Assessment of meniscus with adiabatic T1ρ and T2ρ relaxation time in asymptomatic subjects and patients with mild osteoarthritis: a feasibility study

Measurement of T1ρ dispersion with compressed sensing and magnetization prepared radial balanced steady-state free precession in spontaneous human osteoarthritis

PURPOSE

To assess the potential for accelerating continuous-wave (CW) T1ρ dispersion measurement with compressed sensing approach via studying the effect that the data reduction has on the ability to detect differences between intact and degenerated articular cartilage with different spin-lock amplitudes and to assess quantitative bias due to acceleration.

METHODS

Osteochondral plugs (n = 27, 4 mm diameter) from femur (n = 14) and tibia (n = 13) regions from human cadaver knee joints were obtained from commercial biobank (Science Care, USA) under Ethical permission 134/2015. MRI of specimens was performed at 9.4T with magnetization prepared radial balanced SSFP (bSSFP) readout sequence, and the CWT1ρ relaxation time maps were computed from the measured data. The relaxation time maps were evaluated in the cartilage zones for different acceleration factors. For reference, Osteoarthritis Research Society International (OARSI) grading and biomechanical measurements were performed and correlated with the MRI findings.

RESULTS

Four-fold acceleration of CWT1ρ dispersion measurement by compressed sensing approach was feasible without meaningful loss in the sensitivity to osteoarthritic (OA) changes within the articular cartilage. Differences were significant between intact and OA groups in the superficial and transitional zones, and CWT1ρ correlated moderately with the reference measurements (0.3 < r < 0.7).

CONCLUSION

CWT1ρ was able to differentiate between intact and OA cartilage even with four-fold acceleration. This indicates that acceleration of CWT1ρ dispersion measurement by compressed sensing approach is feasible with negligible loss in the sensitivity to osteoarthritic changes in articular cartilage.

Machine Learning Prediction of Collagen Fiber Orientation and Proteoglycan Content From Multiparametric Quantitative MRI in Articular Cartilage

BACKGROUND

Machine learning models trained with multiparametric quantitative MRIs (qMRIs) have the potential to provide valuable information about the structural composition of articular cartilage.

PURPOSE

To study the performance and feasibility of machine learning models combined with qMRIs for noninvasive assessment of collagen fiber orientation and proteoglycan content.

STUDY TYPE

Retrospective, animal model.

ANIMAL MODEL

An open-source single slice MRI dataset obtained from 20 samples of 10 Shetland ponies (seven with surgically induced cartilage lesions followed by treatment and three healthy controls) yielded to 1600 data points, including 10% for test and 90% for train validation.

FIELD STRENGTH/SEQUENCE

A 9.4 T MRI scanner/qMRI sequences: T₁ , T₂ , adiabatic T_1ρ and T_2ρ , continuous-wave T_1ρ and relaxation along a fictitious field (T_RAFF ) maps.

ASSESSMENT

Five machine learning regression models were developed: random forest (RF), support vector regression (SVR), gradient boosting (GB), multilayer perceptron (MLP), and Gaussian process regression (GPR). A nested cross-validation was used for performance evaluation. For reference, proteoglycan content and collagen fiber orientation were determined by quantitative histology from digital densitometry (DD) and polarized light microscopy (PLM), respectively.

STATISTICAL TESTS

Normality was tested using Shapiro-Wilk test, and association between predicted and measured values was evaluated using Spearman's Rho test. A P-value of 0.05 was considered as the limit of statistical significance.

RESULTS

Four out of the five models (RF, GB, MLP, and GPR) yielded high accuracy (R²  = 0.68-0.75 for PLM and 0.62-0.66 for DD), and strong significant correlations between the reference measurements and predicted cartilage matrix properties (Spearman's Rho = 0.72-0.88 for PLM and 0.61-0.83 for DD). GPR algorithm had the highest accuracy (R²  = 0.75 and 0.66) and lowest prediction-error (root mean squared [RMSE] = 1.34 and 2.55) for PLM and DD, respectively.

