Cachexia in preclinical rheumatoid arthritis: Longitudinal observational study of thigh magnetic resonance imaging from osteoarthritis initiative cohort.

BACKGROUND: Preclinical rheumatoid arthritis (Pre-RA) is defined as the early stage before the development of clinical RA. While cachexia is a well-known and potentially modifiable complication of RA, it is not known if such an association exists also in the Pre-RA stage. To investigate such issue, we aimed to compare the longitudinal alterations in the muscle composition and adiposity of participants with Pre-RA with the matched controls. METHODS: In this observational cohort study, the Osteoarthritis Initiative (OAI) participants were categorized into Pre-RA and propensity score (PS)-matched control groups. Pre-RA was retrospectively defined as the absence of RA from baseline to year-2, with progression to physician-diagnosed clinical RA between years 3-8 of the follow-up period. Using a validated deep learning algorithm, we measured MRI biomarkers of thigh muscles and adiposity at baseline and year-2 follow-ups of the cohort. The outcomes were the differences between Pre-RA and control groups in the 2-year rate of change for thigh muscle composition [cross-sectional area (CSA) and intramuscular adipose tissue (Intra-MAT)] and adiposity [intermuscular adipose tissue (Inter-MAT) and subcutaneous adipose tissue (SAT)]. Linear mixed-effect regression models were used for comparison. RESULTS: After 1:3 PS-matching of the groups for confounding variables (demographics, risk factors, co-morbidities, and knee osteoarthritis status), 408 thighs (102 Pre-RA and 306 control) of 322 participants were included (age mean ± SD: 61.7 ± 8.9 years; female/male: 1.8). Over a 2-year period, Pre-RA was associated with a larger decrease in total thigh muscle CSA [estimate, 95% confidence interval (CI): -180.13 mm2/2-year, -252.80 to -107.47, P-value < 0.001]. Further examination of thigh muscle composition showed that the association of the presence of Pre-RA with a larger decrease in muscle CSA over 2 years was noticeable in the quadriceps, flexors, and sartorius muscle groups (P-values < 0.05). Comparison of changes in total adipose tissue showed no difference between Pre-RA and control participants (estimate, 95% CI: 48.48 mm2/2-year, -213.51 to 310.47, P-value = 0.691). However, in the detailed analysis of thigh adiposity, Pre-RA presence was associated with a larger increase in Inter-MAT (estimate, 95% CI: 150.55 mm2/2-year, 95.58 to 205.51, P-value < 0.001). CONCLUSIONS: Preclinical rheumatoid arthritis is associated with a decrease in muscle cross-sectional area and an increase in intermuscular adipose tissue, similar to rheumatoid cachexia in clinical rheumatoid arthritis. These findings suggest the presence of cachexia in the preclinical phase of rheumatoid arthritis. Given that cachexia, which can exacerbate health outcomes, is potentially modifiable, this study emphasizes the importance of early identification of patients in their preclinical phase.

Deep learning-based classification of erosion, synovitis and osteitis in hand MRI of patients with inflammatory arthritis.

OBJECTIVES: To train, test and validate the performance of a convolutional neural network (CNN)-based approach for the automated assessment of bone erosions, osteitis and synovitis in hand MRI of patients with inflammatory arthritis. METHODS: Hand MRIs (coronal T1-weighted, T2-weighted fat-suppressed, T1-weighted fat-suppressed contrast-enhanced) of rheumatoid arthritis (RA) and psoriatic arthritis (PsA) patients from the rheumatology department of the Erlangen University Hospital were assessed by two expert rheumatologists using the Outcome Measures in Rheumatology-validated RA MRI Scoring System and PsA MRI Scoring System scores and were used to train, validate and test CNNs to automatically score erosions, osteitis and synovitis. Scoring performance was compared with human annotations in terms of macro-area under the receiver operating characteristic curve (AUC) and balanced accuracy using fivefold cross-validation. Validation was performed on an independent dataset of MRIs from a second patient cohort. RESULTS: In total, 211 MRIs from 112 patients (14 906 region of interests (ROIs)) were included for training/internal validation using cross-validation and 220 MRIs from 75 patients (11 040 ROIs) for external validation of the networks. The networks achieved high mean (SD) macro-AUC of 92%±1% for erosions, 91%±2% for osteitis and 85%±2% for synovitis. Compared with human annotation, CNNs achieved a high mean Spearman correlation for erosions (90±2%), osteitis (78±8%) and synovitis (69±7%), which remained consistent in the validation dataset. CONCLUSIONS: We developed a CNN-based automated scoring system that allowed a rapid grading of erosions, osteitis and synovitis with good diagnostic accuracy and using less MRI sequences compared with conventional scoring. This CNN-based approach may help develop standardised cost-efficient and time-efficient assessments of hand MRIs for patients with arthritis.

