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

Cartilage compositional MRI-a narrative review of technical development and clinical applications over the past three decades

Articular cartilage damage and degeneration are among hallmark manifestations of joint injuries and arthritis, classically osteoarthritis. Cartilage compositional MRI (Cart-C MRI), a quantitative technique, which aims to detect early-stage cartilage matrix changes that precede macroscopic alterations, began development in the 1990s. However, despite the significant advancements over the past three decades, Cart-C MRI remains predominantly a research tool, hindered by various technical and clinical hurdles. This paper will review the technical evolution of Cart-C MRI, delve into its clinical applications, and conclude by identifying the existing gaps and challenges that need to be addressed to enable even broader clinical application of Cart-C MRI.

What is New in Osteoarthritis Imaging?

Osteoarthritis (OA) is the leading joint disorder globally, affecting a significant proportion of the population. Recent studies have changed our understanding of OA, viewing it as a complex pathology of the whole joint with a multifaceted etiology, encompassing genetic, biological, and biomechanical elements. This review highlights the role of imaging in diagnosing and monitoring OA. Today's role of radiography is discussed, while also elaborating on the advances in computed tomography and magnetic resonance imaging, discussing semiquantitative methods, quantitative morphologic and compositional techniques, and giving an outlook on the potential role of artificial intelligence in OA research.

The Effect of Probiotics on the Management of Pain and Inflammation in Osteoarthritis: A Systematic Review and Meta-Analysis of Clinical Studies

Osteoarthritis (OA) is one of the most common musculoskeletal disorders. Recently, research has focused on the role of intestinal microbiome dysbiosis in OA. The aim of this study was to systematically review randomized intervention clinical studies investigating the effect of probiotics on the management of OA-related pain and inflammation. Pre-clinical studies and non-randomized trials were excluded. A literature search was conducted using MEDLINE, EMBASE, and Web of Science. Study quality was assessed with the Cochrane risk of bias (RoB2) tool and the Risk of Bias in N-of-1 Trials (RoBiNT) scale. RevMan was used for the meta-analysis. Outcome measures assessed self-reported pain, stiffness and impediment, and serum hs-CRP. Three studies, with 501 participants, were considered eligible for qualitative synthesis and meta-analysis. A significant reduction in symptoms across all outcomes measured, except stiffness, was evident with Lactobacillus casei Shirota. However, all other probiotics reviewed did not seem to have any effect on the measured outcomes. Pre-clinical evidence, along with the RCTs reviewed, suggests that probiotics of the Lactobacillus strains might be of use for managing pain and inflammation in OA. Considering the small number of studies included in the present review and the possible risk of bias, we conclude that further studies on the role of probiotics in humans with OA are warranted.

Clinical validation of fully automated laminar knee cartilage transverse relaxation time (T2) analysis in anterior cruciate ligament (ACL)-injured knees- on behalf of the osteoarthritis (OA)-Bio consortium

Background

Magnetic resonance imaging (MRI) cartilage transverse relaxation time (T2) reflects cartilage composition, mechanical properties, and early osteoarthritis (OA). T2 analysis requires cartilage segmentation. In this study, we clinically validate fully automated T2 analysis at 1.5 Tesla (T) in anterior cruciate ligament (ACL)-injured and healthy knees.

Methods

We studied 71 participants: 20 ACL-injured patients with, and 22 without dynamic knee instability, 13 with surgical reconstruction, and 16 healthy controls. Sagittal multi-echo-spin-echo (MESE) MRIs were acquired at baseline and 1-year follow-up. Femorotibial cartilage was segmented manually; a convolutional neural network (CNN) algorithm was trained on MRI data from the same scanner.

Results

Dice similarity coefficients (DSCs) of automated versus manual segmentation in the 71 participants were 0.83 (femora) and 0.89 (tibiae). Deep femorotibial T2 was similar between automated (45.7±2.6 ms) and manual (45.7±2.7 ms) segmentation (P=0.828), whereas superficial layer T2 was slightly overestimated by automated analysis (53.2±2.2 vs. 52.1±2.1 ms for manual; P<0.001). T2 correlations were r=0.91-0.99 for deep and r=0.86-0.97 for superficial layers across regions. The only statistically significant T2 increase over 1 year was observed in the deep layer of the lateral femur [standardized response mean (SRM) =0.58 for automated vs. 0.52 for manual analysis; P<0.001]. There was no relevant difference in baseline/longitudinal T2 values/changes between the ACL-injured groups and healthy participants, with either segmentation method.

