Sexual dimorphism in articular tissue anatomy - Key to understanding sex differences in osteoarthritis?

OBJECTIVE: Osteoarthritis (OA) prevalence and incidence varies between women and men, but it is unknown whether this follows sex-specific differences in systemic factors (e.g. hormones) and/or differences in pre-morbid joint anatomy. We recognize that classifications of sex within humans cannot be reduced to female/male, but given the lack of literature on non-binary individuals, this review is limited to the sexual dimorphism of articular morphotypes. METHODS: Based on a Pubmed search using relevant terms, and input from experts, we selected articles based on the authors' judgment of their relevance, interest, originality, and scientific quality; no "hard" bibliometric measures were used to evaluate their quality or importance. Focus was on clinical rather than pre-clinical studies, with most (imaging) data being available for the knee joint. RESULTS: After introducing "sexual dimorphism", the specific literature on articular morphotypes is reviewed, structured by: radiographic joint space width (JSW), meniscus, ligaments, articular cartilage morphology, articular cartilage composition and deformation, and articular tissue response to treatment. CONCLUSIONS: Sex-specific differences were clearly observed for JSW, meniscus damage, ligament size, and cartilage morphometry (volume, thickness, and surface areas) but not for cartilage composition. Ligament and cartilage measures were smaller in women even after matching for confounders. Taken together, the findings indicate that female (knee) joints may be structurally more vulnerable and at greater risk of OA. The "one size/sex fits all" approach must be abandoned in OA research, and all observational and interventional studies should report their results for sex-specific strata, at least in pre-specified secondary or post-hoc analyses.

30 Years of MRI-based cartilage & bone morphometry in knee osteoarthritis: From correlation to clinical trials.

OBJECTIVE: The first publication on morphometric analysis of articular cartilage using magnetic resonance imaging (MRI) in 1994 set the scene for a game change in osteoarthritis (OA) research. The current review highlights milestones in cartilage and bone morphometry, summarizing the rapid progress made in imaging, its application to understanding joint (patho-)physiology, and its use in interventional clinical trials. METHODS: Based on a Pubmed search of articles from 1994 to 2023, the authors subjectively selected representative work illustrating important steps in the development or application of magnetic resonance-based cartilage and bone morphometry, with a focus on studies in humans, and on the knee. Research on OA-pathophysiology is addressed only briefly, given length constraints. Compositional and semi-quantitative assessment are not covered here. RESULTS: The selected articles are presented in historical order as well as by content. We review progress in the technical aspects of image acquisition, segmentation and analysis, advances in understanding tissue growth, physiology, function, and adaptation, and a selection of clinical trials examining the efficacy of interventions on knee cartilage and bone. A perspective is provided of how lessons learned may be applied to future research and clinical management. CONCLUSIONS: Over the past 30 years, MRI-based morphometry of cartilage and bone has contributed to a paradigm shift in understanding articular tissue physiology and OA pathophysiology, and to the development of new treatment strategies. It is likely that these technologies will continue to play a key role in the development and (accelerated) approval of therapy, potentially targeted to different OA phenotypes.

Anterior cruciate ligament injury and age affect knee cartilage T2 but not thickness.