Intra-Articular Mineralization on Computerized Tomography of the Knee and Risk of Cartilage Damage: The Multicenter Osteoarthritis Study.

OBJECTIVE: Intra-articular (IA) mineralization may contribute to osteoarthritis (OA) structural progression. We studied the association of IA mineralization on knee computed tomography (CT) with cartilage damage worsening on knee magnetic resonance imaging (MRI), with a focus on location- and tissue-specific effects. METHODS: Participants from the Multicenter Osteoarthritis Study with knee CT and MRI scans were included. Presence of IA mineralization on CT was defined as a Boston University Calcium Knee Score >0 anywhere in the knee. Cartilage worsening on MRI was defined as any increase in the MRI OA Knee Score, including incident damage. We evaluated the association of whole-knee, compartment-specific (ie, medial or lateral), and subregion-specific (ie, location-matched) IA mineralization at baseline with cartilage worsening at two years' follow-up in the corresponding locations using binomial regression with generalized estimating equations, adjusting for age, sex, and body mass index (BMI). RESULTS: We included 1,673 participants (mean age 60 years, 56% female, mean BMI 29). Nine percent had any IA mineralization in the knee, and 47.4% had any cartilage worsening on follow-up. Mineralization of any tissue in the knee, regardless of location, was not associated with MRI cartilage worsening. However, cartilage mineralization was associated with 1.39 (95% confidence interval 1.04-1.88) times higher risk of cartilage worsening in the same compartment, with similar results in subregion-specific analysis. CONCLUSION: CT-detected IA mineralization in the cartilage was associated with higher risk of MRI cartilage worsening in the same compartment and subregion over two years. These findings suggest potential localized, tissue-specific effects of IA mineralization on cartilage pathology in knee OA.

Primary anterior cruciate ligament repair-morphological and quantitative assessment by 7-T MRI and clinical outcome after 1.5 years.

OBJECTIVES: The purpose of this study was to assess morphological and quantitative changes of the anterior cruciate ligament (ACL) and cartilage after ACL repair. METHODS: 7T MRI of the knee was acquired in 31 patients 1.5 years after ACL repair and in 13 controls. Proton density-weighted images with fat saturation (PD-fs) were acquired to assess ACL width, signal intensity, elongation, and fraying. T2/T2* mapping was performed for assessment of ACL and cartilage. Segmentation of the ACL, femoral, and tibial cartilage was carried out at 12 ROIs. The outcome evaluation consisted of the Lysholm Knee Score and International Knee Documentation Committee (IKDC) subjective score and clinical examination. RESULTS: ACL showed a normal signal intensity in 96.8% and an increased width in 76.5% after repair. Fraying occurred in 22.6% without having an impact on the clinical outcome (Lysholm score: 90.39 ± 9.75, p = 0.76 compared to controls). T2 analysis of the ACL revealed no difference between patients and controls (p = 0.74). Compared to controls, assessment of the femoral and tibial cartilage showed a significant increase of T2* times in all ROIs, except at the posterolateral femur. Patients presented a good outcome in clinical examination with a Lysholm score of 87.19 ± 14.89 and IKDC of 80.23 ± 16.84. CONCLUSION: T2 mapping results suggest that the tissue composition of the ACL after repair is similar to that of a native ACL after surgery, whereas the ACL exhibits an increased width. Fraying of the ACL can occur without having any impact on functional outcomes. T2* analysis revealed early degradation at the cartilage. CLINICAL RELEVANCE STATEMENT: MRI represents a noninvasive diagnostic tool for the morphological and compositional assessment of the anterior cruciate ligament after repair, whereas knowledge about post-surgical alterations is crucial for adequate imaging interpretation. KEY POINTS: • There has been renewed interest in repairing the anterior cruciate ligament with a proximally torn ligament. • T2 times of the anterior cruciate ligament do not differ between anterior cruciate ligament repair patients and controls. • T2 mapping may serve as a surrogate for the evaluation of the anterior cruciate ligament after repair.

