Multiparametric MRI and Computational Modelling in the Assessment of Human Articular Cartilage Properties: A Comprehensive Approach

Time-efficient combined morphologic and quantitative joint MRI: an in situ study of standardized knee cartilage defects in human cadaveric specimens

BACKGROUND

Quantitative techniques such as T2 and T1ρ mapping allow evaluating the cartilage and meniscus. We evaluated multi-interleaved X-prepared turbo-spin echo with intuitive relaxometry (MIXTURE) sequences with turbo spin-echo (TSE) contrast and additional parameter maps versus reference TSE sequences in an in situ model of human cartilage defects.

METHODS

Standardized cartilage defects of 8, 5, and 3 mm in diameter were created in the lateral femora of ten human cadaveric knee specimens (81 ± 10 years old; nine males, one female). MIXTURE sequences providing proton density-weighted fat-saturated images and T2 maps or T1-weighted images and T1ρ maps as well as the corresponding two- and three-dimensional TSE reference sequences were acquired before and after defect creation (3-T scanner; knee coil). Defect delineability, bone texture, and cartilage relaxation times were quantified. Appropriate parametric or non-parametric tests were used.

RESULTS

Overall, defect delineability and texture features were not significantly different between the MIXTURE and reference sequences (p ≤ 0.47). After defect creation, relaxation times significantly increased in the central femur (T2pre = 51 ± 4 ms [mean ± standard deviation] versus T2post = 56 ± 4 ms; p = 0.002) and all regions combined (T1ρpre = 40 ± 4 ms versus T1ρpost = 43 ± 4 ms; p = 0.004).

CONCLUSIONS

MIXTURE permitted time-efficient simultaneous morphologic and quantitative joint assessment based on clinical image contrasts. While providing T2 or T1ρ maps in clinically feasible scan time, morphologic image features, i.e., cartilage defects and bone texture, were comparable between MIXTURE and reference sequences.

RELEVANCE STATEMENT

Equally time-efficient and versatile, the MIXTURE sequence platform combines morphologic imaging using familiar contrasts, excellent image correspondence versus corresponding reference sequences and quantitative mapping information, thereby increasing the diagnostic value beyond mere morphology.

KEY POINTS

• Combined morphologic and quantitative MIXTURE sequences are based on three-dimensional TSE contrasts. • MIXTURE sequences were studied in an in situ human cartilage defect model. • Morphologic image features, i.e., defect delineabilty and bone texture, were investigated. • Morphologic image features were similar between MIXTURE and reference sequences. • MIXTURE allowed time-efficient simultaneous morphologic and quantitative knee joint assessment.

Two for One-Combined Morphologic and Quantitative Knee Joint MRI Using a Versatile Turbo Spin-Echo Platform

Quantitative MRI techniques such as T2 and T1ρ mapping are beneficial in evaluating knee joint pathologies; however, long acquisition times limit their clinical adoption. MIXTURE (Multi-Interleaved X-prepared Turbo Spin-Echo with IntUitive RElaxometry) provides a versatile turbo spin-echo (TSE) platform for simultaneous morphologic and quantitative joint imaging. Two MIXTURE sequences were designed along clinical requirements: "MIX1", combining proton density (PD)-weighted fat-saturated (FS) images and T2 mapping (acquisition time: 4:59 min), and "MIX2", combining T1-weighted images and T1ρ mapping (6:38 min). MIXTURE sequences and their reference 2D and 3D TSE counterparts were acquired from ten human cadaveric knee joints at 3.0 T. Contrast, contrast-to-noise ratios, and coefficients of variation were comparatively evaluated using parametric tests. Clinical radiologists (n = 3) assessed diagnostic quality as a function of sequence and anatomic structure using five-point Likert scales and ordinal regression, with a significance level of α = 0.01. MIX1 and MIX2 had at least equal diagnostic quality compared to reference sequences of the same image weighting. Contrast, contrast-to-noise ratios, and coefficients of variation were largely similar for the PD-weighted FS and T1-weighted images. In clinically feasible scan times, MIXTURE sequences yield morphologic, TSE-based images of diagnostic quality and quantitative parameter maps with additional insights on soft tissue composition and ultrastructure.

