Quantitative MRI for Evaluation of Musculoskeletal Disease: Cartilage and Muscle Composition, Joint Inflammation, and Biomechanics in Osteoarthritis

Gaining Insight into Updated MR Imaging for Quantitative Assessment of Cartilage Injury in Knee Osteoarthritis

PURPOSE OF THE REVIEW

Knee Osteoarthritis (KOA) entails progressive cartilage degradation, reviewed via MRI for morphology, biochemical composition, and microtissue alterations, discussing clinical advantages, limitations, and research applicability.

RECENT FINDINGS

Compositional MRI, like T2/T2* mapping, T1rho mapping, gagCEST, dGEMRIC, sodium imaging, diffusion-weighted imaging, and diffusion-tensor imaging, provide insights into cartilage injury in KOA. These methods quantitatively measure collagen, glycosaminoglycans, and water content, revealing important information about biochemical compositional and microstructural alterations. Innovative techniques like hybrid multi-dimensional MRI and diffusion-relaxation correlation spectrum imaging show potential in depicting initial cartilage changes at a sub-voxel level. Integration of automated image analysis tools addressed limitations in manual cartilage segmentation, ensuring robust and reproducible assessments of KOA cartilage. Compositional MRI techniques reveal microstructural changes in cartilage. Multi-dimensional MR imaging assesses biochemical alterations in KOA-afflicted cartilage, aiding early degeneration identification. Integrating artificial intelligence enhances cartilage analysis, optimal diagnostic accuracy for early KOA detection and monitoring.

Association of Graft Maturity on MRI With Return to Sports at 9 Months After Primary Single-Bundle ACL Reconstruction With Autologous Hamstring Graft

Background

The relationship between graft maturity on magnetic resonance imaging (MRI) and return to sports (RTS) after anterior cruciate ligament (ACL) reconstruction is unclear.

Purpose

To compare signal-to-noise quotient (SNQ) values and ACL graft T2* (gradient echo) values between patients who did RTS and those who did not RTS (NRTS) after ACL reconstruction and to evaluate the predictive value of T2* mapping for RTS after ACL reconstruction.

Study Design

Case-control study; Level of evidence, 3.

Methods

At a minimum of 9 months after arthroscopic single-bundle ACL reconstruction with autologous hamstring tendon graft, 82 patients underwent RTS assessment as well as MRI evaluation. The patients were classified into RTS (n = 53) and NRTS (n = 29) groups based on the results of the assessment. The SNQ values in the proximal, middle, and distal regions of the graft and the T2* values of the graft were measured on MRI. The correlation between T2* values and RTS was assessed using Spearman correlation analysis. Receiver operating characteristic curves were constructed to compare the diagnostic performance, and the optimal T2* cutoff value for detecting RTS was determined based on the maximum Youden index.

Results

At 9 months after ACL reconstruction, the proximal, middle, and mean SNQ values in the RTS group were significantly lower than those in the NRTS group (proximal: 17.15 ± 4.85 vs 19.55 ± 5.05, P = .038; middle: 13.45 ± 5.15 vs. 17.75 ± 5.75, P = .001; mean: 12.37 ± 2.74 vs 15.07 ± 3.32, P < .001). The T2* values were lower in the RTS group (14.92 ± 2.28 vs 17.69 ± 2.48; P < .001) and were correlated with RTS (r = -0.41; P = .02). The area under the curve of T2* was 0.79 (95% CI, 0.75-0.83), and the optimal cutoff value for T2* was 16.65, with a sensitivity and specificity for predicting failure to RTS of 67.9% and 88.2%, respectively.

Conclusion

Study findings indicated that the SNQs (mean, proximal, and middle) and the T2* values of the graft in the RTS group were significantly lower than those in NRTS group. A T2* value of 16.65 was calculated to predict patients who failed RTS tests with a sensitivity of 67.9% and specificity of 88.2%.

