diagnosis, the imaging features are limited to bony changes and less sensitive to short-term OA changes. Researchers have recommended the usage of MRI to study the hidden OA-related radiomic features in soft tissues and bony structures. Furthermore, ultrasound imaging features should be explored to make it more feasible for point-of-care diagnosis. Traditional knee OA diagnosis mainly relies on manual interpretation of medical images based on the Kellgren-Lawrence (KL) grading scheme, but this approach is consistently prone to human resource and time constraints and less effective for OA prevention. Recent studies revealed the capability of machine learning approaches in automating knee OA diagnosis and prognosis, through three major tasks: knee joint localization (detection and segmentation), classification of OA severity, and prediction of disease progression. AI-aided diagnostic models improved the quality of knee OA diagnosis significantly in terms of time taken, reproducibility, and accuracy. Prognostic ability was demonstrated by several prediction models in terms of estimating possible OA onset, OA deterioration, progressive pain, progressive structural change, progressive structural change with pain, and time to total knee replacement (TKR) incidence. Despite research gaps, machine learning techniques still manifest huge potential to work on demanding tasks such as early knee OA detection and estimation of future disease events, as well as fundamental tasks such as discovering the new imaging features and establishment of novel OA status measure. Continuous machine learning model enhancement may favour the discovery of new OA treatment in future.

Identification and development of the novel 7-genes diagnostic signature by integrating multi cohorts based on osteoarthritis

Background

A chronic progressive degenerative joint disease, such as osteoarthritis (OA) is positively related to age. The medical economy is facing a major burden, because of the high disability rate seen in patients with OA. Therefore, to prevent and treat OA, exploring the diagnostic biomarkers of OA will be of great significance.

Methods

Differentially expressed genes (DEGs) were obtained from the Gene Expression Omnibus database using the RobustRankAggreg R package, and a protein–protein interaction network was constructed. The module was obtained from Cytoscape, and the four algorithms of degree, MNC, closeness, and MCC in CytoHubba were used to identify the hub genes. A diagnostic model was constructed using Support Vector Machines (SVM), and the ability of the model to predict was evaluated by other cohorts.

Results

From normal and OA samples, 136 DEGs were identified, out of which 45 were downregulated in the normal group and 91 were upregulated in the OA group. These genes were associated with the extracellular matrix-receptor interactions, the PI3K-Akt signaling pathway, and the protein digestion and absorption pathway, as per a functional enrichment analysis. Finally, we identified the 7 hub genes (COL6A3, COL1A2, COL1A1, MMP2, COL3A1, POST, and FN1). These genes have important roles and are widely involved in the immune response, apoptosis, inflammation, and bone development. These 7 genes were used to construct a diagnostic model by SVM, and it performed well in different cohorts. Additionally, we verified the methylation expression of these hub genes.

Conclusions

The 7-genes signature can be used for the diagnosis of OA and can provide new ideas in the clinical decision-making for patients with OA.

Detecting early osteoarthritis through changes in biomechanical properties - A review of recent advances in indentation technologies in a clinical arthroscopic setup

Osteoarthritis (OA) is a degenerative joint disease currently affecting half of all women and one-third of all men aged over 65 and it is predicted to even increase in the next decades. In the variety of causes leading to OA, the first common denominator are changes in the extracellular matrix of the cartilage. In later stages, OA affects the whole joint spreading to higher levels of tissue architecture causing irreversible functional and structural damage. To date, the diagnosis of OA is only formulated in the late stages of the disease. This is also, where most present therapies apply. Since a precise diagnosis is a prerequisite for targeted therapy, tools to diagnose early OA, monitor its progression, and accurately stage the disease are wanted. This review article focuses on recent advances in indentation technologies to diagnose early OA through describing biomechanical cartilage characteristics. We provide an overview of microindentation instruments, indentation-type Atomic Force Microscopy, ultrasound, and water-jet ultrasound indentation, Optical Coherence Tomography-based air-jet indentation, as well as fiber Bragg grating.