[Current MR imaging of cartilage in the context of knee osteoarthritis (part 1) : Principles and sequences]

Magnetic resonance imaging (MRI) is the clinical method of choice for cartilage imaging in the context of degenerative and nondegenerative joint diseases. The MRI-based definitions of osteoarthritis rely on the detection of osteophytes, cartilage pathologies, bone marrow edema and meniscal lesions but currently a scientific consensus is lacking. In the clinical routine proton density-weighted, fat-suppressed 2D turbo spin echo sequences with echo times of 30-40 ms are predominantly used, which are sufficiently sensitive and specific for the assessment of cartilage. The additionally acquired T1-weighted sequences are primarily used for evaluating other intra-articular and periarticular structures. Diagnostically relevant artifacts include magic angle and chemical shift artifacts, which can lead to artificial signal enhancement in cartilage or incorrect representations of the subchondral lamina and its thickness. Although scientifically validated, high-resolution 3D gradient echo sequences (for cartilage segmentation) and compositional MR sequences (for quantification of physical tissue parameters) are currently reserved for scientific research questions. The future integration of artificial intelligence techniques in areas such as image reconstruction (to reduce scan times while maintaining image quality), image analysis (for automated identification of cartilage defects), and image postprocessing (for automated segmentation of cartilage in terms of volume and thickness) will significantly improve the diagnostic workflow and advance the field further.

Rapid Whole-Knee Quantification of Cartilage Using T1, T2*, and TRAFF2 Mapping With Magnetic Resonance Fingerprinting

OBJECTIVE

Quantitative Magnetic Resonance Imaging (MRI) holds great promise for the early detection of cartilage deterioration. Here, a Magnetic Resonance Fingerprinting (MRF) framework is proposed for comprehensive and rapid quantification of T1, T2*, and TRAFF2 with whole-knee coverage.

METHODS

A MRF framework was developed to achieve quantification of Relaxation Along a Fictitious Field in the 2nd rotating frame of reference ( TRAFF2) along with T1 and T2*. The proposed sequence acquires 65 measurements of 25 high-resolution slices, interleaved with 7 inversion pulses and 40 RAFF2 trains, for whole-knee quantification in a total acquisition time of 3:25 min. Comparison with reference T1, T2*, and TRAFF2 methods was performed in phantom and in seven healthy subjects at 3 T. Repeatability (test-retest) with and without repositioning was also assessed.

RESULTS

Phantom measurements resulted in good agreement between MRF and the reference with mean biases of -54, 2, and 5 ms for T1, T2*, and TRAFF2, respectively. Complete characterization of the whole-knee cartilage was achieved for all subjects, and, for the femoral and tibial compartments, a good agreement between MRF and reference measurements was obtained. Across all subjects, the proposed MRF method yielded acceptable repeatability without repositioning ( R2 ≥ 0.94) and with repositioning ( R2 ≥ 0.57) for T1, T2*, and TRAFF2.

SIGNIFICANCE

The short scan time combined with the whole-knee coverage makes the proposed MRF framework a promising candidate for the early assessment of cartilage degeneration with quantitative MRI, but further research may be warranted to improve repeatability after repositioning and assess clinical value in patients.

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.

Quantitative assessment of articular cartilage degeneration using 3D ultrashort echo time cones adiabatic T1ρ (3D UTE-Cones-AdiabT1ρ) imaging

OBJECTIVES

To evaluate articular cartilage degeneration using quantitative three-dimensional ultrashort-echo-time cones adiabatic-T1ρ (3D UTE-Cones-AdiabT1ρ) imaging.

METHODS

Sixty-six human subjects were recruited for this study. Kellgren-Lawrence (KL) grade and Whole-Organ Magnetic-Resonance-Imaging Score (WORMS) were evaluated by two musculoskeletal radiologists. The human subjects were categorized into three groups, namely normal controls (KL0), doubtful-minimal osteoarthritis (OA) (KL1-2), and moderate-severe OA (KL3-4). WORMS were regrouped to encompass the extent of lesions and the depth of lesions. The UTE-Cones-AdiabT1ρ values were obtained using 3D UTE-Cones data acquisitions preceded by seven paired adiabatic full passage pulses that corresponded to seven spin-locking times (TSLs) of 0, 12, 24, 36, 48, 72, and 96 ms. The performance of the UTE-Cones-AdiabT1ρ technique in evaluating the degeneration of knee cartilage was assessed via the ANOVA comparisons with subregional analysis and Spearman's correlation coefficient as well as the receiver-operating-characteristic (ROC) curve.