MRI-derived Articular Cartilage Strains Predict Patient-Reported Outcomes Six Months Post Anterior Cruciate Ligament Reconstruction

Key terms

Multicontrast and Multiparametric, Magnetic Resonance Imaging, Osteoarthritis, Functional Biomechanical Imaging, Knee Joint Degeneration What is known about the subject: dualMRI has been used to quantify strains in a healthy human population in vivo and in cartilage explant models. Previously, OA severity, as determined by histology, has been positively correlated to increased shear and transverse strains in cartilage explants. What this study adds to existing knowledge: This is the first in vivo use of dualMRI in a participant demographic post-ACL reconstruction and at risk for developing osteoarthritis. This study shows that dualMRI-derived strains are more significantly correlated with patient-reported outcomes than any MRI relaxometry metric.

Background

Anterior cruciate ligament (ACL) injuries lead to an increased risk of osteoarthritis, characterized by altered cartilage tissue structure and function. Displacements under applied loading by magnetic resonance imaging (dualMRI) is a novel MRI technique that can be used to quantify mechanical strain in cartilage while undergoing a physiological load.

Purpose

To determine if strains derived by dualMRI and relaxometry measures correlate with patient-reported outcomes at six months post unilateral ACL reconstruction.

Study Design

Cohort study.

Methods

Quantitative MRI (T2, T2*, T1ρ) measurements and transverse, axial, and shear strains were quantified in the medial articular tibiofemoral cartilage of 35 participants at six-months post unilateral ACL reconstruction. The relationships between patient-reported outcomes (WOMAC, KOOS, MARS) and all qMRI relaxation times were quantified using general linear mixed-effects models. A combined best-fit multicontrast MRI model was then developed using backwards regression to determine the patient features and MRI metrics that are most predictive of patient-reported outcome scores.

Results

Higher femoral strains were significantly correlated with worse patient-reported functional outcomes. Femoral shear and transverse strains were positively correlated with six-month KOOS and WOMAC scores, after controlling for covariates. No relaxometry measures were correlated with patient-reported outcome scores. We identified the best-fit model for predicting WOMAC score using multiple MRI measures and patient-specific information, including sex, age, graft type, femoral transverse strain, femoral axial strain, and femoral shear strain. The best-fit model significantly predicted WOMAC score (p<0.001) better than any one individual MRI metric alone. When we regressed the model-predicted WOMAC scores against the patient-reported WOMAC scores, we found that our model achieved a goodness of fit exceeding 0.52.

Conclusions

This work presents the first use of dualMRI in vivo in a cohort of participants at risk for developing osteoarthritis. Our results indicate that both shear and transverse strains are highly correlated with patient-reported outcome severity could serve as novel imaging biomarkers to predict the development of osteoarthritis.

Evaluation of the consistency of the MRI- based AI segmentation cartilage model using the natural tibial plateau cartilage

OBJECTIVE

The study aims to evaluate the accuracy of an MRI-based artificial intelligence (AI) segmentation cartilage model by comparing it to the natural tibial plateau cartilage.

METHODS

This study included 33 patients (41 knees) with severe knee osteoarthritis scheduled to undergo total knee arthroplasty (TKA). All patients had a thin-section MRI before TKA. Our study is mainly divided into two parts: (i) In order to evaluate the MRI-based AI segmentation cartilage model's 2D accuracy, the natural tibial plateau was used as gold standard. The MRI-based AI segmentation cartilage model and the natural tibial plateau were represented in binary visualization (black and white) simulated photographed images by the application of Simulation Photography Technology. Both simulated photographed images were compared to evaluate the 2D Dice similarity coefficients (DSC). (ii) In order to evaluate the MRI-based AI segmentation cartilage model's 3D accuracy. Hand-crafted cartilage model based on knee CT was established. We used these hand-crafted CT-based knee cartilage model as gold standard to evaluate 2D and 3D consistency of between the MRI-based AI segmentation cartilage model and hand-crafted CT-based cartilage model. 3D registration technology was used for both models. Correlations between the MRI-based AI knee cartilage model and CT-based knee cartilage model were also assessed with the Pearson correlation coefficient.

