T2 MR imaging vs. computational modeling of human articular cartilage tissue functionality

Quantitative MRI methods for the assessment of structure, composition, and function of musculoskeletal tissues in basic research and preclinical applications

Osteoarthritis (OA) is a disabling chronic disease involving the gradual degradation of joint structures causing pain and dysfunction. Magnetic resonance imaging (MRI) has been widely used as a non-invasive tool for assessing OA-related changes. While anatomical MRI is limited to the morphological assessment of the joint structures, quantitative MRI (qMRI) allows for the measurement of biophysical properties of the tissues at the molecular level. Quantitative MRI techniques have been employed to characterize tissues' structural integrity, biochemical content, and mechanical properties. Their applications extend to studying degenerative alterations, early OA detection, and evaluating therapeutic intervention. This article is a review of qMRI techniques for musculoskeletal tissue evaluation, with a particular emphasis on articular cartilage. The goal is to describe the underlying mechanism and primary limitations of the qMRI parameters, their association with the tissue physiological properties and their potential in detecting tissue degeneration leading to the development of OA with a primary focus on basic and preclinical research studies. Additionally, the review highlights some clinical applications of qMRI, discussing the role of texture-based radiomics and machine learning in advancing OA research.

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.

[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.

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.

Application of quantitative T1, T2 and T2* mapping magnetic resonance imaging in cartilage degeneration of the shoulder joint

To investigate and compare the values of 3.0 T MRI T1, T2 and T2* mapping quantification techniques in evaluating cartilage degeneration of the shoulder joint. This study included 123 shoulder joints of 119 patients, which were scanned in 3.0 T MRI with axial Fat Suppression Proton Density Weighted Image (FS-PDWI), sagittal fat suppression T2 Weighted Image (FS-T2WI), coronal T1Weighted Image (T1WI), FS-PDWI, cartilage-specific T1, T2 and T2* mapping sequences. Basing on MRI images, the shoulder cartilage was classified into grades 0 1, 2, 3 and 4 according to the International Cartilage Regeneration & Joint Preservation Society (ICRS). The grading of shoulder cartilage was based on MRI images with ICRS as reference, and did not involve arthroscopy or histology.The T1, T2 and T2* relaxation values in the superior, middle and inferior bands of shoulder articular cartilage were measured at all grades, and the differences in various indicators between groups were analyzed and compared using a single-factor ANOVA test. The correlation between T1, T2 and T2* relaxation values and MRI-based grading was analyzed by SPSS software. There were 46 shoulder joints with MRI-based grade 0 in healthy control group (n = 46), while 49 and 28 shoulder joints with grade 1-2 (mild degeneration subgroup) and grade 3-4 (severe degeneration subgroup) in patient group (n = 73), accounting for 63.6% and 36.4%, respectively. The T1, T2 and T2* relaxation values of the superior, middle and inferior bands of shoulder articular cartilage were significantly and positively correlated with the MRI-based grading (P < 0.01). MRI-basedgrading of shoulder cartilage was markedly associated with age (r = 0.766, P < 0.01). With the aggravation of cartilage degeneration, T1, T2 and T2* relaxation values showed an upward trend (all P < 0.01), and T1, T2 and T2* mapping could distinguish cartilage degeneration at all levels (all P < 0.01). The T1, T2 and T2* relaxation values were significantly different between normal group and mild degeneration subgroup, normal group and severe degeneration subgroup, mild degeneration subgroup and severe degeneration subgroup (all P < 0.05). Quantitative T1, T2 and T2* mapping can quantify the degree of shoulder cartilage degeneration. All these MRI mapping quantification techniques can be used as critical supplementary sequences to assess shoulder cartilage degeneration, among which T2 mapping has the highest value.