DATA CONCLUSION

Multiparametric qMRIs in combination with regression models can determine cartilage compositional and structural features, with higher accuracy for collagen fiber orientation than proteoglycan content.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Ultrashort echo time magnetization transfer imaging of knee cartilage and meniscus after long-distance running

OBJECTIVE

To assess the detection of changes in knee cartilage and meniscus of amateur marathon runners before and after long-distance running using a 3D ultrashort echo time MRI sequence with magnetization transfer preparation (UTE-MT).

METHODS

We recruited 23 amateur marathon runners (46 knees) in this prospective cohort study. MRI scans using UTE-MT and UTE-T2* sequences were performed pre-race, 2 days post-race, and 4 weeks post-race. UTE-MT ratio (UTE-MTR) and UTE-T2* were measured for knee cartilage (eight subregions) and meniscus (four subregions). The sequence reproducibility and inter-rater reliability were also investigated.

RESULTS

Both the UTE-MTR and UTE-T2* measurements showed good reproducibility and inter-rater reliability. For most subregions of cartilage and meniscus, the UTE-MTR values decreased 2 days post-race and increased after 4 weeks of rest. Conversely, the UTE-T2* values increased 2 days post-race and decreased after 4 weeks. The UTE-MTR values in lateral tibial plateau, central medial femoral condyle, and medial tibial plateau showed a significant decrease at 2 days post-race compared to the other two time points (p < 0.05). By comparison, no significant UTE-T2* changes were found for any cartilage subregions. For meniscus, the UTE-MTR values in medial posterior horn and lateral posterior horn regions at 2 days post-race were significantly lower than those at pre-race and 4 weeks post-race (p < 0.05). By comparison, only the UTE-T2* values in medial posterior horn showed a significant difference.

CONCLUSIONS

UTE-MTR is a promising method for the detection of dynamic changes in knee cartilage and meniscus after long-distance running.

KEY POINTS

• Long-distance running causes changes in the knee cartilage and meniscus. • UTE-MT monitors dynamic changes of knee cartilage and meniscal non-invasively. • UTE-MT is superior to UTE-T2* in monitoring dynamic changes in knee cartilage and meniscus.

Myocardium Assessment by Relaxation along Fictitious Field, Extracellular Volume, Feature Tracking, and Myocardial Strain in Hypertensive Patients with Left Ventricular Hypertrophy

Background

Previous research has shown impaired global longitudinal strain (GLS) and slightly elevated extracellular volume fraction (ECV) in hypertensive patients with left ventricular hypertrophy (HTN LVH). Up to now, only little attention has been paid to interactions between macromolecules and free water in hypertrophied myocardium.

Purpose

To evaluate the feasibility of relaxation along a fictitious field with rank 2 (RAFF2) in HTN LVH patients. Study Type. Single institutional case control.

Subjects

9 HTN LVH (age, 69 ± 10 years) and 11 control subjects (age, 54 ± 12 years). Field Strength/Sequence. Relaxation time mapping (T₁, T_1ρ, and T_RAFF2 with 11.8 μT maximum radio frequency field amplitude) was performed at 1.5 T using a Siemens Aera (Erlangen, Germany) scanner equipped with an 18-channel body array coil. Assessment. ECV was calculated using pre- and postcontrast T₁, and global strains parameters were assessed by Segment CMR (Medviso AB Co, Sweden). The parametric maps of T_1ρ and T_RAFF2 were computed using a monoexponential model, while the Bloch-McConnell equations were solved numerically to model effect of the chemical exchange during radio frequency pulses. Statistical Tests. Parametric maps were averaged over myocardium for each subject to be used in statistical analysis. Kolmogorov-Smirnov was used as the normality test followed by Student's t-test and Pearson's correlation to determine the difference between the HTN LVH patients and controls along with Hedges' g effect size and the association between variables, respectively.