Can we afford to ignore the biology of joint healing and graft incorporation after ACL reconstruction?

Anterior cruciate ligament (ACL) reconstruction is successful at restoring stability to return ACL injured patients to high-demand work, sports, and recreational activities. The development of posttraumatic osteoarthritis (OA) in roughly half of patients just 10-15 years after ACLR highlight the need to improve clinical care pathways. Graft failure and reinjury rates, which further increase OA risk, also remain high for younger and more active patients. The biological components of joint recovery and graft incorporation, therefore, impact short- and long-term clinical outcomes. Biochemical and magnetic resonance imaging (MRI) data show substantial compromise of articular cartilage metabolism and matrix composition after ACL injury and reconstructive surgery suggesting a potential need for activity modulation in early recovery. Furthermore, joint recovery is variable with compositional MRI studies showing progressive cartilage degeneration 1 and 2 years after ACLR. Biopsy and MRI studies also show high variability in ACL graft characteristics within the 1st year after ACLR followed by continued graft maturation into the 2nd year and beyond. To improve the care of ACL injured patients, there is a critical need for clinical attention and scientific inquiry into timing the reintroduction of higher load activities in relationship to neuromuscular recovery, joint biology, and graft maturation. In addition to symptomatic and mechanical recovery, development and validation of biological markers for joint and cartilage homeostasis as well as ACL graft healing are needed for personalized decision making on rehabilitation needs, reduction of OA risk, and resumption of athletic, recreational, and vocational activities.

Health-Related Outcomes 3-15 Years Following Ankle Sprain Injury in Youth Sport: What Does the Future Hold?

BACKGROUND

This study examined the association between youth sport-related ankle sprain injury and health-related outcomes, 3-15 years postinjury.

METHODS

A historical cohort study in which uninjured controls were cluster-matched with injured cases. The primary outcome was self-reported Foot and Ankle Outcome Score (FAOS). Secondary outcomes included measures of adiposity, validated questionnaires for physical activity, athletic identity, fear of pain, and tests of strength, balance, and function.

RESULTS

We recruited 86 participants (median age of 23 years; 77% female); 50 with a time-loss ankle sprain, median of 8 years postinjury, and 36 uninjured controls cluster-matched by sex and sport. Based on mixed effects multivariable regression models, previously injured participants demonstrated poorer outcomes than controls on all 5 FAOS subscales regardless of sex and time since injury, with the largest differences observed in symptoms (-20.9, 99% CI: -29.5 to -12.3) and ankle-related quality of life (-25.3, 99% CI: -34.7 to -15.9) subscales. Injured participants also had poorer unipedal dynamic balance (-1.9, 99% CI: 3.5 to -0.2) and greater fear of pain (7.2, 99% CI: 0.9-13.4) compared with controls. No statistically significant differences were found for other secondary outcomes.

CONCLUSION

At 3-15 years following time-loss ankle sprain injury in youth sport, previously injured participants had more pain and symptoms, poorer self-reported function, ankle-related quality of life, reduced sport participation, balance, and greater fear of pain than controls. This underlines the need to promote the primary prevention of ankle sprains and secondary prevention of potential health consequences, including posttraumatic osteoarthritis.

LEVEL OF EVIDENCE

Level III, historical cohort study.

Cartilage Matrix Degeneration Occurs within the First Year after ACLR and Is Associated with Impaired Clinical Outcome

OBJECTIVE

Anterior cruciate ligament reconstruction (ACLR) has not been shown to decrease the risk for development of post-traumatic osteoarthritis. Magnetic resonance imaging (MRI) T2 mapping can be used to assess cartilage compositional changes. This study tests whether (1) worse cartilage arthroscopic status at ACLR is reflected by higher cartilage T2 values in matched study regions 6 weeks and 1 year after ACLR, and (2) increasing cartilage T2 values between 6 weeks and 1 year after ACLR are associated with worsening patient-reported outcomes.