Fast, Accurate, and Robust T2 Mapping of Articular Cartilage by Neural Networks

For T2 mapping, the underlying mono-exponential signal decay is traditionally quantified by non-linear Least-Squares Estimation (LSE) curve fitting, which is prone to outliers and computationally expensive. This study aimed to validate a fully connected neural network (NN) to estimate T2 relaxation times and to assess its performance versus LSE fitting methods. To this end, the NN was trained and tested in silico on a synthetic dataset of 75 million signal decays. Its quantification error was comparatively evaluated against three LSE methods, i.e., traditional methods without any modification, with an offset, and one with noise correction. Following in-situ acquisition of T2 maps in seven human cadaveric knee joint specimens at high and low signal-to-noise ratios, the NN and LSE methods were used to estimate the T2 relaxation times of the manually segmented patellofemoral cartilage. In-silico modeling at low signal-to-noise ratio indicated significantly lower quantification error for the NN (by medians of 6−33%) than for the LSE methods (p < 0.001). These results were confirmed by the in-situ measurements (medians of 10−35%). T2 quantification by the NN took only 4 s, which was faster than the LSE methods (28−43 s). In conclusion, NNs provide fast, accurate, and robust quantification of T2 relaxation times.

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.

Magnetic Resonance Imaging-based biomechanical simulation of cartilage: A systematic review

MRI-based mathematical and computational modeling studies can contribute to a better understanding of the mechanisms governing cartilage's mechanical performance and cartilage disease. In addition, distinct modeling of cartilage is needed to optimize artificial cartilage production. These studies have opened up the prospect of further deepening our understanding of cartilage function. Furthermore, these studies reveal the initiation of an engineering-level approach to how cartilage disease affects material properties and cartilage function. Aimed at researchers in the field of MRI-based cartilage simulation, research articles pertinent to MRI-based cartilage modeling were identified, reviewed, and summarized systematically. Various MRI applications for cartilage modeling are highlighted, and the limitations of different constitutive models used are addressed. In addition, the clinical application of simulations and studied diseases are discussed. The paper's quality, based on the developed questionnaire, was assessed, and out of 79 reviewed papers, 34 papers were determined as high-quality. Due to the lack of the best constitutive models for various clinical conditions, researchers may consider the effect of constitutive material models on the cartilage disease simulation. In the future, research groups may incorporate various aspects of machine learning into constitutive models and MRI data extraction to further refine the study methodology. Moreover, researchers should strive for further reproducibility and rigorous model validation and verification, such as gait analysis.

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.

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 backward pre-stressing algorithm for efficient finite element implementation of in vivo material and geometrical parameters into fibril-reinforced mixture models of articular cartilage

Classical continuum mechanics has been widely used for implementation of the material models of articular cartilage (AC) mainly with the aid of the finite element (FE) method, which, in many cases, considers the stress-free configuration as the initial configuration. On the contrary, the AC experimental tests typically begin with the pre-stressed state of both material and geometrical properties. Indeed, imposing the initial pre-stress onto AC models with the in vivo values as the initial state would result in nonphysiologically expansion of the FE mesh due to the soft nature of AC. This change in the model configuration can also affect the material behavior kinematically in the mixture models of cartilage due to the intrinsic compressibility of the tissue. Although several different fixed-point backward algorithms, as the most straightforward pre-stressing methods, have already been developed to incorporate these initial conditions into FE models iteratively, such methods focused merely on the geometrical parameters, and they omitted the material variations of the anisotropic mixture models of AC. To address this issue, we propose an efficient algorithm generalizing the backward schemes to restore stress-free conditions by optimizing both the involving variables, and we hypothesize that it can affect the results considerably. To this end, a comparative simulation was implemented on an advanced and validated multiphasic model by the new and conventional algorithms. The results are in support of the hypothesis, as in our illustrative general AC model, the material parameters experienced a maximum error of 16% comparing to the initial in vivo data when the older algorithm was employed, and it led to a maximum variation of 44% in the recorded stresses comparing to the results of the new method. We conclude that our methodology enhanced the model fidelity, and it is applicable in most of the existing FE solvers for future mixture studies with accurate stress distributions.