RESULTS

UTE-Cones-AdiabT1ρ showed significant positive correlations with KL grade (r = 0.15, p < 0.05) and WORMS (r = 0.57, p < 0.05). Higher UTE-Cones-AdiabT1ρ values were observed in both larger and deeper lesions in the cartilage. The differences in UTE-Cones-AdiabT1ρ values among different extent and depth groups of cartilage lesions were all statistically significant (p < 0.05). Subregional analyses showed that the correlations between UTE-Cones-AdiabT1ρ and WORMS varied with the location of cartilage. The AUC value of UTE-Cones-AdiabT1ρ for mild cartilage degeneration (WORMS=1) was 0.8. The diagnostic threshold value of UTE-Cones-AdiabT1ρ for mild cartilage degeneration was 39.4 ms with 80.8% sensitivity.

CONCLUSIONS

The 3D UTE-Cones-AdiabT1ρ sequence can be useful in quantitative evaluation of articular cartilage degeneration.

KEY POINTS

• The 3D UTE-Cones-AdiabT1ρ sequence can distinguish mild cartilage degeneration from normal cartilage with a diagnostic threshold value of 39.4 ms for mild cartilage degeneration with 80.8% sensitivity. • Higher UTE-Cones-AdiabT1ρ values were observed in both larger and deeper lesions in the articular cartilage. • UTE-Cones-AdiabT1ρ is a promising biomarker for quantitative evaluation of early cartilage degeneration.

Evaluation of cartilage degeneration using multiparametric quantitative ultrashort echo time-based MRI: an ex vivo study

BACKGROUND

The quantitative MR techniques developed rapidly, vary MR-biomarkers have shown the ability to assess the quality of articular cartilage. This study aimed to investigate the diagnostic efficacy of multi-parametric quantitative ultrashort echo time (UTE)-based MRI for evaluating human cartilage degeneration.

METHODS

Twenty fresh anterolateral femoral condyle samples were obtained from 20 patients (age, 58.8±6.6 years; 6 females) who underwent total knee arthroplasty due to primary osteoarthritis (OA). The samples were imaged using UTE-based magnetization transfer (UTE-MT), UTE-based adiabatic T1ρ (UTE-AdiabT1ρ), UTE-based T2* (UTE-T2*), and CubeQuant-T2 sequences. Cartilage degeneration was classified based on the OA Research Society International grade and polarized light microscopy (PLM) collagen organization score. Spearman's correlation analysis was used to determine the relationships between quantitative MRI biomarkers [UTE-MT ratio (UTE-MTR), UTE-AdiabT1ρ, UTE-T2*, and CubeQuant-T2], OA Research Society International grade, and PLM collagen organization score. The diagnostic efficacy of each MRI biomarker for the detection of mild cartilage degeneration was assessed using the area under the receiver operating characteristic (ROC) curve (AUC).

RESULTS

Of the quantitative MRI biomarkers, UTE-MTR had the strongest correlation with both OA Research Society International grade (r=-0.709, P<0.001) and PLM collagen organization score (r=0.579, P<0.001). The UTE-MTR and UTE-AdiabT1ρ values showed significant differences between the normal group and the mild degeneration group (P=0.047 and 0.015, respectively), while UTE-T2* and CubeQuant-T2 did not. The UTE-MTR values were 15.90%±1.06% and 14.59%±1.35% for normal and mildly degenerated cartilage, respectively. The UTE-AdiabT1ρ values were 40.19±2.87 and 42.6±2.26 ms for normal and mildly degenerated cartilage, respectively. ROC analysis showed that UTE-MTR (AUC =0.805, P=0.001, sensitivity =73.7%, specificity =89.5%) had the highest diagnostic efficacy for mild cartilage degeneration, while UTE-AdiabT1ρ (AUC =0.727, P=0.017) and CubeQuant-T2 (AUC =0.712, P=0.026) showed lower diagnostic efficacy.