CD200+ fibroblasts form a pro-resolving mesenchymal network in arthritis.

Fibroblasts are important regulators of inflammation, but whether fibroblasts change phenotype during resolution of inflammation is not clear. Here we use positron emission tomography to detect fibroblast activation protein (FAP) as a means to visualize fibroblast activation in vivo during inflammation in humans. While tracer accumulation is high in active arthritis, it decreases after tumor necrosis factor and interleukin-17A inhibition. Biopsy-based single-cell RNA-sequencing analyses in experimental arthritis show that FAP signal reduction reflects a phenotypic switch from pro-inflammatory MMP3+/IL6+ fibroblasts (high FAP internalization) to pro-resolving CD200+DKK3+ fibroblasts (low FAP internalization). Spatial transcriptomics of human joints indicates that pro-resolving niches of CD200+DKK3+ fibroblasts cluster with type 2 innate lymphoid cells, whereas MMP3+/IL6+ fibroblasts colocalize with inflammatory immune cells. CD200+DKK3+ fibroblasts stabilized the type 2 innate lymphoid cell phenotype and induced resolution of arthritis via CD200-CD200R1 signaling. Taken together, these data suggest a dynamic molecular regulation of the mesenchymal compartment during resolution of inflammation.

Association of biochemical markers with bone marrow lesion changes on imaging-data from the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium.

BACKGROUND: To assess the prognostic value of short-term change in biochemical markers as it relates to bone marrow lesions (BMLs) on MRI in knee osteoarthritis (OA) over 24 months and, furthermore, to assess the relationship between biochemical markers involved with tissue turnover and inflammation and BMLs on MRI. METHODS: Data from the Foundation for the National Institutes of Health OA Biomarkers Consortium within the Osteoarthritis Initiative (n = 600) was analyzed. BMLs were measured according to the MRI Osteoarthritis Knee Score (MOAKS) system (0-3), in 15 knee subregions. Serum and urinary biochemical markers assessed were as follows: serum C-terminal crosslinked telopeptide of type I collagen (CTX-I), serum crosslinked N-telopeptide of type I collagen (NTX-I), urinary CTX-Iα and CTX-Iß, urinary NTX-I, urinary C-terminal cross-linked telopeptide of type II collagen (CTX-II), serum matrix metalloproteinase (MMP)-degraded type I, II, and III collagen (C1M, C2M, C3M), serum high sensitivity propeptide of type IIb collagen (hsPRO-C2), and matrix metalloproteinase-generated neoepitope of C-reactive protein (CRPM). The association between change in biochemical markers over 12 months and BMLs over 24 months was examined using regression models adjusted for covariates. The relationship between C1M, C2M, C3M, hsPRO-C2, and CRPM and BMLs at baseline and over 24 months was examined. RESULTS: Increases in serum CTX-I and urinary CTX-Iß over 12 months were associated with increased odds of changes in the number of subregions affected by any BML at 24 months. Increase in hsPRO-C2 was associated with decreased odds of worsening in the number of subregions affected by any BML over 24 months. C1M and C3M were associated with BMLs affected at baseline. CONCLUSIONS: Short-term changes in serum CTX-I, hsPRO-C2, and urinary CTX-Iß hold the potential to be prognostic of BML progression on MRI. The association of C1M and C3M with baseline BMLs on MRI warrants further investigation.

[Current MR imaging of cartilage in the context of knee osteoarthritis (part 1) : Principles and sequences]. / Aktuelle MRT-Bildgebung des Knorpels im Kontext der Gonarthrose (Teil 1) : Grundlagen und Sequenzen.

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

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.

Comparison of evaluation metrics of deep learning for imbalanced imaging data in osteoarthritis studies.