DESIGN

Twenty-two participants with ACLR and 26 controls underwent 3T MRI. T2 values in medial and lateral femoral and tibial cartilage were measured at 6 weeks and 1 year after ACLR and compared with arthroscopic grades, Knee injury and Osteoarthritis Outcome Scores (KOOS), and control T2 values.

RESULTS

Most (59%-86%) cartilage study regions examined by arthroscopy demonstrated intact articular surfaces. Average T2 value increased in 3 of 4 study regions between 6 weeks and 1 year after ACLR (P = .001-.011). T2 value increased (P < .013) even for participants whose cartilage had intact articular surfaces at ACLR. Participants with ACLR who showed greater increases in cartilage T2 values had less improvement to KOOS Quality of Life (P = .009, ρ = -0.62).

DISCUSSION

Cartilage status assessed arthroscopically at ACLR and by MRI T2 maps 6 weeks later was healthier than cartilage status assessed by MRI T2 maps at 1-year follow-up. Progressive T2 elevations were observed over the first year after ACLR even in patients with arthroscopically intact cartilage at the time of surgery and were associated with reduced improvement in knee quality of life suggesting preosteoarthritis.

Quantification of Cartilage Surface Degeneration by Curvature Analysis Using 3D Scanning in a Rabbit Model

OBJECTIVE

Accurate analysis to quantify cartilage morphology is critical for evaluating degenerative conditions in osteoarthritis (OA). Three-dimensional (3D) optical scanning provides 3D data for the entire cartilage surface; however, there is no consensus on how to quantify it. Our purpose was to validate a 3D method for evaluating spatiotemporal alterations in degenerative cartilages in a rabbit OA model by analyzing their curvatures at various stages of progression.

DESIGN

Twelve rabbits underwent anterior cruciate ligament transection (ACLT) unilaterally and were divided into 4 groups: 4 weeks control, 4 weeks OA, 8 weeks control, and 8 weeks OA. 3D scanning, India ink staining, and histological assessments were performed in all groups. In 3D curvature visualization, the surfaces of the condyles were divided into 8 areas. The standard deviations (SD) of mean curvatures from all vertices of condylar surfaces and subareas were calculated.

RESULTS

Regarding the site of OA change, curvature analysis was consistent with India ink scoring. The SD of mean curvature correlated strongly with the India ink Osteoarthritis Research Society International (OARSI) score. In curvature histograms, the curvature distribution in OA was more scattered than in control. Of the 8 areas, significant OA progression in the posterolateral part of the lateral condyle (L-PL) was observed at 4 weeks. The histology result was consistent with the 3D evaluation in terms of representative section.

CONCLUSIONS

This study demonstrated that 3D scanning with curvature analysis can quantify the severity of cartilage degeneration objectively. Furthermore, the L-PL was found to be the initial area where OA degeneration occurred in the rabbit ACLT model.

Serum Calprotectin as a Blood-Based Biomarker for Monitoring Knee Osteoarthritis at Early but Not Late Stages

OBJECTIVE

The identification of early-stage osteoarthritis (OA) is crucial for the deceleration of its progression; however, no reliable biomarker is available for this purpose. The current study aimed to determine the role of serum calprotectin in the detection of early-stage knee OA.

DESIGN

In a case-control study, serum samples were collected from 84 patients with primary bilateral knee OA and 52 healthy controls. The radiographic grading of knee OA was performed using the Kellgren-Lawrence classification system. Serum concentrations of calprotectin were measured using an enzyme-linked immunosorbent assay.

RESULTS

The mean serum calprotectin level was 2908 ± 2516 ng/mL in OA patients and 901 ± 875 ng/mL in healthy control subjects (P < 0.001). Mean serum calprotectin levels were significantly higher in the lower stages of OA: 3740 ± 2728 ng/mL in OA grade I, 3100 ± 2084 ng/mL in OA grade II, 2246 ± 1418 ng/mL in OA grade III, and 2035 ± 765 ng/mL in OA grade IV (P = 0.047). Serum calprotectin levels were significantly higher in patients with a disease duration <42 months compared with those with a disease duration >42 months (P = 0.043).