RESULTS

The AI segmentation cartilage model produced reasonably high two-dimensional DSC. The average 2D DSC between MRI-based AI cartilage model and the tibial plateau cartilage is 0.83. The average 2D DSC between the AI segmentation cartilage model and the CT-based cartilage model is 0.82. As for 3D consistency, the average 3D DSC between MRI-based AI cartilage model and CT-based cartilage model is 0.52. However, the quantification of cartilage segmentation with the AI and CT-based models showed excellent correlation (r = 0.725; P values < 0.05).

CONCLUSION

Our study demonstrated that our MRI-based AI cartilage model can reliably extract morphologic features such as cartilage shape and defect location of the tibial plateau cartilage. This approach could potentially benefit clinical practices such as diagnosing osteoarthritis. However, in terms of cartilage thickness and three-dimensional accuracy, MRI-based AI cartilage model underestimate the actual cartilage volume. The previous AI verification methods may not be completely accurate and should be verified with natural cartilage images. Combining multiple verification methods will improve the accuracy of the AI model.

Morphological and Quantitative Parametric MRI Follow-up of Cartilage Changes Before and After Intra-articular Injection Therapy in Patients With Mild to Moderate Knee Osteoarthritis: A Randomized, Placebo-Controlled Trial

BACKGROUND

Intra-articular injections are routinely used for conservative treatment of knee osteoarthritis (OA). The detailed comparative therapeutic effects of these injections on cartilage tissue are still unclear.

OBJECTIVE

The aim of this study was to detect and compare knee cartilage changes after intra-articular injection of glucocorticoid, hyaluronic acid, or platelet-rich plasma (PRP) to placebo using quantitative (T2 and T2* mapping) and morphological magnetic resonance imaging parameters in patients with mild or moderate osteoarthritis.

MATERIALS AND METHODS

In a double-blinded, placebo-controlled, single-center trial, knees with mild or moderate osteoarthritis (Kellgren-Lawrence grade 1-3) were randomly assigned to an intra-articular injection with 1 of these substances: glucocorticoid, hyaluronic acid, PRP, or placebo. Cartilage degeneration on baseline and follow-up magnetic resonance imaging scans (after 3 and 12 months) was assessed by 2 readers using quantitative T2 and T2* times (milliseconds) and morphological parameters (modified Outerbridge grading, subchondral bone marrow edema, subchondral cysts, osteophytes).

RESULTS

One hundred twenty knees (30 knees per treatment group) were analyzed with a median patient age of 60 years (interquartile range, 54.0-68.0 years). Interreader reliability was good for T2 (ICC, 0.76; IQR, 0.68-0.83) and T2* (ICC, 0.83; IQR, 0.76-0.88) measurements. Morphological parameters showed no significant changes between all groups after 3 and 12 months. T2 mapping after 12 months showed the following significant ( P = 0.001-0.03) changes between groups in 6 of 14 compartments: values after PRP injection decreased compared with glucocorticoid in 4 compartments (complete medial femoral condyle and central part of lateral condyle) and compared with placebo in 2 compartments (anterior and central part of medial tibial plateau); values after glucocorticoid injection decreased compared with placebo in 1 compartment (central part of medial tibial plateau). No significant changes were seen for T2 and T2* times after 3 months and T2* times after 12 months. No correlation was found between T2/T2* times and Kellgren-Lawrence grade, age, body mass index, or pain (Spearman ρ, -0.23 to 0.18).

CONCLUSIONS

Platelet-rich plasma injection has a positive long-term effect on cartilage quality in the medial femoral compartment compared to glucocorticoid, resulting in significantly improved T2 values after 12 months. For morphological cartilage parameters, injections with glucocorticoid, PRP, or hyaluronic acid showed no better effect in the short or long term compared with placebo.