PURPOSE: To compare the evaluation metrics for deep learning methods that were developed using imbalanced imaging data in osteoarthritis studies. MATERIALS AND METHODS: This retrospective study utilized 2996 sagittal intermediate-weighted fat-suppressed knee MRIs with MRI Osteoarthritis Knee Score readings from 2467 participants in the Osteoarthritis Initiative study. We obtained probabilities of the presence of bone marrow lesions (BMLs) from MRIs in the testing dataset at the sub-region (15 sub-regions), compartment, and whole-knee levels based on the trained deep learning models. We compared different evaluation metrics (e.g., receiver operating characteristic (ROC) and precision-recall (PR) curves) in the testing dataset with various class ratios (presence of BMLs vs. absence of BMLs) at these three data levels to assess the model's performance. RESULTS: In a subregion with an extremely high imbalance ratio, the model achieved a ROC-AUC of 0.84, a PR-AUC of 0.10, a sensitivity of 0, and a specificity of 1. CONCLUSION: The commonly used ROC curve is not sufficiently informative, especially in the case of imbalanced data. We provide the following practical suggestions based on our data analysis: 1) ROC-AUC is recommended for balanced data, 2) PR-AUC should be used for moderately imbalanced data (i.e., when the proportion of the minor class is above 5% and less than 50%), and 3) for severely imbalanced data (i.e., when the proportion of the minor class is below 5%), it is not practical to apply a deep learning model, even with the application of techniques addressing imbalanced data issues.

Machine-learning predicted and actual 2-year structural progression in the IMI-APPROACH cohort.

In the Innovative Medicine's Initiative Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) knee osteoarthritis (OA) study, machine learning models were trained to predict the probability of structural progression (s-score), predefined as >0.3 mm/year joint space width (JSW) decrease and used as inclusion criterion. The current objective was to evaluate predicted and observed structural progression over 2 years according to different radiographic and magnetic resonance imaging (MRI)-based structural parameters. Radiographs and MRI scans were acquired at baseline and 2-year follow-up. Radiographic (JSW, subchondral bone density, osteophytes), MRI quantitative (cartilage thickness), and MRI semiquantitative [SQ; cartilage damage, bone marrow lesions (BMLs), osteophytes] measurements were obtained. The number of progressors was calculated based on a change exceeding the smallest detectable change (SDC) for quantitative measures or a full SQ-score increase in any feature. Prediction of structural progression based on baseline s-scores and Kellgren-Lawrence (KL) grades was analyzed using logistic regression. Among 237 participants, around 1 in 6 participants was a structural progressor based on the predefined JSW-threshold. The highest progression rate was seen for radiographic bone density (39%), MRI cartilage thickness (38%), and radiographic osteophyte size (35%). Baseline s-scores could only predict JSW progression parameters (most P>0.05), while KL grades could predict progression of most MRI-based and radiographic parameters (P<0.05). In conclusion, between 1/6 and 1/3 of participants showed structural progression during 2-year follow-up. KL scores were observed to outperform the machine-learning-based s-scores as progression predictor. The large amount of data collected, and the wide range of disease stage, can be used for further development of more sensitive and successful (whole joint) prediction models. Trial Registration: Clinicaltrials.gov number NCT03883568.

Associations of myosteatosis with disc degeneration: A 3T magnetic resonance imaging study in individuals with impaired glycaemia.