CONCLUSIONS

Quantitative UTE-MT and UTE-AdiabT1ρ biomarkers may potentially be used in the evaluation of early cartilage degeneration.

Human Umbilical Mesenchymal Stromal Cells Mixed with Hyaluronan Transplantation Decreased Cartilage Destruction in a Rabbit Osteoarthritis Model

Osteoarthritis (OA), the most common type of arthritis, causes pain in joints and disability. Due to the absence of ideal effective medication, stem cell transplantation emerges as a new hope for OA therapy. This study is aimed at evaluating the capability of human umbilical cord mesenchymal stromal cells (HUCMSCs) mixed with hyaluronan (HA) to treat osteoarthritis in a rabbit model. Differentiation capability of HUCMSCs, magnetic resonance image examination, and immunohistochemistry of the cartilage after transplantation of HUCMSCs mixed with HA in a rabbit OA model were explored. HUCMSCs exhibited typical mesenchymal stromal cell (MSC) characteristics, including spindle-shaped morphology, surface marker expressions (positive for human leukocyte antigen- (HLA-) ABC, CD44, CD73, CD90, and CD105; negative for HLA-DR, CD34, and CD45), and trilineage differentiation (chondrogenesis, adipogenesis, and osteogenesis). The gene expression of SOX9, type II collagen, and aggrecan in the HUCMSC-derived chondrocytes mixed with HA was increased after in vitro chondrogenesis compared with HUCMSCs. A gross and histological significant improvement in hyaline cartilage destruction after HUCMSCs mixed with HA was noted in the animal model compared to the OA knees. The International Cartilage Repair Society histological score and Safranin O staining were significantly higher for the treated knees than the control knees (p < 0.05). Moreover, the expression of MMP13 was significantly decreased in the treated knees than in the OA knees. In conclusion, HUCMSCs mixed with HA in vitro and in vivo might attenuate the cartilage destruction in osteoarthritis. Our study provided evidence for future clinical trials.

Micro- and Macroscale Assessment of Posterior Cruciate Ligament Functionality Based on Advanced MRI Techniques

T2 mapping assesses tissue ultrastructure and composition, yet the association of imaging features and tissue functionality is oftentimes unclear. This study aimed to elucidate this association for the posterior cruciate ligament (PCL) across the micro- and macroscale and as a function of loading. Ten human cadaveric knee joints were imaged using a clinical 3.0T scanner and high-resolution morphologic and T2 mapping sequences. Emulating the posterior drawer test, the joints were imaged in the unloaded (δ0) and loaded (δ1) configurations. For the entire PCL, its subregions, and its osseous insertion sites, loading-induced changes were parameterized as summary statistics and texture variables, i.e., entropy, homogeneity, contrast, and variance. Histology confirmed structural integrity. Statistical analysis was based on parametric and non-parametric tests. Mean PCL length (37.8 ± 1.8 mm [δ0]; 44.0 ± 1.6 mm [δ1] [p < 0.01]), mean T2 (35.5 ± 2.0 ms [δ0]; 37.9 ± 1.3 ms [δ1] [p = 0.01]), and mean contrast values (4.0 ± 0.6 [δ0]; 4.9 ± 0.9 [δ1] [p = 0.01]) increased significantly under loading. Other texture features or ligamentous, osseous, and meniscal structures remained unaltered. Beyond providing normative T2 values across various scales and configurations, this study suggests that ligaments can be imaged morphologically and functionally based on joint loading and advanced MRI acquisition and post-processing techniques to assess ligament integrity and functionality in variable diagnostic contexts.

Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage composition

BACKGROUND

Articular cartilage degeneration is the hallmark change of osteoarthritis, a severely disabling disease with high prevalence and considerable socioeconomic and individual burden. Early, potentially reversible cartilage degeneration is characterized by distinct changes in cartilage composition and ultrastructure, while the tissue's morphology remains largely unaltered. Hence, early degenerative changes may not be diagnosed by clinical standard diagnostic tools.