Identifying the imaging correlates of cartilage functionality based on quantitative MRI mapping - The collagenase exposure model

Cartilage functionality is determined by tissue structure and composition. If altered, cartilage is predisposed to premature degeneration. This pathomimetical study of early osteoarthritis evaluated the dose-dependant effects of collagenase-induced collagen disintegration and proteoglycan depletion on cartilage functionality as assessed by serial T1, T1ρ, T2, and T2* mapping under loading. 30 human femoral osteochondral samples underwent imaging on a clinical 3.0 T MRI scanner (Achieva, Philips) in the unloaded reference configuration (δ₀) and under pressure-controlled quasi-static indentation loading to 15.1 N (δ₁) and to 28.6 N (δ₂). Imaging was performed before and after exposure to low (LC, 0.5 mg/mL; n = 10) or high concentration (HC, 1.5 mg/mL; n = 10) of collagenase. Untreated samples served as controls (n = 10). Loading responses were determined for the entire sample and the directly loaded (i.e. sub-pistonal) and bilaterally adjacent (i.e. peri‑pistonal) regions, referenced histologically, quantified as relative changes, and analysed using adequate parametric and non-parametric statistical tests. Dose-dependant surface disintegration and tissue loss were reflected by distinctly different pre- and post-exposure response-to-loading patterns. While T1 generally decreased with loading, regardless of collagenase exposure, T1ρ increased significantly after HC exposure (p = 0.008). Loading-induced decreases in T2 were significant after LC exposure (p = 0.006), while changes in T2* were ambiguous. In conclusion, aberrant loading-induced changes in T2 and T1ρ reflect moderate and severe matrix changes, respectively, and indicate the close interrelatedness of matrix changes and functionality in cartilage.

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.

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.

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.

Linking hyperelastic theoretical models and experimental data of vaginal tissue through histological data

Mechanical characterization of living tissues and computer-based simulations related to medical issues, has become increasingly important to improve diagnostic processes and treatments evaluation. This work proposes a link between the mechanical testing and the material model predictions through histological data of vaginal tissue. Histological data was used to link tensile testing experiments with material-dependent parameters; the approach was adequate to capture the nonlinear response of ovine vaginal tissue over a large strain range. The experimental data obtained on a previous study, has two main components: tensile testing and histological analysis of the ovine vaginal tissue. Uniaxial tensile test data and histological data were collected from three sheep groups: virgins, pregnant and parous. The distal part of vaginal wall was selected since it is prone to tears induced by vaginal delivery. The HGO (Holzapfel-Gasser-Ogden) model parameters were fitted using a stochastic approach, namely the Simple Genetic Algorithm (SGA). The SGA was able to fit the experimental data successfully (R² > 0.986). The dimensionless coefficient ξ, was highly correlated with histological data. The ratio was seen to increase linearly with increasing collagen content. Coefficient ξ brings a new way of interpreting and understanding experimental data; it connects the nonlinear mechanical behaviour (tensile test) with tissue's morphology (histology). It can be used as an 'inverse' (approximate) method to estimate the mechanical properties without direct experimental measurements, through basic histology. In this context, the proposed methodology appears very promising in estimating the response of the tissue via histological information.

Cartilage-on-cartilage contact: effect of compressive loading on tissue deformations and structural integrity of bovine articular cartilage

OBJECTIVE

This study aims to characterize the deformations in articular cartilage under compressive loading and link these to changes in the extracellular matrix constituents described by magnetic resonance imaging (MRI) relaxation times in an experimental model mimicking in vivo cartilage-on-cartilage contact.

DESIGN

Quantitative MRI images, T₁, T₂ and T_1ρ relaxation times, were acquired at 9.4T from bovine femoral osteochondral explants before and immediately after loading. Two-dimensional intra-tissue displacement and strain fields under cyclic compressive loading (350N) were measured using the displacement encoding with stimulated echoes (DENSE) method. Changes in relaxation times in response to loading were evaluated against the deformation fields.

RESULTS

Deformation fields showed consistent patterns among all specimens, with maximal strains at the articular surface that decrease with tissue depth. Axial and transverse strains were maximal around the center of the contact region, whereas shear strains were minimal around the contact center but increased towards contact edges. A decrease in T₂ and T_1ρ was observed immediately after loading whereas the opposite was observed for T₁. No correlations between cartilage deformation patterns and changes in relaxation times were observed.

CONCLUSIONS

Displacement encoding combined with relaxometry by MRI can noninvasively monitor the cartilage biomechanical and biochemical properties associated with loading. The deformation fields reveal complex patterns reflecting the depth-dependent mechanical properties, but intra-tissue deformation under compressive loading does not correlate with structural and compositional changes. The compacting effect of cyclic compression on the cartilage tissue was revealed by the change in relaxation time immediately after loading.