BACKGROUND: Intervertebral disc degeneration (IVDD) may be linked to dysregulations of skeletal muscle glucose metabolism and fatty alterations of muscle composition (Myosteatosis). Our aim was to evaluate the different associations of magnetic resonance imaging (MRI)-based paravertebral myosteatosis with lumbar disc degeneration in individuals with impaired glucose metabolism and normoglycaemic controls. METHODS: In total, 304 individuals (mean age: 56.3 ± 9.1 years, 53.6% male sex, mean body mass index [BMI]: 27.6 ± 4.7 kg/m2 ) from a population-based cohort study who underwent 3-Tesla whole-body chemical-shift-encoded (six echo times) and T2-weighted single-shot-fast-spin-echo MRI were included. Lumbar disc degeneration was assessed at motion segments L1 to L5, categorized according to the Pfirrmann score and defined as Pfirrmann grade > 2 and/or disc bulging/herniation on at least one segment. Fat content of the autochthonous back muscles and the quadratus lumborum muscle was quantified as proton density fat fraction (PDFFmuscle ). Logistic regression models adjusted for age, sex, BMI and regular physical activity were calculated to evaluate the association between PDFFmuscle and outcome IVDD. RESULTS: The overall prevalence of IVDD was 79.6%. There was no significant difference in the prevalence or severity distribution of IVDD between participants with or without impaired glucose metabolism (77.7% vs. 80.7%, P = 0.63 and P = 0.71, respectively). PDFFmuscle was significantly and positively associated with an increased risk for the presence of IVDD in participants with impaired glycaemia when adjusted for age, sex and BMI (PDFFautochthonous back muscles : odds ratio [OR] 2.16, 95% confidence interval [CI] [1.09, 4.3], P = 0.03; PDFFquadratus lumborum : OR 2.01, 95% CI [1.04, 3.85], P = 0.04). After further adjustment for regular physical activity, the results attenuated, albeit approaching statistical significance (PDFFautochthonous back muscles : OR 1.97, 95% CI [0.97, 3.99], P = 0.06; PDFFquadratus lumborum : OR 1.86, 95% CI [0.92, 3.76], P = 0.09). No significant associations were shown in healthy controls (PDFFautochthonous back muscles : OR 0.62, 95% CI [0.34, 1.14], P = 0.13; PDFFquadratus lumborum : OR 1.06, 95% CI [0.6, 1.89], P = 0.83). CONCLUSIONS: Paravertebral myosteatosis is positively associated with intervertebral disc disease in individuals with impaired glucose metabolism, independent of age, sex and BMI. Regular physical activity may confound these associations. Longitudinal studies will help to better understand the pathophysiological role of skeletal muscle in those with concomitant disturbed glucose haemostasis and intervertebral disc disease, as well as possible underlying causal relationships.

Development of a Magnetic Resonance Imaging-Based Definition of Knee Osteoarthritis: Data From the Multicenter Osteoarthritis Study.

OBJECTIVE: Although magnetic resonance imaging (MRI) is the imaging modality of choice for research, there is no widely accepted MRI definition of knee osteoarthritis (OA). We undertook this study to test the performance of different MRI definitions of OA. METHODS: We studied Multicenter Osteoarthritis Study participants with knee symptoms using posteroanterior and lateral knee radiographs and MRIs. Radiographic OA was defined as Kellgren/Lawrence grade ≥2 in the tibiofemoral (TF) and/or patellofemoral (PF) joint. Symptomatic OA was defined using a validated questionnaire. MRI findings of cartilage damage, osteophytes, bone marrow lesions (BMLs), and synovitis were scored using the Whole-Organ MRI Score system. We compared definitions using combinations of MRI features to the validation criteria of prevalent radiographic OA and symptomatic OA. All combinations included cartilage damage score ≥2 (0-6 scale) and osteophyte score ≥2 (0-6 scale); addition of BMLs and synovitis score was also tested. We also evaluated a Delphi panel definition that defined OA differently for the PF and TF joints. For each definition, we calculated sensitivity, specificity, and the area under the curve (AUC). RESULTS: We included 1,185 knees from 1,185 participants (mean age 66 years, 62% female, 89% White). Among the 1,185 knees, 482 knees had radiographic OA, and 524 knees had symptomatic OA. The MRI definitions with a cartilage score ≥2 and osteophyte score ≥2 and definitions which added BMLs or synovitis score ≥1 had the highest sensitivities (95.2% and 94.5%, respectively) for prevalent radiographic OA (AUCs 0.67 and 0.69, respectively), and also had the highest sensitivities for symptomatic OA. The Delphi panel definition had similar performance but was more complex to apply. CONCLUSION: An MRI OA definition requiring cartilage damage and a small osteophyte with or without BMLs or synovitis had the best performance and was simplest for identifying radiographic OA and symptomatic OA.

Worsening of Articular Tissue Damage as Defined by Semi-Quantitative MRI Is Associated With Concurrent Quantitative Cartilage Loss Over 24 Months.

