Anisotropy of T2 and T1ρ relaxation time in articular cartilage at 3 T.

PURPOSE: The anisotropy of R2 and R1ρ relaxation rates in articular cartilage contains information about the collagenous structure of the tissue. Here we determine and study the anisotropic and isotropic components of T2 and T1ρ relaxation parameters in articular cartilage with a clinical 3T MRI device. Furthermore, a visual representation of the topographical variation in anisotropy is given via anisotropy mapping. METHODS: Eight bovine stifle joints were imaged at 22 orientations with respect to the main magnetic field using T2, continuous-wave (CW) T1ρ, and adiabatic T1ρ mapping sequences. Relaxation rates were separated into isotropic and anisotropic relaxation components using a previously established relaxation anisotropy model. Pixel-wise anisotropy values were determined from the relaxation-time maps using Michelson contrast. RESULTS: The relaxation rates obtained from the samples displayed notable variation depending on the sample orientation, magnetization preparation, and cartilage layer. R2 demonstrated significant anisotropy, whereas CW-R1ρ (300 Hz) and CW-R1ρ (500 Hz) displayed a low degree of anisotropy. Adiabatic R1ρ was largely isotropic. In the deep cartilage regions, relaxation rates were generally faster and more anisotropic than in the cartilage closer to the tissue surface. The isotropic relaxation rate components were found to have similar values regardless of measurement sequence. CONCLUSIONS: The fitted relaxation model for T2 and T1ρ demonstrated varying amounts anisotropy, depending on magnetization preparation, and studied the articular cartilage layer. Anisotropy mapping of full joints showed varying amounts of anisotropy depending on the quantitative MRI parameter and topographical location, and in the case of T2, showed systematic changes in anisotropy across cartilage depth.

Non-invasive assessment and visualization of Phytophthora cactorum infection in strawberry crowns using quantitative magnetic resonance imaging.

Phytophthora cactorum is an oomycete species that causes enormous losses on horticultural crops, including strawberries. The purpose of this work was to investigate the alterations caused by P. cactorum inoculation in hydroponically grown strawberry plantlets (Fragaria × ananassa Duch.) using quantitative magnetic resonance imaging (qMRI). It was observed that with MRI, spatial and temporal progression of the infection could be observed in the crown using quantitative MR parameters, namely relaxation time maps. Relaxation times are numeric subject-specific properties that describe the MR signal behavior in an examined anatomical region. Elevated [Formula: see text] relaxation time values were observed inside the infected plant crowns with respect to the healthy references. The [Formula: see text] and [Formula: see text] values of healthy plants were small in the crown region and further diminished during the development of the plant. Furthermore, elevated [Formula: see text] relaxation time values were seen in regions where P. cactorum progression was observed in corresponding plant dissection photographs. Quantitative susceptibility maps (QSM) were calculated to estimate the local magnetic field inhomogeneities. The QSM suggests magnetic susceptibility differences near the center of the pith. This study provides novel non-invasive information on the structure and development of strawberry plants and the effects caused by the P. cactorum infection.

Epiphyseal cartilage vascular architecture at the distal humeral osteochondritis dissecans predilection site in juvenile pigs.

Failure of endochondral ossification due to interruption of the vascular supply to the epiphyseal cartilage is a critical step in the development of osteochondritis dissecans (OCD). Herein we describe the vascular architecture of the distal humeral epiphyseal cartilage in pigs and identify characteristic features that have been associated with sites predisposed to OCD development across species. Distal humeral specimens were harvested from pigs (n = 5, ages = 1, 10, 18, 30, and, 42 days old) and imaged at 9.4T magnetic resonance imaging (MRI) using a 3D gradient recalled echo sequence. The MRI data were processed using a quantitative susceptibility mapping (QSM) pipeline to visualize the vascular architecture. Specimens were also evaluated histologically to identify the presence of ischemic epiphyseal cartilage necrosis (osteochondrosis [OC]-latens) and associated failure of endochondral ossification (OC-manifesta). The QSM data enabled visualization of two distinct vascular beds arising from the perichondrium at the lateral and medial aspects of the distal humeral epiphysis. Elongated vessels originating from these beds coursed axially to supply the lateral and medial thirds of epiphyseal cartilage. At 18 days of age and older, a shift from perichondrial to transosseous blood supply was noted axially, which appeared more pronounced on the lateral side. This shift coincided with histologic identification of OC-latens (30- and 42-day-old specimens) and OC-manifesta (18- and 42-day-old specimens) lesions in the corresponding regions. The vascular anatomy and its evolution at the distal humeral epiphysis closely resembles that previously reported at predilection sites of knee OCD, suggesting a shared pathophysiology between the knee and elbow joints.

Fast Compressed Sensing of 3D Radial T1 Mapping with Different Sparse and Low-Rank Models.