OBJECTIVE: To investigate the effect of unilateral anterior cruciate ligament (ACL) injury on cartilage thickness and composition, specifically laminar transverse relaxation time (T2) by magnetic resonance imaging (MRI), in younger and older participants and to compare within-person side differences in these parameters between ACL-injured and healthy controls. DESIGN: Quantitative double-echo steady-state 3 Tesla MRI-sequences were acquired in both knees of 85 participants in four groups: 20-30 years: healthy, HEA20-30, n = 24; ACL-injured, ACL20-30, n = 23; 40-60 years: healthy, HEA40-60, n = 24; ACL-injured, ACL40-60, n = 14 (ACL injury 2-10 years prior to study inclusion). Weight-bearing femorotibial cartilages were manually segmented; cartilage T2 and thickness were computed using custom software. Mean and side differences in subregional cartilage thickness, superficial and deep cartilage T2 were compared within and between groups using non-parametric statistics. RESULTS: Cartilage thickness did not differ within or between groups. Only the side difference in medial femorotibial cartilage thickness was greater in ACL20-30 than in HEA20-30. Deep zone T2 was longer in the ACL-injured than in the contralateral uninjured knees and than in healthy controls, especially in the lateral compartment. Most ACL-injured participants had side differences in femorotibial deep zone T2 above the threshold derived from controls. CONCLUSION: In the ACL-injured knee, early compositional differences in femorotibial cartilage (T2) appear to occur in the deep zone and precede cartilage thickness loss. These results suggest that monitoring laminar T2 after ACL injury may be useful in diagnosing and monitoring early articular cartilage changes.

Is detection of disease-modifying osteoarthritis drug treatment more effective when performing cartilage morphometry without blinding to MR image acquisition order?

OBJECTIVE: We here explore whether observed treatment effects of a putative disease-modifying osteoarthritis drug (DMOAD) are greater when cartilage morphometry is performed with rather than without knowledge of magnetic resonance imaging (MRI) acquisition order (unblinded/blinded to time point). METHODS: In the FORWARD (FGF-18 Osteoarthritis Randomized Controlled Trial with Administration of Repeated Doses) randomized controlled trial, 549 knee osteoarthritis patients were randomized 1:1:1:1:1 to three once-weekly intra-articular injections of placebo, 30 µg sprifermin every 6 or 12 months (M), or 100 µg every 6/12 M. After year 2, cartilage segmentation of BL through 24 M MRIs was performed, with blinding to acquisition order. After year 5, 24 and 60 M MRIs were analyzed together, with unknown relative order, but with segmented BL images as reference (24 M unblinded vs. BL), by the same operators. Total femorotibial joint cartilage thickness (TFTJ_ThC) change was obtained for 352 participants analyzed under both conditions. RESULTS: Twenty-four-month data read unblinded to order revealed a -35 ± 44 µm lower TFTJ_ThC than blinded analysis (all groups: lower/upper bounds -120/+51 µm; correlation r2 = 97%). With unblinded analysis, the placebo group lost -46 ± 57 µm TFTJ_ThC over 24 M, whereas 100 µg/every 6 M lost -2.2 ± 73 µm (difference =44 µm [95% CI: 22, 66]). With blinded analysis, placebo lost -11 ± 53 µm, whereas 100 µg/every 6 M gained 30 ± 62 µm (difference = 40 µm [95% CI: 21, 60]). 100 µg sprifermin injected every 6 M showed statistically significant (p < 0.001) treatment effects on TFTJ_ThC, with Cohen D = -0.66 for unblinded and D = -0.69 for blinded analysis. CONCLUSIONS: These results do not reveal that detection of proposed DMOAD treatment is enhanced with MRIs read unblinded to order; rather, the sensitivity is similar to blinded analysis. Choices on blinded vs. unblinded analysis may thus be based on other criteria.

Association between knee magnetic resonance imaging markers and knee symptoms over 6-9 years in young adults.