OBJECTIVE: To assess the association of worsening of magnetic resonance imaging (MRI) semi-quantitative (SQ) tissue features with concurrent change in quantitative (Q) cartilage thickness measurements over 24 months within the Foundation for the National Institutes of Health (FNIH) Biomarker Consortium study. METHODS: In all, 599 participants were included. SQ assessment included cartilage damage, meniscal extrusion and damage, osteophytes, bone marrow lesions (BMLs), and effusion- and Hoffa-synovitis. Change in medial compartment Q cartilage thickness was stratified by concurrent ipsicompartmental SQ changes. Between-group comparisons were performed using analysis of covariance (ANCOVA) with adjustment for age, sex, and body mass index (BMI). Results were presented as adjusted mean difference. RESULTS: Knees with any increase in SQ cartilage scores in the medial compartment (n = 268) showed more Q cartilage loss compared to knees that remained stable (mean adjusted difference [MAD] = -0.16 mm, 95% confidence interval [CI]: [-0.19, -0.13] mm). Knees with any increase in meniscal extrusion in the medial compartment (n = 98) showed more Q cartilage loss than knees without (MAD = -0.18 mm, 95% CI: [-0.22, -0.14] mm. Comparable findings were seen for meniscal damage worsening. Regarding BMLs, an increase by one subregion resulted in a MAD of Q cartilage loss of -0.10 mm, 95% CI: [-0.14, -0.06] mm, while this effect almost tripled for change in two or more subregions. Increase in either effusion- and/or Hoffa-synovitis by one grade resulted in a MAD of -0.07 mm, 95% CI: [-0.10, -0.03] mm. CONCLUSION: Worsening of SQ cartilage damage, meniscal extrusion and damage, number of subregions affected by BML, maximum size of BMLs and worsening of effusion- and/or Hoffa synovitis is associated with increased Q cartilage loss.

Structural phenotypes of knee osteoarthritis: potential clinical and research relevance.

A joint contains many different tissues that can exhibit pathological changes, providing many potential targets for treatment. Researchers are increasingly suggesting that osteoarthritis (OA) comprises several phenotypes or subpopulations. Consequently, a treatment for OA that targets only one pathophysiologic abnormality is unlikely to be similarly efficacious in preventing or delaying the progression of all the different phenotypes of structural OA. Five structural phenotypes have been proposed, namely the inflammatory, meniscus-cartilage, subchondral bone, and atrophic and hypertrophic phenotypes. The inflammatory phenotype is characterized by marked synovitis and/or joint effusion, while the meniscus-cartilage phenotype exhibits severe meniscal and cartilage damage. Large bone marrow lesions characterize the subchondral bone phenotype. The hypertrophic and atrophic OA phenotype are defined based on the presence large osteophytes or absence of any osteophytes, respectively, in the presence of concomitant cartilage damage. Limitations of the concept of structural phenotyping are that they are not mutually exclusive and that more than one phenotype may be present. It must be acknowledged that a wide range of views exist on how best to operationalize the concept of structural OA phenotypes and that the concept of structural phenotypic characterization is still in its infancy. Structural phenotypic stratification, however, may result in more targeted trial populations with successful outcomes and practitioners need to be aware of the heterogeneity of the disease to personalize their treatment recommendations for an individual patient. Radiologists should be able to define a joint at risk for progression based on the predominant phenotype present at different disease stages.

Crystal arthropathies and osteoarthritis-where is the link?

Osteoarthritis (OA) is one of the leading causes of disability worldwide. As our understanding of OA progressively has moved from a purely mechanical "wear and tear" concept toward a complex multi-tissue condition in which inflammation plays a central role, the possible role of crystal-induced inflammation in OA incidence and progression may be relevant. In addition to gout, which affects 4% of the US population, basic calcium phosphate and calcium pyrophosphate deposition both may induce joint inflammation and may play a role in pain in OA. This narrative review article discusses the possible mechanisms underlying the associations between crystal-induced arthropathies and OA, and the important implications of these for clinical practice and future research.