Results

T_RAFF2 decreased statistically (83 ± 2 ms vs 88 ± 6 ms, P < 0.031), and global longitudinal strain was impaired (GLS, −14 ± 3 vs − 18 ± 2, P < 0.002) in HTN LVH patients compared to the controls, respectively. Also, significant negative correlation was found between T_RAFF2 and GLS (r = −0.53, P < 0.05). Data Conclusion. Our results suggest that T_RAFF2 decrease in HTN LVH patients may be explained by gradual collagen accumulation which can be reflected in GLS changes. Most likely, it increases the water proton interactions and consequently decreases T_RAFF2 before myocardial scarring.

Tractography of Porcine Meniscus Microstructure Using High-Resolution Diffusion Magnetic Resonance Imaging

To noninvasively evaluate the three-dimensional collagen fiber architecture of porcine meniscus using diffusion MRI, meniscal specimens were scanned using a 3D diffusion-weighted spin-echo pulse sequence at 7.0 T. The collagen fiber alignment was revealed in each voxel and the complex 3D collagen network was visualized for the entire meniscus using tractography. The proposed automatic segmentation methods divided the whole meniscus to different zones (Red-Red, Red-White, and White-White) and different parts (anterior, body, and posterior). The diffusion tensor imaging (DTI) metrics were quantified based on the segmentation results. The heatmap was generated to investigate the connections among different regions of meniscus. Strong zonal-dependent diffusion properties were demonstrated by DTI metrics. The fractional anisotropy (FA) value increased from 0.13 (White-White zone) to 0.26 (Red-Red zone) and the radial diffusivity (RD) value changed from 1.0 × 10^-3 mm²/s (White-White zone) to 0.7 × 10^-3 mm²/s (Red-Red zone). Coexistence of both radial and circumferential collagen fibers in the meniscus was evident by diffusion tractography. Weak connections were found between White-White zone and Red-Red zone in each part of the meniscus. The anterior part and posterior part were less connected, while the body part showed high connections to both anterior part and posterior part. The tractography based on diffusion MRI may provide a complementary method to study the integrity of meniscus and nondestructively visualize the 3D collagen fiber architecture.

Macromolecular fraction (MMF) from 3D ultrashort echo time cones magnetization transfer (3D UTE-Cones-MT) imaging predicts meniscal degeneration and knee osteoarthritis

OBJECTIVE

Meniscal degeneration is strongly associated with osteoarthritis (OA). We aimed to evaluate a 3D ultrashort-echo-time Cones magnetization transfer (UTE-Cones-MT) sequence for quantification of macromolecular fraction (MMF) and MT ratio (MTR) in menisci of healthy volunteers and patients with different degrees of OA.

METHODS

Patients with mild OA (n = 19; 37-86 years; 10 males) or advanced OA (n = 12; 52-88 years; 4 males) and healthy volunteers (n = 17; 20-49 years; 7 males) were scanned with T2-FSE and UTE-Cones-MT sequences at 3T. Morphological assessment was performed using meniscal whole-organ magnetic resonance imaging score (WORMS). MMF and MTR were calculated for menisci, and correlated with age and meniscal WORMS scores. The diagnostic efficiency was performed by using receiver operating characteristic (ROC) curve and the area under the curve (AUC) analyses.

RESULTS

Decreased MMF and MTR were observed in menisci of patients with mild or advanced OA compared with healthy subjects, and in menisci with tears (Grade 2-4) compared with normal menisci (Grade 0). Significant negative correlations were observed between MMF (r = -0.769, P < 0.01), MTR (r = -0.320, P < 0.01), and meniscal WORMS score. There was a mild negative correlation between MMF (r = -0.438, P < 0.01), MTR (r = -0.289, P < 0.01), and age. The AUC values of MMF and MTR in the four horns of meniscus and the posterior horn medial meniscus for differentiating OA patients from healthy volunteers were 0.762 and 0.699, and 0.835 and 0.883, respectively.

CONCLUSION

The 3D UTE-Cones-MT biomarkers of MTR and especially MMF can detect compositional changes in meniscus and differentiate healthy subjects from patients with mild or advanced knee OA.