METHODS

Against this background, this study introduces a novel method to determine the tissue composition non-invasively. Our method involves quantitative MRI parameters (i.e., T₁, T_1ρ, T₂ and [Formula: see text] maps), compositional reference measurements (i.e., microspectroscopically determined local proteoglycan [PG] and collagen [CO] contents) and machine learning techniques (i.e., artificial neural networks [ANNs] and multivariate linear models [MLMs]) on 17 histologically grossly intact human cartilage samples.

RESULTS

Accuracy and precision were higher in ANN-based predictions than in MLM-based predictions and moderate-to-strong correlations were found between measured and predicted compositional parameters.

CONCLUSION

Once trained for the clinical setting, advanced machine learning techniques, in particular ANNs, may be used to non-invasively determine compositional features of cartilage based on quantitative MRI parameters with potential implications for the diagnosis of (early) degeneration and for the monitoring of therapeutic outcomes.

Longitudinal T2 Mapping and Texture Feature Analysis in the Detection and Monitoring of Experimental Post-Traumatic Cartilage Degeneration

Background: Traumatic cartilage injuries predispose articulating joints to focal cartilage defects and, eventually, posttraumatic osteoarthritis. Current clinical-standard imaging modalities such as morphologic MRI fail to reliably detect cartilage trauma and to monitor associated posttraumatic degenerative changes with oftentimes severe prognostic implications. Quantitative MRI techniques such as T2 mapping are promising in detecting and monitoring such changes yet lack sufficient validation in controlled basic research contexts. Material and Methods: 35 macroscopically intact cartilage samples obtained from total joint replacements were exposed to standardized injurious impaction with low (0.49 J, n = 14) or high (0.98 J, n = 14) energy levels and imaged before and immediately, 24 h, and 72 h after impaction by T2 mapping. Contrast, homogeneity, energy, and variance were quantified as features of texture on each T2 map. Unimpacted controls (n = 7) and histologic assessment served as reference. Results: As a function of impaction energy and time, absolute T2 values, contrast, and variance were significantly increased, while homogeneity and energy were significantly decreased. Conclusion: T2 mapping and texture feature analysis are sensitive diagnostic means to detect and monitor traumatic impaction injuries of cartilage and associated posttraumatic degenerative changes and may be used to assess cartilage after trauma to identify “cartilage at risk”.

A serial multiparametric quantitative magnetic resonance imaging study to assess proteoglycan depletion of human articular cartilage and its effects on functionality

Water, collagen, and proteoglycans determine articular cartilage functionality. If altered, susceptibility to premature degeneration is increased. This study investigated the effects of enzymatic proteoglycan depletion on cartilage functionality as assessed by advanced Magnetic Resonance Imaging (MRI) techniques under standardized loading. Lateral femoral condylar cartilage-bone samples from patients undergoing knee replacement (n = 29) were serially imaged by Proton Density-weighted and T1, T1ρ, T2, and T2* mapping sequences on a clinical 3.0 T MRI scanner (Achieva, Philips). Using pressure-controlled indentation loading, samples were imaged unloaded and quasi-statically loaded to 15.1 N and 28.6 N, and both before and after exposure to low-concentrated (LT, 0.1 mg/mL, n = 10) or high-concentrated trypsin (HT, 1.0 mg/mL, n = 10). Controls were not treated (n = 9). Responses to loading were assessed for the entire sample and regionally, i.e. sub- and peri-pistonally, and zonally, i.e. upper and lower sample halves. Trypsin effects were quantified as relative changes (Δ), analysed using appropriate statistical tests, and referenced histologically. Histological proteoglycan depletion was reflected by significant sub-pistonal decreases in T1 (p = 0.003) and T2 (p = 0.008) after HT exposure. Loading-induced changes in T1ρ and T2* were not related. In conclusion, proteoglycan depletion alters cartilage functionality and may be assessed using serial T1 and T2 mapping under loading.

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.