OBJECTIVES: To describe associations between MRI markers with knee symptoms in young adults. METHODS: Knee symptoms were assessed using the WOMAC scale during the Childhood Determinants of Adult Health Knee Cartilage study (CDAH-knee; 2008-2010) and at the 6- to 9-year follow-up (CDAH-3; 2014-2019). Knee MRI scans obtained at baseline were assessed for morphological markers (cartilage volume, cartilage thickness, subchondral bone area) and structural abnormalities [cartilage defects and bone marrow lesions (BMLs)]. Univariable and multivariable (age, sex, BMI adjusted) zero-inflated Poisson (ZIP) regression models were used for analysis. RESULTS: The participants' mean age in CDAH-knee and CDAH-3 were 34.95 (s.d. 2.72) and 43.27 (s.d. 3.28) years, with 49% and 48% females, respectively. Cross-sectionally, there was a weak but significant negative association between medial femorotibial compartment (MFTC) [ratio of the mean (RoM) 0.99971084 (95% CI 0.9995525, 0.99986921), P < 0.001], lateral femorotibial compartment (LFTC) [RoM 0.99982602 (95% CI 0.99969915, 0.9999529), P = 0.007] and patellar cartilage volume [RoM 0.99981722 (95% CI 0.99965326, 0.9999811), P = 0.029] with knee symptoms. Similarly, there was a negative association between patellar cartilage volume [RoM 0.99975523 (95% CI 0.99961427, 0.99989621), P = 0.014], MFTC cartilage thickness [RoM 0.72090775 (95% CI 0.59481806, 0.87372596), P = 0.001] and knee symptoms assessed after 6-9 years. The total bone area was negatively associated with knee symptoms at baseline [RoM 0.9210485 (95% CI 0.8939677, 0.9489496), P < 0.001] and 6-9 years [RoM 0.9588811 (95% CI 0.9313379, 0.9872388), P = 0.005]. The cartilage defects and BMLs were associated with greater knee symptoms at baseline and 6-9 years. CONCLUSION: BMLs and cartilage defects were positively associated with knee symptoms, whereas cartilage volume and thickness at MFTC and total bone area were weakly and negatively associated with knee symptoms. These results suggest that the quantitative and semiquantitative MRI markers can be explored as a marker of clinical progression of OA in young adults.

Imaging Biomarkers of Osteoarthritis.

Currently no disease-modifying osteoarthritis drug has been approved for the treatment of osteoarthritis (OA) that can reverse, hold, or slow the progression of structural damage of OA-affected joints. The reasons for failure are manifold and include the heterogeneity of structural disease of the OA joint at trial inclusion, and the sensitivity of biomarkers used to measure a potential treatment effect.This article discusses the role and potential of different imaging biomarkers in OA research. We review the current role of radiography, as well as advances in quantitative three-dimensional morphological cartilage assessment and semiquantitative whole-organ assessment of OA. Although magnetic resonance imaging has evolved as the leading imaging method in OA research, recent developments in computed tomography are also discussed briefly. Finally, we address the experience from the Foundation for the National Institutes of Health Biomarker Consortium biomarker qualification study and the future role of artificial intelligence.

Evaluation of an automated laminar cartilage T2 relaxation time analysis method in an early osteoarthritis model.

OBJECTIVE: A fully automated laminar cartilage composition (MRI-based T2) analysis method was technically and clinically validated by comparing radiographically normal knees with (CL-JSN) and without contra-lateral joint space narrowing or other signs of radiographic osteoarthritis (OA, CL-noROA). MATERIALS AND METHODS: 2D U-Nets were trained from manually segmented femorotibial cartilages (n = 72) from all 7 echoes (AllE), or from the 1st echo only (1stE) of multi-echo-spin-echo (MESE) MRIs acquired by the Osteoarthritis Initiative (OAI). Because of its greater accuracy, only the AllE U-Net was then applied to knees from the OAI healthy reference cohort (n = 10), CL-JSN (n = 39), and (1:1) matched CL-noROA knees (n = 39) that all had manual expert segmentation, and to 982 non-matched CL-noROA knees without expert segmentation. RESULTS: The agreement (Dice similarity coefficient) between automated vs. manual expert cartilage segmentation was between 0.82 ± 0.05/0.79 ± 0.06 (AllE/1stE) and 0.88 ± 0.03/0.88 ± 0.03 (AllE/1stE) across femorotibial cartilage plates. The deviation between automated vs. manually derived laminar T2 reached up to - 2.2 ± 2.6 ms/ + 4.1 ± 10.2 ms (AllE/1stE). The AllE U-Net showed a similar sensitivity to cross-sectional laminar T2 differences between CL-JSN and CL-noROA knees in the matched (Cohen's D ≤ 0.54) and the non-matched (D ≤ 0.54) comparison as the matched manual analyses (D ≤ 0.48). Longitudinally, the AllE U-Net also showed a similar sensitivity to CL-JSN vs. CS-noROA differences in the matched (D ≤ 0.51) and the non-matched (D ≤ 0.43) comparison as matched manual analyses (D ≤ 0.41). CONCLUSION: The fully automated T2 analysis showed a high agreement, acceptable accuracy, and similar sensitivity to cross-sectional and longitudinal laminar T2 differences in an early OA model, compared with manual expert analysis. TRIAL REGISTRATION: Clinicaltrials.gov identification: NCT00080171.