Functional assessment of strains around a full-thickness and critical sized articular cartilage defect under compressive loading using MRI

OBJECTIVE

The objective of this study was to evaluate the effect of full-thickness chondral defects on intratissue deformation patterns and matrix constituents in an experimental model mimicking in vivo cartilage-on-cartilage contact conditions.

DESIGN

Pairs of bovine osteochondral explants, in a unique cartilage-on-cartilage model system, were compressed uniaxially by 350 N during 2 s loading and 1.4 s unloading cycles (≈1700 repetitions). Tissue deformations under quasi-steady state load deformation response were measured with displacement encoded imaging with stimulated echoes (DENSE) in a 9.4 T magnetic resonance imaging (MRI) scanner. Pre- and post-loading, T₁, T₂ and T_1ρ relaxation time maps were measured. We analyzed differences in strain patterns and relaxation times between intact cartilage (n = 8) and cartilage in which a full-thickness and critical sized defect was created (n = 8).

RESULTS

Under compressive loading, strain magnitudes were elevated at the defect rim, with elevated tensile and compressive principal strains (Δϵ_max = 4.2%, P = 0.02; Δϵ_min = -4.3%, P = 0.02) and maximum shear strain at the defect rim (Δγ_max = 4.4%, P = 0.007). The opposing cartilage showed minimal increase in strain patterns at contact with the defect rim but decreased strains opposing the defect. After defect creation, T₁, T₂ and T_1ρ relaxation times were elevated at the defect rim only. Following loading, the overall relaxations times of the defect tissue and especially at the rim, increased compared to intact cartilage.

CONCLUSIONS

This study demonstrates that the local biomechanical changes occurring after defect creation may induce tissue damage by increasing shear strains and depletion of cartilage constituents at the defect rim under compressive loading.

Biologic canine and human intervertebral disc repair by notochordal cell-derived matrix: from bench towards bedside

The socioeconomic burden of chronic back pain related to intervertebral disc (IVD) disease is high and current treatments are only symptomatic. Minimally invasive strategies that promote biological IVD repair should address this unmet need. Notochordal cells (NCs) are replaced by chondrocyte-like cells (CLCs) during IVD maturation and degeneration. The regenerative potential of NC-secreted substances on CLCs and mesenchymal stromal cells (MSCs) has already been demonstrated. However, identification of these substances remains elusive. Innovatively, this study exploits the regenerative NC potential by using healthy porcine NC-derived matrix (NCM) and employs the dog as a clinically relevant translational model. NCM increased the glycosaminoglycan and DNA content of human and canine CLC aggregates and facilitated chondrogenic differentiation of canine MSCs in vitro. Based on these results, NCM, MSCs and NCM+MSCs were injected in mildly (spontaneously) and moderately (induced) degenerated canine IVDs in vivo and, after six months of treatment, were analyzed. NCM injected in moderately (induced) degenerated canine IVDs exerted beneficial effects at the macroscopic and MRI level, induced collagen type II-rich extracellular matrix production, improved the disc height, and ameliorated local inflammation. MSCs exerted no (additive) effects. In conclusion, NCM induced in vivo regenerative effects on degenerated canine IVDs. NCM may, comparable to demineralized bone matrix in bone regeneration, serve as ‘instructive matrix’, by locally releasing growth factors and facilitating tissue repair. Therefore, intradiscal NCM injection could be a promising regenerative treatment for IVD disease, circumventing the cumbersome identification of bioactive NC-secreted substances.