Evaluation of articular cartilage with quantitative MRI in an equine model of post-traumatic osteoarthritis

Chondral lesions lead to degenerative changes in the surrounding cartilage tissue, increasing the risk of developing post-traumatic osteoarthritis (PTOA). This study aimed to investigate the feasibility of quantitative magnetic resonance imaging (qMRI) for evaluation of articular cartilage in PTOA. Articular explants containing surgically induced and repaired chondral lesions were obtained from the stifle joints of seven Shetland ponies (14 samples). Three age-matched nonoperated ponies served as controls (six samples). The samples were imaged at 9.4 T. The measured qMRI parameters included T₁ , T₂ , continuous-wave T_1ρ (CWT_1ρ ), adiabatic T_1ρ (AdT_1ρ ), and T_2ρ (AdT_2ρ ) and relaxation along a fictitious field (T_RAFF ). For reference, cartilage equilibrium and dynamic moduli, proteoglycan content and collagen fiber orientation were determined. Mean values and profiles from full-thickness cartilage regions of interest, at increasing distances from the lesions, were used to compare experimental against control and to correlate qMRI with the references. Significant alterations were detected by qMRI parameters, including prolonged T₁ , CWT_1ρ , and AdT_1ρ in the regions adjacent to the lesions. The changes were confirmed by the reference methods. CWT_1ρ was more strongly associated with the reference measurements and prolonged in the affected regions at lower spin-locking amplitudes. Moderate to strong correlations were found between all qMRI parameters and the reference parameters (ρ = -0.531 to -0.757). T₁ , low spin-lock amplitude CWT_1ρ , and AdT_1ρ were most responsive to changes in visually intact cartilage adjacent to the lesions. In the context of PTOA, these findings highlight the potential of T₁ , CWT_1ρ , and AdT_1ρ in evaluation of compositional and structural changes in cartilage.

Multiparametric MR imaging reveals early cartilage degeneration at 2 and 8 weeks after ACL transection in a rabbit model

In this study, the rabbit model with anterior cruciate ligament transection (ACLT) was used to investigate early degenerative changes in cartilage using multiparametric quantitative magnetic resonance imaging (qMRI). ACLT was surgically induced in the knees of skeletally mature New Zealand White rabbits (n = 14). ACL transected and contralateral knee compartments-medial femur, lateral femur, medial tibia, and lateral tibia-were harvested 2 (n = 8) and 8 weeks (n = 6) postsurgery. Twelve age-matched nonoperated rabbits served as control. qMRI was conducted at 9.4 T and included relaxation times T₁ , T₂ , continuous-wave T_1ρ (CWT_1ρ ), adiabatic T_1ρ (AdT_1ρ ), adiabatic T_2ρ (AdT_2ρ ), and relaxation along a fictitious field (T_RAFF ). For reference, quantitative histology and biomechanical measurements were carried out. Posttraumatic changes were primarily noted in the superficial half of the cartilage. Prolonged T₁ , T₂ , CWT_1ρ , and AdT_1ρ were observed in the lateral femur 2 and 8 weeks post-ACLT, compared with the corresponding control and contralateral groups (P < .05). Collagen orientation was significantly altered in the lateral femur at 2 weeks post-ACLT compared with the corresponding control group. In the medial femur, all the studied relaxation time parameters, except T_RAFF , were increased 8 weeks post-ACLT, as compared with the corresponding contralateral and control groups (P < .05). Similarly, significant proteoglycan loss was observed in the medial femur at 8 weeks following surgery (P < .05). Multiparametric MRI demonstrated early degenerative changes primarily in the superficial cartilage with T₁ , T₂ , CWT_1ρ , and AdT_1ρ sensitive to cartilage changes at 2 weeks after surgery.