Association of quantitative measures of medial meniscal extrusion with structural and symptomatic knee osteoarthritis progression - Data from the OAI FNIH biomarker study.

OBJECTIVE: To study the association of quantitative medial meniscal position measures with radiographic and symptomatic knee osteoarthritis (OA) progression over 2-4 years. METHODS: The FNIH OAI Biomarkers study comprised 600 participants in four subgroups: 194 case knees with combined structural (medial minimum joint space width (minJSW) loss ≥0.7 mm) and symptomatic (persistent Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale increase ≥9 [0-100 scale]) progression; 200 knees with neither structural nor symptomatic progression; 103 knees with isolated structural and 103 with isolated symptomatic progression. Coronal double echo at steady state (DESS) MRIs were used for segmenting five central slices of the medial meniscus. Associations with progression were examined using logistic regression (adjusted for demographic and clinical data). RESULTS: Greater baseline medial meniscal extrusion was associated with combined structural/symptomatic progression (OR 1.59; 95%CI: [1.25,2.04]). No relationship was observed for tibial plateau coverage or meniscal overlap distance. The two-year increase in meniscal extrusion (OR 1.48 [1.21, 1.83]), and reduction in tibial plateau coverage (OR 0.70 [0.58,0.86]) and overlap distance (OR 0.73 [0.60,0.89]) were associated with combined progression. Greater baseline extrusion was associated with isolated structural and less extrusion with isolated symptomatic progression. The longitudinal increase in meniscal extrusion, and reduction in tibial plateau coverage and overlap distance were associated with structural, but not with symptomatic progression. CONCLUSION: Baseline measures of medial meniscal extrusion were consistently positively associated with combined radiographic/symptomatic progression and with isolated structural, but not with isolated symptomatic progression. These measures may therefore allow one to assess the risk of structural knee OA progression and to monitor interventions restoring meniscal position and function.

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.

Quantitative measurement of cartilage morphology in osteoarthritis: current knowledge and future directions.

Quantitative measures of cartilage morphology ("cartilage morphometry") extracted from high resolution 3D magnetic resonance imaging (MRI) sequences have been shown to be sensitive to osteoarthritis (OA)-related change and also to treatment interventions. Cartilage morphometry is therefore nowadays widely used as outcome measure for observational studies and randomized interventional clinical trials. The objective of this narrative review is to summarize the current status of cartilage morphometry in OA research, to provide insights into aspects relevant for the design of future studies and clinical trials, and to give an outlook on future developments. It covers the aspects related to the acquisition of MRIs suitable for cartilage morphometry, the analysis techniques needed for deriving quantitative measures from the MRIs, the quality assurance required for providing reliable cartilage measures, and the appropriate participant recruitment criteria for the enrichment of study cohorts with knees likely to show structural progression. Finally, it provides an overview over recent clinical trials that relied on cartilage morphometry as a structural outcome measure for evaluating the efficacy of disease-modifying OA drugs (DMOAD).

Exploring the differences between radiographic joint space width and MRI cartilage thickness changes using data from the IMI-APPROACH cohort.