Osteoarthritis year in review 2019: mechanics

Mechanics play a critical - but not sole - role in the pathogenesis of osteoarthritis, and recent research has highlighted how mechanical constructs are relevant at the cellular, joint, and whole-body level related to osteoarthritis outcomes. This review examined papers from April 2018 to April 2019 that reported on the role of mechanics in osteoarthritis etiology, with a particular emphasis on studies that focused on the interaction between movement and tissue biomechanics with other clinical outcomes relevant to the pathophysiology of osteoarthritis. Studies were grouped by themes that were particularly prevalent from the past year. Results of the search highlighted the large exposure of knee-related research relative to other body areas, as well as studies utilizing laboratory-based motion capture technology. New research from this past year highlighted the important role that rate of exerted loads and rate of muscle force development - rather than simply force capacity (strength) - have in OA etiology and treatment. Further, the role of muscle activation patterns in functional and structural aspects of joint health has received much interest, though findings remain equivocal. Finally, new research has identified potential mechanical outcome measures that may be related to osteoarthritis disease progression. Future research should continue to combine knowledge of mechanics with other relevant research techniques, and to identify mechanical markers of joint health and structural and functional disease progression that are needed to best inform disease prevention, monitoring, and treatment.

Quantitative ultrashort echo time magnetization transfer (UTE-MT) for diagnosis of early cartilage degeneration: comparison with UTE-T2* and T2 mapping

Background

To investigate the feasibility of using quantitative ultrashort echo time magnetization transfer (UTE-MT) technique in diagnosing early cartilage degeneration and to compare the technique's diagnostic efficacy with UTE-T2* mapping and T2 mapping.

Methods

Twenty human anterolateral condyle specimens with degeneration were obtained from volunteers undergoing total knee arthroplasty (TKA); they then underwent magnetic resonance (MR) scan on a clinical 3.0T scanner (GE, MR750). Seventy-two regions of interest (ROI) were manually drawn on specimens for UTE-MT, UTE-T2*, and T2 measurement, and the corresponding cartilage-bone regions were further divided into degeneration classifications of normal (n=11, Mankin scores 0-1), mild (n=28, Mankin scores 2-5), moderate (n=21, Mankin scores 6-9), and severe (n=12, Mankin scores 10-14) based on histological measures of degeneration (i.e., Mankin scores) as a reference standard. Differences among groups and correlations between quantitative MR parameters and Mankin scores were assessed using analysis of variance (ANOVA), Tamhane-T2, LSD, Kruskal-Wallis tests, and Spearman's correlation coefficient. The receiver-operating characteristic (ROC) curve was used to compare the diagnostic efficacy of different quantitative MR parameters for the detection of mild cartilage degeneration.

Results

The UTE magnetization transfer ratio (UTE-MTR) in the normal group was significantly different from the mild group (P=0.021), moderate group (P<0.001), and severe group (P<0.001). Significant differences were observed in the T2* values between both the normal group and the moderate group (P<0.032), and between the normal group and the severe group (P<0.001). For T2 values, the only significant difference was observed between the severe group and the normal group (P=0.011). The UTE-MTR, UTE-T2*, and T2 values were all significantly correlated with Mankin scores: UTE-MTR values were strongly (r=-0.678, P<0.001) correlated, UTE-T2* values were markedly correlated (r=-0.501, P<0.001), and T2 values were weakly correlated (r=0.337, P=0.004) correlated with Mankin scores. The diagnostic efficacy of UTE-MTR (AUC =0.828, P=0.002) was better than UTE T2* mapping and T2 mapping (AUC =0.604, P=0.318; AUC =0.644, P=0.165, respectively) for the diagnosis of early cartilage degeneration.

Conclusions

UTE-MTR values were strongly correlated with histological grades of cartilage degeneration, and its diagnostic efficacy was better than both UTE T2* mapping and T2 mapping in detecting early cartilage degeneration. Once the clinical potential of the technique has been confirmed, UTE-MT may provide a promising imaging biomarker with potential application in a more comprehensive diagnosis and monitoring of cartilage degeneration.

Human articular cartilage mechanosensitivity is related to histological degeneration - a functional MRI study

OBJECTIVE

To investigate changes in response to sequential pressure-controlled loading and unloading in human articular cartilage of variable histological degeneration using serial T1ρ mapping.

