Test-retest precision and longitudinal cartilage thickness loss in the IMI-APPROACH cohort

Can gait patterns be explained by joint structure in people with and without radiographic knee osteoarthritis? Data from the IMI-APPROACH cohort

OBJECTIVE

To determine the association between joint structure and gait in patients with knee osteoarthritis (OA).

METHODS

IMI-APPROACH recruited 297 clinical knee OA patients. Gait data was collected (GaitSmart®) and OA-related joint measures determined from knee radiographs (KIDA) and MRIs (qMRI/MOAKS). Patients were divided into those with/without radiographic OA (ROA). Principal component analyses (PCA) were performed on gait parameters; linear regression models were used to evaluate whether image-based structural and demographic parameters were associated with gait principal components.

RESULTS

Two hundred seventy-one patients (age median 68.0, BMI 27.0, 77% female) could be analyzed; 149 (55%) had ROA. PCA identified two components: upper leg (primarily walking speed, stride duration, hip range of motion [ROM], thigh ROM) and lower leg (calf ROM, knee ROM in swing and stance phases). Increased age, BMI, and radiographic subchondral bone density (sclerosis), decreased radiographic varus angle deviation, and female sex were statistically significantly associated with worse lower leg gait (i.e. reduced ROM) in patients without ROA (R2 = 0.24); in ROA patients, increased BMI, radiographic osteophytes, MRI meniscal extrusion and female sex showed significantly worse lower leg gait (R2 = 0.18). Higher BMI was significantly associated with reduced upper leg function for non-ROA patients (R2 = 0.05); ROA patients with male sex, higher BMI and less MRI synovitis showed significantly worse upper leg gait (R2 = 0.12).

CONCLUSION

Structural OA pathology was significantly associated with gait in patients with clinical knee OA, though BMI may be more important. While associations were not strong, these results provide a significant association between OA symptoms (gait) and joint structure.

Fluctuation of Bone Marrow Lesions and Inflammatory MRI Markers over 2 Years and Concurrent Associations with Quantitative Cartilage Loss

OBJECTIVE

To assess whether change of semiquantitatively magnetic resonance imaging (MRI)-defined bone marrow lesions (BMLs) and inflammatory markers is associated with change in quantitatively-assessed cartilage loss in the femorotibial joint (FTJ) in knees with radiographic osteoarthritis (OA) over 24 months.

DESIGN

Participants were included from the IMI-APPROACH and the Osteoarthritis Initiative FNIH studies. Semiquantitative MRI assessment was performed for BMLs, Hoffa- and effusion-synovitis. Quantitative cartilage thickness measurements were performed manually. Definitions of change included number of subregions with BMLs, change in sum and change in maximum increase in size. Change in Hoffa-synovitis and effusion-synovitis was categorized in addition. Between-group comparisons regarding cartilage loss in the FTJ, medial and lateral compartments were performed using analysis of variance (ANOVA).

RESULTS

A total of 629 participants were included. Knees without any BMLs at baseline (BL) and follow-up (FU) had significantly less cartilage loss compared to the other subgroups. Change in both directions in the sum score of BMLs was associated with increased rates of cartilage loss. Maximum increase in size of BMLs was associated with increased rates of cartilage loss (FTJ increase by 2 grades -0.183 mm, 95% CI [-0.335, -0.031], by 3 grades -0.306 mm, [-0.511, -0.101]). Worsening of Hoffa-synovitis was associated with increased rates of cartilage loss.

CONCLUSION

Knees without BMLs at BL and FU showed lowest rates of cartilage loss. Knees with an increase in BML size showed increased rates of concurrent cartilage loss. Approaches with the aim to inhibit BML development, avoidance of increase in size and avoidance of Hoffa-synovitis worsening may have beneficial effects on cartilage loss.

The design of a sample rapid magnetic resonance imaging (MRI) acquisition protocol supporting assessment of multiple articular tissues and pathologies in knee osteoarthritis

Objective

This expert opinion paper proposes a design for a state-of-the-art magnetic resonance image (MRI) acquisition protocol for knee osteoarthritis clinical trials in early and advanced disease. Semi-quantitative and quantitative imaging endpoints are supported, partly amendable to automated analysis. Several (peri-) articular tissues and pathologies are covered, including synovitis.