Conclusions

This clinical validation study suggests that automated cartilage T2 analysis from MESE at 1.5T is technically feasible and accurate. More efficient 3D sequences and longer observation intervals may be required to detect the impact of ACL injury induced joint instability on cartilage composition (T2).

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.

Morphological assessment of cartilage and osteoarthritis in clinical practice and research: Intermediate-weighted fat-suppressed sequences and beyond

Magnetic resonance imaging (MRI) is widely regarded as the primary modality for the morphological assessment of cartilage and all other joint tissues involved in osteoarthritis. 2D fast spin echo fat-suppressed intermediate-weighted (FSE FS IW) sequences with a TE between 30 and 40ms have stood the test of time and are considered the cornerstone of MRI protocols for clinical practice and trials. These sequences offer a good balance between sensitivity and specificity and provide appropriate contrast and signal within the cartilage as well as between cartilage, articular fluid, and subchondral bone. Additionally, FS IW sequences enable the evaluation of menisci, ligaments, synovitis/effusion, and bone marrow edema-like signal changes. This review article provides a rationale for the use of FSE FS IW sequences in the morphological assessment of cartilage and osteoarthritis, along with a brief overview of other clinically available sequences for this indication. Additionally, the article highlights ongoing research efforts aimed at improving FSE FS IW sequences through 3D acquisitions with enhanced resolution, shortened examination times, and exploring the potential benefits of different magnetic field strengths. While most of the literature on cartilage imaging focuses on the knee, the concepts presented here are applicable to all joints. KEY POINTS: 1. MRI is currently considered the modality of reference for a "whole-joint" morphological assessment of osteoarthritis. 2. Fat-suppressed intermediate-weighted sequences remain the keystone of MRI protocols for the assessment of cartilage morphology, as well as other structures involved in osteoarthritis. 3. Trends for further development in the field of cartilage and joint imaging include 3D FSE imaging, faster acquisition including AI-based acceleration, and synthetic imaging providing multi-contrast sequences.

Relations between Structure/Composition and Mechanics in Osteoarthritic Regenerated Articular Tissue: A Machine Learning Approach

In the context of a large animal model of early osteoarthritis (OA) treated by orthobiologics, the purpose of this study was to reveal relations between articular tissues structure/composition and cartilage viscoelasticity. Twenty-four sheep, with induced knee OA, were treated by mesenchymal stem cells in various preparations-adipose-derived mesenchymal stem cells (ADSCs), stromal vascular fraction (SVF), and amniotic endothelial cells (AECs)-and euthanized at 3 or 6 months to evaluate the (i) biochemistry of synovial fluid; (ii) histology, immunohistochemistry, and histomorphometry of articular cartilage; and (iii) viscoelasticity of articular cartilage. After performing an initial analysis to evaluate the correlation and multicollinearity between the investigated variables, this study used machine learning (ML) models-Variable Selection Using Random Forests (VSURF) and Extreme Gradient Boosting (XGB)-to classify variables according to their importance and employ them for interpretation and prediction. The experimental setup revealed a potential relation between cartilage elastic modulus and cartilage thickness (CT), synovial fluid interleukin 6 (IL6), and prostaglandin E2 (PGE2), and between cartilage relaxation time and CT and PGE2. SVF treatment was the only limit on the deleterious OA effect on cartilage viscoelastic properties. This work provides indications to future studies aiming to highlight these and other relationships and focusing on advanced regeneration targets.

Updates on Compositional MRI Mapping of the Cartilage: Emerging Techniques and Applications

Osteoarthritis (OA) is a widely occurring degenerative joint disease that is severely debilitating and causes significant socioeconomic burdens to society. Magnetic resonance imaging (MRI) is the preferred imaging modality for the morphological evaluation of cartilage due to its excellent soft tissue contrast and high spatial resolution. However, its utilization typically involves subjective qualitative assessment of cartilage. Compositional MRI, which refers to the quantitative characterization of cartilage using a variety of MRI methods, can provide important information regarding underlying compositional and ultrastructural changes that occur during early OA. Cartilage compositional MRI could serve as early imaging biomarkers for the objective evaluation of cartilage and help drive diagnostics, disease characterization, and response to novel therapies. This review will summarize current and ongoing state-of-the-art cartilage compositional MRI techniques and highlight emerging methods for cartilage compositional MRI including MR fingerprinting, compressed sensing, multiexponential relaxometry, improved and robust radio-frequency pulse sequences, and deep learning-based acquisition, reconstruction, and segmentation. The review will also briefly discuss the current challenges and future directions for adopting these emerging cartilage compositional MRI techniques for use in clinical practice and translational OA research studies. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.