Time-of-Flight Angiography in Ultra-High-Field 7 T MRI for the Evaluation of Peroneal Perforator Arteries Before Osseomyocutaneous Flap Surgery.

OBJECTIVES: Presurgical identification and morphologic characterization of the peroneal perforator arteries (PPAs) are essential for osseomyocutaneous flap surgery. The aim of this study was to evaluate PPAs using time-of-flight (TOF) angiography in 7 T magnetic resonance imaging in comparison with dual-energy computed tomographic angiography (CTA). MATERIALS AND METHODS: In this prospective study, TOF angiography and CTA of both lower legs were acquired before flap surgery from 07/2019 to 02/2020. Magnetic resonance imaging was performed using a dedicated 28-channel knee coil with an acquisition time of 9:55 minutes (voxel size: 0.4 × 0.4 × 0.8 mm). Computed tomographic angiography was acquired with a third-generation dual-source computed tomography on the same day. Virtual monoenergetic reconstructions at 40 keV photon energy served as the standard of reference for PPA identification and subtyping. Two independent readers assessed the image quality, quantity, length assessment, and classification according to surgical considerations of PPAs for TOF angiography and CTA. Both TOF angiography and CTA were used for presurgical flap design and were evaluated by an orofacial surgeon. RESULTS: Ten patients (mean age, 59.9 ± 14.9 years; 7 men) were included. Time-of-flight angiography and CTA identified 53 and 51 PPAs in total, respectively. Time-of-flight angiography showed superior image quality (both readers, P < 0.05). Time-of-flight angiography enabled specific classification of PPA subtypes more often (53 vs 39; P < 0.05), and both readers reported higher diagnostic confidence for TOF angiography than CTA in all patients (interrater agreement κ = 0.8; P < 0.05). Regarding length assessment, PPAs were significantly more conspicuous with TOF angiography (TOF mean , 50 ± 11 mm; CTA mean , 40 ± 9 mm; P = 0.001). In comparison with CTA, TOF angiography prospectively changed the orofacial surgeon's final decision on the presurgical selected PPAs in 60% of cases. CONCLUSIONS: Presurgical assessment of PPAs is feasible using TOF in 7 T magnetic resonance imaging. Moreover, TOF angiography was superior to CTA for classifying and identifying PPAs, which may facilitate the planning of reconstructive surgery.

Structural tissue damage and 24-month progression of semi-quantitative MRI biomarkers of knee osteoarthritis in the IMI-APPROACH cohort.

BACKGROUND: The IMI-APPROACH cohort is an exploratory, 5-centre, 2-year prospective follow-up study of knee osteoarthritis (OA). Aim was to describe baseline multi-tissue semiquantitative MRI evaluation of index knees and to describe change for different MRI features based on number of subregion-approaches and change in maximum grades over a 24-month period. METHODS: MRIs were acquired using 1.5 T or 3 T MRI systems and assessed using the semi-quantitative MRI OA Knee Scoring (MOAKS) system. MRIs were read at baseline and 24-months for cartilage damage, bone marrow lesions (BML), osteophytes, meniscal damage and extrusion, and Hoffa- and effusion-synovitis. In descriptive fashion, the frequencies of MRI features at baseline and change in these imaging biomarkers over time are presented for the entire sample in a subregional and maximum score approach for most features. Differences between knees without and with structural radiographic (R) OA are analyzed in addition. RESULTS: Two hundred eighty-nine participants had readable baseline MRI examinations. Mean age was 66.6 ± 7.1 years and participants had a mean BMI of 28.1 ± 5.3 kg/m2. The majority (55.3%) of included knees had radiographic OA. Any change in total cartilage MOAKS score was observed in 53.1% considering full-grade changes only, and in 73.9% including full-grade and within-grade changes. Any medial cartilage progression was seen in 23.9% and any lateral progression on 22.1%. While for the medial and lateral compartments numbers of subregions with improvement and worsening of BMLs were very similar, for the PFJ more improvement was observed compared to worsening (15.5% vs. 9.0%). Including within grade changes, the number of knees showing BML worsening increased from 42.2% to 55.6%. While for some features 24-months change was rare, frequency of change was much more common in knees with vs. without ROA (e.g. worsening of total MOAKS score cartilage in 68.4% of ROA knees vs. 36.7% of no-ROA knees, and 60.7% vs. 21.8% for an increase in maximum BML score per knee). CONCLUSIONS: A wide range of MRI-detected structural pathologies was present in the IMI-APPROACH cohort. Baseline prevalence and change of features was substantially more common in the ROA subgroup compared to the knees without ROA. TRIAL REGISTRATION: Clinicaltrials.gov identification: NCT03883568.