Method

A PubMed literature search was conducted, with focus on the past 5 years. Further, osteoarthritis imaging experts provided input. Specific MRI sequences, orientations, spatial resolutions and parameter settings were identified to align with study goals. We strived for implementation on standard clinical scanner hardware, with a net acquisition time ≤30 ​min.

Results

Short- and long-term longitudinal MRIs should be obtained at ≥1.5T, if possible without hardware changes during the study. We suggest a series of gradient- and spin-echo-sequences, supporting MOAKS, quantitative analysis of cartilage morphology and T2, and non-contrast-enhanced depiction of synovitis. These sequences should be properly aligned and positioned using localizer images. One of the sequences may be repeated in each participant (re-test), optimally at baseline and follow-up, to estimate within-study precision. All images should be checked for quality and protocol-adherence as soon as possible after acquisition. Alternative approaches are suggested that expand on the structural endpoints presented.

Conclusions

We aim to bridge the gap between technical MRI acquisition guides and the wealth of imaging literature, proposing a balance between image acquisition efficiency (time), safety, and technical/methodological diversity. This approach may entertain scientific innovation on tissue structure and composition assessment in clinical trials on disease modification of knee osteoarthritis.

Variations in knee cartilage thickness: Fully automatic three-dimensional analysis of MRIs from five manufacturers

BACKGROUND

Measurements of knee cartilage thickness derived from MR images are attractive biomarkers for osteoarthritis research. Although some cross-sectional multivendor studies exist, none have employed fully automatic three-dimensional MRI analysis. Our objective was to evaluate the variations in knee cartilage thickness measurements obtained using automated methods and MRI instruments from five different vendors.

METHODS

The subjects were 10 healthy volunteers aged 22-60 years. MRI models with 3 Tesla strength from five different companies were used. Cartilage thickness was quantified fully automatically for seven regions. We hypothesized that "the MRI model influences cartilage thickness measurements." Inter-measurement error, defined as the absolute difference between the targeted and median thicknesses determined by the five MRI models, was analyzed using histograms. The factors generating the largest inter-measurement error were also examined.

RESULTS

No exceptional trends attributable to a specific instrument model were observed, and the p-value from the Kruskal-Wallis test exceeded 0.05 in all seven regions. Therefore, the study hypothesis was rejected. Of the 350 measurements, the inter-measurement error was ≤0.05 mm in 53 %, ≤0.10 mm in 75 %, and ≤0.20 mm in 95 %. Analysis of the medial tibial cartilage, which had the largest inter-measurement error, revealed mis-extraction of synovial fluid as cartilage.

CONCLUSIONS

The choice of MRI model did not influence cartilage thickness measurements. Overall, 95 % of the inter-measurement errors were within 0.20 mm. The greatest error resulted from mis-extracting synovial fluid as cartilage.

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.

Osteoarthritis year in review 2023: Imaging

PURPOSE

This narrative review summarizes the original research in the field of in vivo osteoarthritis (OA) imaging between 1 January 2022 and 1 April 2023.

METHODS

A PubMed search was conducted using the following several terms pertaining to OA imaging, including but not limited to "Osteoarthritis / OA", "Magnetic resonance imaging / MRI", "X-ray" "Computed tomography / CT", "artificial intelligence /AI", "deep learning", "machine learning". This review is organized by topics including the anatomical structure of interest and modality, AI, challenges of OA imaging in the context of clinical trials, and imaging biomarkers in clinical trials and interventional studies. Ex vivo and animal studies were excluded from this review.

RESULTS

Two hundred and forty-nine publications were relevant to in vivo human OA imaging. Among the articles included, the knee joint (61%) and MRI (42%) were the predominant anatomical area and imaging modalities studied. Marked heterogeneity of structural tissue damage in OA knees was reported, a finding of potential relevance to clinical trial inclusion. The use of AI continues to rise rapidly to be applied in various aspect of OA imaging research but a lack of generalizability beyond highly standardized datasets limit interpretation and wide-spread application. No pharmacologic clinical trials using imaging data as outcome measures have been published in the period of interest.

CONCLUSIONS

Recent advances in OA imaging continue to heavily weigh on the use of AI. MRI remains the most important modality with a growing role in outcome prediction and classification.

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.