METHOD

We obtained 42 cartilage samples of variable degeneration from the medial femoral condyles of 42 patients undergoing total knee replacement. Samples were placed in a standardized artificial knee joint within an MRI-compatible whole knee-joint compressive loading device and imaged before (δ₀), during (δ_ld1, δ_ld2, δ_ld3, δ_ld4, δ_ld5) and after (δ_rl1, δ_rl2, δ_rl3, δ_rl4, δ_rl5) pressure-controlled loading to 0.663 ± 0.021 kN (94% body weight) using serial T1ρ mapping (spin-lock multigradient echo sequence; 3.0T MRI system [Achieva, Philips]). Reference assessment included histology (Mankin scoring) and conventional biomechanics (Tangent stiffness). We dichotomized sample into intact (n = 21) and degenerative (n = 21) based on histology and analyzed data using Mann Whitney, Kruskal Wallis, one-way ANOVA tests and Spearman's correlation, respectively.

RESULTS

At δ₀, we found no significant differences between intact and degenerative samples, while the response-to-loading patterns were distinctly different. In intact samples, T1ρ increases were consistent and non-significant, while in degenerative samples, T1ρ increases were significantly higher (P = 0.004, δ0 vs δld1, δ0 vs δld3), yet undulating and variable. With unloading, T1ρ increases subsided, yet were persistently elevated beyond δ0.

CONCLUSION

Cartilage mechanosensitivity is related to histological degeneration and assessable by serial T1ρ mapping. Unloaded, T1ρ characteristics are not significantly different in intact vs degenerative cartilage, while load bearing is organized in intact cartilage and disorganized in degenerative cartilage.

Towards Patient-Specific Computational Modelling of Articular Cartilage on the Basis of Advanced Multiparametric MRI Techniques

Cartilage degeneration is associated with tissue softening and represents the hallmark change of osteoarthritis. Advanced quantitative Magnetic Resonance Imaging (qMRI) techniques allow the assessment of subtle tissue changes not only of structure and morphology but also of composition. Yet, the relation between qMRI parameters on the one hand and microstructure, composition and the resulting functional tissue properties on the other hand remain to be defined. To this end, a Finite-Element framework was developed based on an anisotropic constitutive model of cartilage informed by sample-specific multiparametric qMRI maps, obtained for eight osteochondral samples on a clinical 3.0 T MRI scanner. For reference, the same samples were subjected to confined compression tests to evaluate stiffness and compressibility. Moreover, the Mankin score as an indicator of histological tissue degeneration was determined. The constitutive model was optimized against the resulting stress responses and informed solely by the sample-specific qMRI parameter maps. Thereby, the biomechanical properties of individual samples could be captured with good-to-excellent accuracy (mean R² [square of Pearson's correlation coefficient]: 0.966, range [min, max]: 0.904, 0.993; mean Ω [relative approximated error]: 33%, range [min, max]: 20%, 47%). Thus, advanced qMRI techniques may be complemented by the developed computational model of cartilage to comprehensively evaluate the functional dimension of non-invasively obtained imaging biomarkers. Thereby, cartilage degeneration can be perspectively evaluated in the context of imaging and biomechanics.

Detection of Early-Stage Degeneration in Human Articular Cartilage by Multiparametric MR Imaging Mapping of Tissue Functionality

To assess human articular cartilage tissue functionality by serial multiparametric quantitative MRI (qMRI) mapping as a function of histological degeneration. Forty-nine cartilage samples obtained during total knee replacement surgeries were placed in a standardized artificial knee joint within an MRI-compatible compressive loading device and imaged in situ and at three loading positions, i.e. unloaded, at 2.5 mm displacement (20% body weight [BW]) and at 5 mm displacement (110% BW). Using a clinical 3.0 T MRI system (Achieva, Philips), serial T1, T1ρ, T2 and T2* maps were generated for each sample and loading position. Histology (Mankin scoring) and biomechanics (Young’s modulus) served as references. Samples were dichotomized as intact (int, n = 27) or early degenerative (deg, n = 22) based on histology and analyzed using repeated-measures ANOVA and unpaired Student’s t-tests after log-transformation. For T1ρ, T2 and T2*, significant loading-induced differences were found in deg (in contrast to int) samples, while for T1 significant decreases in all zones were observed, irrespective of degeneration. In conclusion, cartilage functionality may be visualized using serial qMRI parameter mapping and the response-to-loading patterns are associated with histological degeneration. Hence, loading-induced changes in qMRI parameter maps provide promising surrogate parameters of tissue functionality and status in health and disease.