OBJECTIVE: Longitudinal weight-bearing radiographic joint space width (JSW) and non-weight-bearing MRI-based cartilage thickness changes often show weak correlations. The current objective was to investigate these correlations, and to explore the influence of different factors that could contribute to longitudinal differences between the two methods. METHODS: The current study included 178 participants with medial osteoarthritis (OA) out of the 297 knee OA participants enrolled in the IMI-APPROACH cohort. Changes over 2 years in medial JSW (ΔJSWmed), minimum JSW (ΔJSWmin), and medial femorotibial cartilage thickness (ΔMFTC) were assessed using linear regression, using measurements from radiographs and MRI acquired at baseline, 6 months, and 1 and 2 years. Pearson R correlations were calculated. The influence of cartilage quality (T2 mapping), meniscal extrusion (MOAKS scoring), potential pain-induced unloading (difference in knee-specific pain scores), and increased loading (BMI) on the correlations was analyzed by dividing participants in groups based on each factor separately, and comparing correlations (slope and strength) between groups using linear regression models. RESULT: Correlations between ΔMFTC and ΔJSWmed and ΔJSWmin were statistically significant (p < 0.004) but weak (R < 0.35). Correlations were significantly different between groups based on cartilage quality and on meniscal extrusion: only patients with the lowest T2 values and with meniscal extrusion showed significant moderate correlations. Pain-induced unloading or BMI-induced loading did not influence correlations. CONCLUSIONS: While the amount of loading does not seem to make a difference, weight-bearing radiographic JSW changes are a better reflection of non-weight-bearing MRI cartilage thickness changes in knees with higher quality cartilage and with meniscal extrusion.

Responsiveness of Subcutaneous Fat, Intermuscular Fat, and Muscle Anatomical Cross-Sectional Area of the Thigh to Longitudinal Body Weight Loss and Gain: Data from the Osteoarthritis Initiative (OAI).

Thigh subcutaneous (SCF) and intermuscular (IMF) fat have been associated with joint health and function. Here, we explore the (sex-specific) responsiveness of SCF, IMF, and muscle during longitudinal weight loss and gain, as well as the change in questionnaire-based and physical performance-based knee function measures. This exploratory study included 103 Osteoarthritis Initiative (OAI) participants, who displayed a ≥10% weight loss or gain between baseline (BL) and 2-year (Y2) follow-up (and maintained half of that weight loss until year 4) and had axial 3T magnetic resonance images (MRI) for measuring SCF, IMF, and muscle cross sectional areas (CSAs). The standardized response mean (SRM = mean divided by the standard deviation of the change) was used as a measure of responsiveness. A total of 52 OAI participants (73% women) displayed ≥10% weight loss, and 51 (67% women) ≥10% weight gain. Both SCF and IMF CSAs showed a significant decrease (mean change) with weight loss (SCF: -22%, SRM = -1.2; IMF: -15%, SRM = -0.7) and a significant increase with weight gain (SCF: +27%, SRM = 1.1; IMF: +21%, SRM = 0.6). Muscle CSAs showed significant changes during weight loss (extensor: -8.3%, SRM = -1.1; flexor: -7.2%, SRM = -1.0), but not during weight gain. Knee function measures were not relevantly associated with bidirectional changes in body weight. SCF and IMF CSAs are highly responsive to bidirectional weight change, whereas muscle CSAs were only responsive to weight loss. These findings highlight that MRI represents a sensitive tool for monitoring changes in thigh adipose tissue composition that may be applied during specific diet and/or exercise interventions.

Muscle weakness is associated with non-contractile muscle tissue of the vastus medialis muscle in knee osteoarthritis.