Biomarkers of Cartilage Composition

Magnetic resonance imaging (MRI) has significantly advanced the understanding of osteoarthritis (OA) because it enables visualization of noncalcified tissues. Cartilage is avascular and nurtured by diffusion, so it has a very low turnover and limited capabilities of repair. Consequently, prevention of structural and detection of premorphological damage is key in maintaining cartilage health. The integrity of cartilage composition and ultrastructure determines its mechanical properties but is not accessible to morphological imaging. Therefore, various techniques of compositional MRI with and without use of intravenous contrast medium have been developed. Spin-spin relaxation time (T2) and spin-lattice relaxation time constant in rotating frame (T1rho) mapping, the most studied cartilage biomarkers, were included in the recent standardization effort by the Quantitative Imaging Biomarkers Alliance (QIBA) that aims to make compositional MRI of cartilage clinically feasible and comparable. Additional techniques that are less frequently used include ultrashort echo time with T2*, delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), glycosaminoglycan concentration by chemical exchange-dependent saturation transfer (gagCEST), sodium imaging, and diffusion-weighted MRI.

Longitudinal changes in magnetic resonance imaging biomarkers of the gluteal muscle groups and functional ability in Duchenne muscular dystrophy: a 12-month cohort study

BACKGROUND

Quantitative magnetic resonance imaging (MRI) is considered an objective biomarker of Duchenne muscular dystrophy (DMD), but the longitudinal progression of MRI biomarkers in gluteal muscle groups and their predictive value for future motor function have not been described.

OBJECTIVE

To explore MRI biomarkers of the gluteal muscle groups as predictors of motor function decline in DMD by characterizing the progression over 12 months.

MATERIALS AND METHODS

A total of 112 participants with DMD were enrolled and underwent MRI examination of the gluteal muscles to determine fat fraction and longitudinal relaxation time (T1). Investigations were based on gluteal muscle groups including flexors, extensors, adductors, and abductors. The North Star Ambulatory Assessment and timed functional tests were performed. All participants returned for follow-up at an average of 12 months and were divided into two subgroups (functional stability/decline groups) based on changes in timed functional tests. Univariable and multivariable logistic regression methods were used to explore the risk factors associated with future motor function decline.

RESULTS

For the functional decline group, all T1 values decreased, while fat fraction values increased significantly over 12 months (P<0.05). For the functional stability group, only the fat fraction of the flexors and abductors increased significantly over 12 months (P<0.05). The baseline T1 value was positively correlated with North Star Ambulatory Assessment and negatively correlated with timed functional tests at the 12-month follow-up (P<0.001), while the baseline fat fraction value was negatively correlated with North Star Ambulatory Assessment and positively correlated with timed functional tests at the 12-month follow-up (P<0.001). Multivariate regression showed that increased fat fraction of the abductors was associated with future motor function decline (model 1: odds ratio [OR]=1.104, 95% confidence interval [CI]: 1.026~1.187, P=0.008; model 2: OR=1.085, 95% CI: 1.013~1.161, P=0.019), with an area under the curve of 0.874.

CONCLUSION

Fat fraction of the abductors is a powerful predictor of future motor functional decline in DMD patients at 12 months, underscoring the importance of focusing early on this parameter in patients with DMD.

Scientific Advances and Technical Innovations in Musculoskeletal Radiology

ABSTRACT

Decades of technical innovations have propelled musculoskeletal radiology through an astonishing evolution. New artificial intelligence and deep learning methods capitalize on many past innovations in magnetic resonance imaging (MRI) to reach unprecedented speed, image quality, and new contrasts. Similarly exciting developments in computed tomography (CT) include clinically applicable molecular specificity and substantially improved spatial resolution of musculoskeletal structures and diseases. This special issue of Investigative Radiology comprises a collection of expert summaries and reviews on the most impactful innovations and cutting-edge topics in musculoskeletal radiology, including radiomics and deep learning methods for musculoskeletal disease detection, high-resolution MR neurography, deep learning-driven ultra-fast musculoskeletal MRI, MRI-based synthetic CT, quantitative MRI, modern low-field MRI, 7.0 T MRI, dual-energy CT, cone beam CT, kinematic CT, and synthetic contrast generation in musculoskeletal MRI.