Update: Posttreatment Imaging of the Knee after Cartilage Repair.

Focal cartilage lesions are common pathologies at the knee joint that are considered important risk factors for the premature development of osteoarthritis. A wide range of surgical options, including but not limited to marrow stimulation, osteochondral auto- and allografting, and autologous chondrocyte implantation, allows for targeted treatment of focal cartilage defects. Arthroscopy is the standard of reference for the assessment of cartilage integrity and quality before and after repair. However, deep cartilage layers, intrachondral composition, and the subchondral bone are only partially or not at all visualized with arthroscopy. In contrast, magnetic resonance imaging offers noninvasive evaluation of the cartilage repair site, the subchondral bone, and the soft tissues of the joint pre- and postsurgery. Radiologists need to be familiar with the different surgical procedures available and their characteristic postsurgical imaging appearances to assess treatment success and possible complications adequately. We provide an overview of the most commonly performed surgical procedures for cartilage repair at the knee and typical postsurgical imaging characteristics.

Editorial Commentary: Arthroscopic Partial Meniscectomy Outcomes Are Worse in Patients With Concomitant Pathology.

Arthroscopic debridement for degenerative joint disease has not been shown to be beneficial, and initial nonoperative management is now recommended for degenerative meniscal tears. Indications for arthroscopic partial meniscectomy (APM) are traumatic tears with a clear history of mechanical symptoms, such as locking and catching, with joint-line pain or acute onset of symptoms that have failed nonsurgical treatment. Predictors of dissatisfaction with APM include female sex, obesity, and lateral meniscal tears. Beyond such demographic factors, concomitant joint pathology negatively affects outcomes of APM because a large majority of patients without radiographic osteoarthritis (OA) have evidence of concomitant tissue changes considered to be associated with OA including chondral damage, subchondral bone changes, signs of inflammation or ligament pathology. Particularly relevant seem to be chondral lesions radiologists would label as "delaminating," which are those a surgeon might call an "impending loose bodies." Cartilage repair surgery may be indicated in these cases.

Advanced neural networks for classification of MRI in psoriatic arthritis, seronegative, and seropositive rheumatoid arthritis.

OBJECTIVES: To evaluate whether neural networks can distinguish between seropositive RA, seronegative RA, and PsA based on inflammatory patterns from hand MRIs and to test how psoriasis patients with subclinical inflammation fit into such patterns. METHODS: ResNet neural networks were utilized to compare seropositive RA vs PsA, seronegative RA vs PsA, and seropositive vs seronegative RA with respect to hand MRI data. Results from T1 coronal, T2 coronal, T1 coronal and axial fat-suppressed contrast-enhanced (CE), and T2 fat-suppressed axial sequences were used. The performance of such trained networks was analysed by the area under the receiver operating characteristics curve (AUROC) with and without presentation of demographic and clinical parameters. Additionally, the trained networks were applied to psoriasis patients without clinical arthritis. RESULTS: MRI scans from 649 patients (135 seronegative RA, 190 seropositive RA, 177 PsA, 147 psoriasis) were fed into ResNet neural networks. The AUROC was 75% for seropositive RA vs PsA, 74% for seronegative RA vs PsA, and 67% for seropositive vs seronegative RA. All MRI sequences were relevant for classification, however, when deleting contrast agent-based sequences the loss of performance was only marginal. The addition of demographic and clinical data to the networks did not provide significant improvements for classification. Psoriasis patients were mostly assigned to PsA by the neural networks, suggesting that a PsA-like MRI pattern may be present early in the course of psoriatic disease. CONCLUSION: Neural networks can be successfully trained to distinguish MRI inflammation related to seropositive RA, seronegative RA, and PsA.