BACKGROUND: Quadriceps weakness is assumed to be associated with compositional properties of the vastus medialis muscle in patients with knee osteoarthritis (OA). METHODS: The aim was to determine the association of non-contractile muscle tissue in the vastus medialis muscle, measured with routine MRI, with muscle extensor strength in patients with knee OA. Sagittal T1-weighted 3T MRI of 94 patients with knee OA, routinely acquired in clinical practice were used for analysis. Using the MRI's, the amount of non-contractile muscle tissue in the vastus medialis muscle was measured, expressed as a percentage of (non)-contractile tissue, dichotomized into a low and a high non-contractile percentage group. Muscle strength was assessed by isokinetic measurement of knee extensors and by conduction of the Get-Up and Go (GUG) test. In regression analyses, associations of percentage of non-contractile muscle tissue with muscle strength and GUG time were determined and controlled for sex, age, BMI and radiographic severity. RESULTS: A high percentage of non-contractile muscle tissue (> 11.2%) was associated with lower muscle strength (B = -0.25, P = 0.006) and with longer GUG time (B = 1.09, P = 0.021). These associations were specifically confounded by sex and BMI, because these two variables decreased the regression coefficient (B) with > 10%. CONCLUSIONS: A high percentage of non-contractile muscle tissue in the vastus medialis muscle measured by clinical T1-weighted 3T MRI is associated with muscle weakness. The association is confounded by sex and BMI. Non-contractile muscle tissue seems to be an important compositional property of the vastus medialis muscle underlying quadriceps weakness.

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.

Meniscus position and size in knees with versus without structural knee osteoarthritis progression: data from the osteoarthritis initiative.

OBJECTIVE: To explore whether and which quantitative 3D measures of medial and/or lateral meniscus position and size are associated with subsequent medial femorotibial structural progression of knee osteoarthritis and to determine the correlation between central slice and total meniscus measures. MATERIALS AND METHODS: Knees with radiographic osteoarthritis from Osteoarthritis Initiative participants with longitudinal medial MRI-based cartilage thickness and radiographic joint space width (JSW) loss over 12 months were selected. These 37 structural progressor knees (64.7 ± 8.0y, 30.2 ± 4.6 kg/m2, 35% men) were matched 1:1 to 37 non-progressor knees (64.6 ± 9.8y, 30.2 ± 4.4 kg/m2, 35% men) without cartilage thickness or JSW loss. Quantitative measures of meniscus position and size were computed from manual segmentations of coronal baseline MRIs. Cohen's D was used as measure of effect size. RESULTS: Maximum extrusion distance of the total medial meniscus and mean extrusion in the central 5 and in the central slice were greater for progressor than non-progressor knees (Cohen's D 0.58-0.66). No significant differences were observed for medial tibial coverage or mean extrusion (entire meniscus). Among medial meniscus morphology measures, only mean height differed between progressor vs non-progressor knees (Cohen's D 0.40). Among lateral meniscus measures, height and volume were greater in progressor vs. non-progressor knees (Cohen's D 0.46-0.83). Mean extrusion measures were highly correlated between the entire meniscus and the central (r = 0.88) or the central 5 (r = 0.93) slices. CONCLUSIONS: 3D maximum and central medial meniscus extrusion may serve as predictors for subsequent structural progression. Central meniscus extrusion measures could substitute 3D extrusion measurement across the entire meniscus.

Do Ahlbäck scores identify subgroups with different magnitudes of cartilage thickness loss in patients with moderate to severe radiographic osteoarthritis? One-year follow-up data from the Osteoarthritis Initiative.