CONCLUSION

Serum calprotectin level increases significantly in the early stages of OA and shows a reverse association with disease severity. Therefore, it could be suggested as a promising blood-based marker for early-stage knee OA.

Emerging and New Treatment Options for Knee Osteoarthritis

Osteoarthritis (OA) is the most prevalent type of arthritis worldwide, resulting in pain and often chronic disability and a significant burden on healthcare systems globally. Non-steroidal anti-inflammatory drugs (NSAIDs), analgesics, intra-articular corticosteroid injections are of little value in the long term, and opioids may have ominous consequences. Radiotherapy of knee OA has no added value. Physical therapy, exercises, weight loss, and lifestyle modifications may give pain relief, improve physical functioning and quality of life. However, no single treatment has regenerating potential for damaged articular cartilage. Due to a better understanding of osteoarthritis, innovative new treatment options have been developed. In this narrative review, we focus on emerging OA knee treatments, relieving symptoms, and regenerating damaged articular cartilage that includes intra-articular human serum albumin, conventional disease-modifying anti-rheumatic drugs (DMARDs), lipid-lowering agents (statin), nerve growth factors antagonists, bone morphogenetic protein, fibroblast growth factors, Platelet-Rich Plasma (PRP), Mesenchymal Stem Cells (MSC), exosomes, interleukin-1 blockers, gene-based therapy, and bisphosphonate.

Assessing collagen alterations in enzymatic degradation models of osteoarthritis via second harmonic generation microscopy

INTRODUCTION

Structural changes in the collagen II architecture of osteoarthritis (OA) are poorly understood, which is a large shortcoming in the early diagnosis of this disease. Though degradation can be simulated by enzymes including trypsin and bacterial collagenase, the specific structural features of each digestion and their relationship to naturally occurring OA remain unclear.

EXPERIMENTAL DESIGN

We used collagen sensitive/specific Second Harmonic Generation (SHG) microscopy in conjunction with optical scattering measurements to probe the resulting architecture changes in bovine knee cartilage upon trypsin and collagenase degradation. Image features extracted from SHG images were used to train a linear discriminant (LD) model capable of classifying enzymatic degradation, which was then applied to human cartilage with varied modified Mankin histological scores.

RESULTS

The treatment of cartilage with these enzymes resulted in more disorganized collagen structure, where this effect was greatest with collagenase treatment. Using the LD model, we classified the control and degraded tissues in the three zones with >92% accuracy, showing that these enzymes have distinct activity on the collagen assembly. Application of the LD model to human cartilage indicated that collagenase effects were more representative of in vivo degeneration and were also consistent with damage beginning at the articular surface and progressing into deeper zones.

CONCLUSIONS

SHG and optical scattering measurements successfully delineate trypsin and collagenase degradation and suggest that collagen alterations in human OA are better simulated by the latter mechanism. These results lay the groundwork for using high-resolution SHG and optical scattering as an earlier diagnostic tool than is currently available.

Quantitative analysis of the ACL and PCL using T1rho and T2 relaxation time mapping: an exploratory, cross-sectional comparison between OA and healthy control knees

Background

Quantitative magnetic resonance imaging (MRI) methods such as T1rho and T2 mapping are sensitive to changes in tissue composition, however their use in cruciate ligament assessment has been limited to studies of asymptomatic populations or patients with posterior cruciate ligament tears only. The aim of this preliminary study was to compare T1rho and T2 relaxation times of the anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) between subjects with mild-to-moderate knee osteoarthritis (OA) and healthy controls.

Methods

A single knee of 15 patients with mild-to-moderate knee OA (Kellgren-Lawrence grades 2–3) and of 6 age-matched controls was imaged using a 3.0 T MRI. Three-dimensional (3D) fat-saturated spoiled gradient recalled-echo images were acquired for morphological assessment and T1ρ- and T2-prepared pseudo-steady-state 3D fast spin echo images for compositional assessment of the cruciate ligaments. Manual segmentation of whole ACL and PCL, as well as proximal / middle / distal thirds of both ligaments was carried out by two readers using ITK-SNAP and mean relaxation times were recorded. Variation between thirds of the ligament were assessed using repeated measures ANOVAs and differences in these variations between groups using a Kruskal-Wallis test. Inter- and intra-rater reliability were assessed using intraclass correlation coefficients (ICCs).