Meniscus Stiffness Measured with Shear Wave Elastography is Correlated with Meniscus Degeneration

The aim of this study was to evaluate the diagnostic performance of shear wave elastography (SWE) in human meniscus degeneration, with histology serving as the standard of reference. This comparative in vivo and ex vivo study was performed in 15 medial and 15 lateral menisci from 13 patients undergoing total knee arthroplasty (TKA) for primary osteoarthritis with varus deformity. Patients underwent in vivo coronal measurement with SWE for meniscus before surgery. Then, ex vivo assessment of meniscus stiffness with SWE was performed with the tissue obtained after TKA. SWE measurements were made in coronal and sagittal views with respect to the meniscus. Samples were analyzed histologically on a 0-18 scale according to the level of degeneration based on surface integrity, cellularity, fiber organization, collagen alignment and Safranin O staining intensity. The correlation between SWE measurement scale and histology was analyzed using Spearman's correlation. The area under the receiver operating characteristic curve (AUROC) was used to calculate the diagnostic performance of SWE in evaluating meniscus degeneration. Significant increases in stiffness were observed with increasing histologic degeneration in both in vivo and ex vivo coronal SWE. AUROCs were 0.79 (95% confidence interval [CI]: 0.49-1.00) for in vivo coronal SWE, 0.73 (95% CI: 0.53-0.95) for ex vivo coronal SWE and 0.56 (95% CI: 0.27-0.84) for ex vivo sagittal SWE. The medial meniscus, which exhibited more degeneration on histologic analysis, had greater stiffness than the lateral meniscus on ex vivo coronal SWE. The values of meniscus stiffness measured with SWE are correlated with the degree of meniscus degeneration. Further large-scale prospective studies may confirm the diagnostic performance of SWE as a non-invasive tool to assess meniscus degeneration.

Biexponential T1ρ relaxation mapping of human knee menisci

BACKGROUND

Measuring T_1ρ in the knee menisci can potentially be used as noninvasive biomarkers in detecting early-stage osteoarthritis (OA).

PURPOSE

To demonstrate the feasibility of biexponential T_1ρ relaxation mapping of human knee menisci.

STUDY TYPE

Prospective.

POPULATION

Eight healthy volunteers with no known inflammation, trauma, or pain in the knee and three symptomatic subjects with early knee OA.

FIELD STRENGTH/SEQUENCE

Customized Turbo-FLASH sequence to acquire 3D-T_1ρ -weighted images on a 3 T MRI scanner.

ASSESSMENT

T_1ρ relaxation values were assessed in 11 meniscal regions of interest (ROIs) using monoexponential and biexponential models.

STATISTICAL TESTS

Nonparametric rank-sum tests, Kruskal-Wallis test, and coefficient of variation.

RESULTS

The mean monoexponential T_1ρ relaxation in the lateral menisci were 28.05 ± 4.2 msec and 37.06 ± 10.64 msec for healthy subjects and early knee OA patients, respectively, while the short and long components were 8.07 ± 0.5 msec and 72.35 ± 3.2 msec for healthy subjects and 2.63 ± 2.99 msec and 55.27 ± 24.76 msec for early knee OA patients, respectively. The mean monoexponential T_1ρ relaxation in the medial menisci were 34.30 ± 3.8 msec and 37.26 ± 11.38 msec for healthy and OA patients, respectively, while the short and long components were 7.76 ± 0.7 msec and 72.19 ± 4.2 msec for healthy subjects and 3.06 ± 3.24 msec and 55.27 ± 24.59 msec for OA patients, respectively. Statistically significant (P ≤ 0.05) differences were observed in the monoexponential relaxation between some of the ROIs. The T_1ρ,short was significantly lower (P = 0.02) in the patients than controls. The rmsCV% ranges were 1.51-16.6%, 3.59-14.3%, and 4.91-15.6% for T_1ρ -mono, T_1ρ -short, and T_1ρ -long, respectively.

DATA CONCLUSION

Our results showed that in all ROIs, T_1ρ relaxation times of outer zones (red zones) were less than inner zones (white zones). Monoexponential T_1ρ was increased in medial, lateral, and body menisci of early OA while the biexponential numbers were decreased in early OA patients.

LEVEL OF EVIDENCE

2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2019;50:824-835.