OBJECTIVE: Kellgren-Lawrence grades (KLG) are frequently used for patient selection in clinical trials. The Ahlbäck radiographic grading system has been developed for moderate and severe knee OA. KLG 3 is comparable to Ahlbäck 1 and KLG 4 is subdivided into Ahlbäck 2-5. The objective of this study was to investigate if the Ahlbäck scoring system is able to subdivide patients with moderate to severe knee OA (KLG 3/4) into groups with different sensitivity to change in cartilage thickness. MATERIALS AND METHODS: This study was based on 108 Osteoarthritis Initiative (OAI) participants with KLG 3/4. Baseline KLG scores were available from the OAI database; Ahlbäck scores were performed using the same x-rays. Cartilage thickness change in the weight-bearing femorotibial cartilage was analysed from baseline and year 1 3D FLASH MRI for the entire femorotibial joint (FTJ), the medial (MFTC) and the lateral compartment (LFTC) and for the location-independent ordered values 1 and 16 (OV 1/OV 16) representing the subregions with largest loss (OV 1) and gain (OV 16) within each knee. RESULTS: Of the 108 patients, n = 30/78 had KLG 3/4. The corresponding Ahlbäck scores (1-5) were n = 30/33/36/9/10. Cartilage thickness changes between Ahlbäck groups showed no statistically significant difference for FTJ, MFTC, LFTC and OV 1, but change in OV 16 was significantly higher in Ahlbäck 4 knees (p = 0.03) compared to Ahlbäck 1-3 knees. CONCLUSION: Radiographic knee OA grading with Ahlbäck scores was not superior to KLG for prediction of cartilage thickness loss over 1 year, in patients with moderate and severe knee OA supporting the continuous use of the easier and more widely used KLG.

Accuracy and longitudinal reproducibility of quantitative femorotibial cartilage measures derived from automated U-Net-based segmentation of two different MRI contrasts: data from the osteoarthritis initiative healthy reference cohort.

OBJECTIVE: To evaluate the agreement, accuracy, and longitudinal reproducibility of quantitative cartilage morphometry from 2D U-Net-based automated segmentations for 3T coronal fast low angle shot (corFLASH) and sagittal double echo at steady-state (sagDESS) MRI. METHODS: 2D U-Nets were trained using manual, quality-controlled femorotibial cartilage segmentations available for 92 Osteoarthritis Initiative healthy reference cohort participants from both corFLASH and sagDESS (n = 50/21/21 training/validation/test-set). Cartilage morphometry was computed from automated and manual segmentations for knees from the test-set. Agreement and accuracy were evaluated from baseline visits (dice similarity coefficient: DSC, correlation analysis, systematic offset). The longitudinal reproducibility was assessed from year-1 and -2 follow-up visits (root-mean-squared coefficient of variation, RMSCV%). RESULTS: Automated segmentations showed high agreement (DSC 0.89-0.92) and high correlations (r ≥ 0.92) with manual ground truth for both corFLASH and sagDESS and only small systematic offsets (≤ 10.1%). The automated measurements showed a similar test-retest reproducibility over 1 year (RMSCV% 1.0-4.5%) as manual measurements (RMSCV% 0.5-2.5%). DISCUSSION: The 2D U-Net-based automated segmentation method yielded high agreement compared with manual segmentation and also demonstrated high accuracy and longitudinal test-retest reproducibility for morphometric analysis of articular cartilage derived from it, using both corFLASH and sagDESS.

Intra-articular sprifermin reduces cartilage loss in addition to increasing cartilage gain independent of location in the femorotibial joint: post-hoc analysis of a randomised, placebo-controlled phase II clinical trial.

OBJECTIVES: In the phase II FGF-18 Osteoarthritis Randomized Trial with Administration of Repeated Doses (FORWARD) study, sprifermin demonstrated cartilage modification in the total femorotibial joint and in both femorotibial compartments by MRI in patients with knee osteoarthritis. Here, we evaluate whether sprifermin reduces cartilage loss and increases cartilage thickness, independent of location. METHODS: Patients were randomised 1:1:1:1:1 to three once-weekly intra-articular injections of 30 µg sprifermin every 6 months (q6mo); 30 µg sprifermin every 12 months (q12mo); 100 µg sprifermin q6mo; 100 µg sprifermin q12mo; or placebo. Post-hoc analysis using thinning/thickening scores and ordered values evaluated femorotibial cartilage thickness change from baseline to 24 months independent of location. Changes were indirectly compared with those of Osteoarthritis Initiative healthy subjects. RESULTS: Thinning scores were significantly lower for sprifermin 100 µg q6mo versus placebo (mean (95% CI) difference: 334 µm (114 to 554)), with a cartilage thinning score similar to healthy subjects. Thickening scores were significantly greater for sprifermin 100 µg q6mo, 100 µg q12mo and 30 µg q6mo versus placebo (mean (95% CI) difference: 425 µm (267 to 584); 450 µm (305 to 594) and 139 µm (19 to 259), respectively) and more than doubled versus healthy subjects. CONCLUSIONS: Sprifermin increases cartilage thickness, and substantially reduces cartilage loss, expanding FORWARD primary results. TRIAL REGISTRATION NUMBER: NCT01919164.