Results

In OA knees, both T1rho and T2 values were significantly higher in the distal ACL when compared to the rest of the ligament with the greatest differences in T1rho (e.g. distal mean = 54.5 ms, proximal = 47.0 ms, p < 0.001). The variation of T2 values within the PCL was lower in OA knees (OA: distal vs middle vs proximal mean = 28.5 ms vs 29.1 ms vs 28.7 ms, p = 0.748; Control: distal vs middle vs proximal mean = 26.4 ms vs 32.7 ms vs 33.3 ms, p = 0.009). ICCs were excellent for the majority of variables.

Conclusion

T1rho and T2 mapping of the cruciate ligaments is feasible and reliable. Changes within ligaments associated with OA may not be homogeneous. This study is an important step forward in developing a non-invasive, radiological biomarker to assess the ligaments in diseased human populations in-vivo.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-021-04755-y.

Using Convolutional Neural Network with Taguchi Parametric Optimization for Knee Segmentation from X-Ray Images

Loss of knee cartilage can cause intense pain at the knee epiphysis and this is one of the most common diseases worldwide. To diagnose this condition, the distance between the femur and tibia is calculated based on X-ray images. Accurate segmentation of the femur and tibia is required to assist in the calculation process. Several studies have investigated the use of automatic knee segmentation to assist in the calculation process, but the results are of limited value owing to the complexity of the knee. To address this problem, this study exploits deep learning for robust segmentation not affected by the environment. In addition, the Taguchi method is applied to optimize the deep learning results. Deep learning architecture, optimizer, and learning rate are considered for the Taguchi table to check the impact and interaction of the results. When the Dilated-Resnet architecture is used with the Adam optimizer and a learning rate of 0.001, dice coefficients of 0.964 and 0.942 are obtained for the femur and tibia for knee segmentation. The implemented procedure and the results of this investigation may be beneficial to help in determining the correct margins for the femur and tibia and can be the basis for developing an automatic diagnosis algorithm for orthopedic diseases.

Visualizing pre-osteoarthritis: Integrating MRI UTE-T2* with mechanics and biology to combat osteoarthritis-The 2019 Elizabeth Winston Lanier Kappa Delta Award

Osteoarthritis (OA) is a leading cause of pain and disability for which disease-modifying treatments remain lacking. This is because the symptoms and radiographic changes of OA occur after the onset of likely irreversible changes. Defining and treating earlier disease states are therefore needed to delay or to halt OA progression. Taking this concept a step further, studying OA pathogenesis before disease onset by characterizing potentially reversible markers of increased OA risk to identify a state of "pre-osteoarthritis (pre-OA)" shifts the paradigm towards OA prevention. The purpose of this review is to summarize the 42 studies comprising the 2019 Kappa Delta Elizabeth Lanier Award where conceptualization of a systems-based definition for "pre-osteoarthritis (pre-OA)" was followed by demonstration of potentially reversible markers of heightened OA risk in patients after anterior cruciate ligament (ACL) injury and reconstruction. In the process, these efforts contributed a new magnetic resonance imaging method of ultrashort echo time (UTE) enhanced T2* mapping to visualize joint tissue damage before the development of irreversible changes. The studies presented here support a transformative approach to OA that accounts for interactions between mechanical, biological, and structural markers of OA risk to develop and evaluate new treatment strategies that can delay or prevent the onset of clinical disease. This body of work was inspired by and performed for patients. Shifting the paradigm from attempting to modify symptomatic radiographic OA towards monitoring and reversing markers of "pre-OA" opens the door for transforming the clinical approach to OA from palliation to prevention.