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

Quantitative magnetic resonance imaging (qMRI) is a promising approach to detect early cartilage degeneration. However, there is no consensus on which cartilage component contributes to the tissue's qMRI signal properties. T1, T1ρ, and T2^⁎ maps of cartilage samples (n = 8) were generated on a clinical 3.0-T MRI system. All samples underwent histological assessment to ensure structural integrity. For cross-referencing, a discretized numerical model capturing distinct compositional and structural tissue properties, that is, fluid fraction (FF), proteoglycan (PG) and collagen (CO) content and collagen fiber orientation (CFO), was implemented. In a pixel-wise and region-specific manner (central versus peripheral region), qMRI parameter values and modelled tissue parameters were correlated and quantified in terms of Spearman's correlation coefficient ρs. Significant correlations were found between modelled compositional parameters and T1 and T2^⁎, in particular in the central region (T1: ρs ≥ 0.7 [FF, CFO], ρs ≤ −0.8 [CO, PG]; T2^⁎: ρs ≥ 0.67 [FF, CFO], ρs ≤ −0.71 [CO, PG]). For T1ρ, correlations were considerably weaker and fewer (0.16 ≤ ρs ≤ −0.15). QMRI parameters are characterized in their biophysical properties and their sensitivity and specificity profiles in a basic scientific context. Although none of these is specific towards any particular cartilage constituent, T1 and T2^⁎ reflect actual tissue compositional features more closely than T1ρ.

Fatigue of soft fibrous tissues: Multi-scale mechanics and constitutive modeling

In recent experimental studies a possible damage mechanism of collagenous tissues mainly caused by fatigue was disclosed. In this contribution, a multi-scale constitutive model ranging from the tropocollagen (TC) molecule level up to bundles of collagen fibers is proposed and utilized to predict the elastic and inelastic long-term tissue response. Material failure of collagen fibrils is elucidated by a permanent opening of the triple helical collagen molecule conformation, triggered either by overstretching or reaction kinetics of non-covalent bonds. This kinetics is described within a probabilistic framework of adhesive detachments of molecular linkages providing collagen fiber integrity. Both intramolecular and interfibrillar linkages are considered. The final constitutive equations are validated against recent experimental data available in literature for both uniaxial tension to failure and the evolution of fatigue in subsequent loading cycles. All material parameters of the proposed model have a clear physical interpretation.

STATEMENT OF SIGNIFICANCE

Irreversible changes take place at different length scales of soft fibrous tissues under supra-physiological loading and alter their macroscopic mechanical properties. Understanding the evolution of those histologic pathologies under loading and incorporating them into a continuum mechanical framework appears to be crucial in order to predict long-term evolution of various diseases and to support the development of tissue engineering.

Non-invasive T1ρ mapping of the human cartilage response to loading and unloading

OBJECTIVE

To define the physiological response to sequential loading and unloading in histologically intact human articular cartilage using serial T1ρ mapping, as T1ρ is considered to indicate the tissue's macromolecular content.

METHOD

18 macroscopically intact cartilage-bone samples were obtained from the central lateral femoral condyles of 18 patients undergoing total knee replacement. Serial T1ρ mapping was performed on a clinical 3.0-T MRI system using a modified prostate coil. Spin-lock multiple gradient-echo sequences prior to, during and after standardized indentation loading (displacement controlled, strain 20%) were used to obtain seven serial T1ρ maps: unloaded (δ₀), quasi-statically loaded (indentation₁-indentation₃) and under subsequent relaxation (relaxation₁-relaxation₃). After manual segmentation, zonal and regional regions-of-interest were defined. ROI-specific relative changes were calculated and statistically assessed using paired t-tests. Histological (Mankin classification) and biomechanical (unconfined compression) evaluations served as references.

RESULTS

All samples were histologically and biomechanically grossly intact (Mankin sum: 1.8 ± 1.2; Young's Modulus: 0.7 ± 0.4 MPa). Upon loading, T1ρ consistently increased throughout the entire sample thickness, primarily subpistonally (indentation₁ [M ± SD]: 9.5 ± 7.8% [sub-pistonal area, SPA] vs 4.2 ± 5.8% [peri-pistonal area, PPA]; P < 0.001). T1ρ further increased with ongoing loading (indentation₃: 14.1 ± 8.1 [SPA] vs 7.7 ± 5.9% [PPA]; P < 0.001). Even upon unloading (i.e., relaxation), T1ρ persistently increased in time.

CONCLUSION

Serial T1ρ-mapping reveals distinct and complex zonal and regional changes in articular cartilage as a function of loading and unloading. Thereby, longitudinal adaptive processes in hyaline cartilage become evident, which may be used for the tissue's non-invasive functional characterization by T1ρ.