Clinical evaluation of fully automated thigh muscle and adipose tissue segmentation using a U-Net deep learning architecture in context of osteoarthritic knee pain.

OBJECTIVE: Segmentation of thigh muscle and adipose tissue is important for the understanding of musculoskeletal diseases such as osteoarthritis. Therefore, the purpose of this work is (a) to evaluate whether a fully automated approach provides accurate segmentation of muscles and adipose tissue cross-sectional areas (CSA) compared with manual segmentation and (b) to evaluate the validity of this method based on a previous clinical study. MATERIALS AND METHODS: The segmentation method is based on U-Net architecture trained on 250 manually segmented thighs from the Osteoarthritis Initiative (OAI). The clinical evaluation is performed on a hold-out test set bilateral thighs of 48 subjects with unilateral knee pain. RESULTS: The segmentation time of the method is < 1 s and demonstrated high agreement with the manual method (dice similarity coeffcient: 0.96 ± 0.01). In the clinical study, the automated method shows that similar to manual segmentation (- 5.7 ± 7.9%, p < 0.001, effect size: 0.69), painful knees display significantly lower quadriceps CSAs than contralateral painless knees (- 5.6 ± 7.6%, p < 0.001, effect size: 0.73). DISCUSSION: Automated segmentation of thigh muscle and adipose tissues has high agreement with manual segmentations and can replicate the effect size seen in a clinical study on osteoarthritic pain.

Association of adiposity measures in childhood and adulthood with knee cartilage thickness, volume and bone area in young adults.

OBJECTIVE: To describe the associations of childhood and adulthood adiposity measures with knee cartilage thickness, volume and bone area in young adults. METHODS: Childhood and adulthood adiposity measures (weight, height, waist circumference and hip circumference) of 186 participants were collected in 1985 (aged 7-15 years) and during 2004-2006 (aged 26-36 years). Knee magnetic resonance imaging was conducted during 2008-2010 (aged 31-41 years) and cartilage thickness, volume and bone area were measured using a quantitative approach (Chondrometrics, Germany). Linear regressions were used to examine the above associations. RESULTS: The prevalence of overweight was 7.6% in childhood and 42.1% in adulthood. Childhood weight (ß = - 5.57 mm2/kg) and body mass index (BMI) (ß = - 11.55 mm2/kg/m2) were negatively associated with adult patellar bone area, whereas adult weight was positively associated with bone area in medial femorotibial compartment (MFTC) (ß = 3.37 mm2/kg) and lateral femorotibial compartment (LFTC) (ß = 2.08 mm2/kg). Adult waist-hip ratio (WHR) was negatively associated with cartilage thickness (MFTC: ß = - 0.011; LFTC: ß = - 0.012 mm/0.01 unit), volume (Patella: ß = - 20.97; LFTC: ß = - 21.71 mm3/0.01 unit) and bone area (Patella: ß = - 4.39 mm2/0.01 unit). The change in WHR z-scores from childhood to adulthood was negatively associated with cartilage thickness (MFTC: ß = - 0.056 mm), volume (patella: - 89.95; LFTC: - 93.98 mm3), and bone area (patella: - 20.74 mm2). All p-values < 0.05. CONCLUSIONS: Childhood weight and BMI were negatively but adult weight was positively associated with adult bone area. Adult WHR and the change in WHR from childhood to adulthood were negatively associated with cartilage thickness, volume, and bone area. These suggest early-life adiposity measures may affect knee structures in young adults.