Knowledge of the relative performance of the well-known sparse and low-rank compressed sensing models with 3D radial quantitative magnetic resonance imaging acquisitions is limited. We use 3D radial T1 relaxation time mapping data to compare the total variation, low-rank, and Huber penalty function approaches to regularization to provide insights into the relative performance of these image reconstruction models. Simulation and ex vivo specimen data were used to determine the best compressed sensing model as measured by normalized root mean squared error and structural similarity index. The large-scale compressed sensing models were solved by combining a GPU implementation of a preconditioned primal-dual proximal splitting algorithm to provide high-quality T1 maps within a feasible computation time. The model combining spatial total variation and locally low-rank regularization yielded the best performance, followed closely by the model combining spatial and contrast dimension total variation. Computation times ranged from 2 to 113 min, with the low-rank approaches taking the most time. The differences between the compressed sensing models are not necessarily large, but the overall performance is heavily dependent on the imaged object.

Axon fiber orientation as the source of T1 relaxation anisotropy in white matter: A study on corpus callosum in vivo and ex vivo.

PURPOSE: Recent studies indicate that T1 in white matter (WM) is influenced by fiber orientation in B0 . The purpose of the study was to investigate the interrelationships between axon fiber orientation in corpus callosum (CC) and T1 relaxation time in humans in vivo as well as in rat brain ex vivo. METHODS: Volunteers were scanned for relaxometric and diffusion MRI at 3 T and 7 T. Angular T1 plots from WM were computed using fractional anisotropy and fiber-to-field-angle maps. T1 and fiber-to-field angle were measured in five sections of CC to estimate the effects of inherently varying fiber orientations on T1 within the same tracts in vivo. Ex vivo rat-brain preparation encompassing posterior CC was rotated in B0 and T1 , and diffusion MRI images acquired at 9.4 T. T1 angular plots were determined at several rotation angles in B0 . RESULTS: Angular T1 plots from global WM provided reference for estimated fiber orientation-linked T1 changes within CC. In anterior midbody of CC in vivo, where small axons are dominantly present, a shift in axon orientation is accompanied by a change in T1 , matching that estimated from WM T1 data. In CC, where large and giant axons are numerous, the measured T1 change is about 2-fold greater than the estimated one. Ex vivo rotation of the same midsagittal CC region of interest produced angular T1 plots at 9.4 T, matching those observed at 7 T in vivo. CONCLUSION: These data causally link axon fiber orientation in B0 to the T1 relaxation anisotropy in WM.

3D T1 relaxation time measurements in an equine model of subtle post-traumatic osteoarthritis using MB-SWIFT.

The aim of this study is to assess whether articular cartilage changes in an equine model of post-traumatic osteoarthritis (PTOA), induced by surgical creation of standard (blunt) grooves, and very subtle sharp grooves, could be detected with ex vivo T1 relaxation time mapping utilizing three-dimensional (3D) readout sequence with zero echo time. Grooves were made on the articular surfaces of the middle carpal and radiocarpal joints of nine mature Shetland ponies and osteochondral samples were harvested at 39 weeks after being euthanized under respective ethical permissions. T1 relaxation times of the samples (n = 8 + 8 for experimental and n = 12 for contralateral controls) were measured with a variable flip angle 3D multiband-sweep imaging with Fourier transform sequence. Equilibrium and instantaneous Young's moduli and proteoglycan (PG) content from OD of Safranin-O-stained histological sections were measured and utilized as reference parameters for the T1 relaxation times. T1 relaxation time was significantly (p < 0.05) increased in both groove areas, particularly in the blunt grooves, compared with control samples, with the largest changes observed in the superficial half of the cartilage. T1 relaxation times correlated weakly (Rs ≈ 0.33) with equilibrium modulus and PG content (Rs ≈ 0.21). T1 relaxation time in the superficial articular cartilage is sensitive to changes induced by the blunt grooves but not to the much subtler sharp grooves, at the 39-week timepoint post-injury. These findings support that T1 relaxation time has potential in detection of mild PTOA, albeit the most subtle changes could not be detected.

T2orientation anisotropy mapping of articular cartilage using qMRI.

Objective.To provide orientation-independent MR parameters potentially sensitive to articular cartilage degeneration by measuring isotropic and anisotropic components ofT2relaxation, as well as 3D fiber orientation angle and anisotropy via multi-orientation MR scans.Approach. Seven bovine osteochondral plugs were scanned with a high angular resolution of thirty-seven orientations spanning 180° at 9.4 T. The obtained data was fitted to the magic angle model of anisotropicT2relaxation to produce pixel-wise maps of the parameters of interest. Quantitative Polarized Light Microscopy (qPLM) was used as a reference method for the anisotropy and fiber orientation.Main results. The number of scanned orientations was found to be sufficient for estimating both fiber orientation and anisotropy maps. The relaxation anisotropy maps demonstrated a high correspondence with qPLM reference measurements of the collagen anisotropy of the samples. The scans also enabled calculating orientation-independentT2maps. Little spatial variation was observed in the isotropic component ofT2while the anisotropic component was much faster in the deep radial zone of cartilage. The estimated fiber orientation spanned the expected 0°-90° in samples that had a sufficiently thick superficial layer. The orientation-independent magnetic resonance imaging (MRI) measures can potentially reflect the true properties of articular cartilage more precisely and robustly.Significance. The methods presented in this study will likely improve the specificity of cartilage qMRI by allowing the assessment of the physical properties such as orientation and anisotropy of collagen fibers in articular cartilage.

Correction: A musculoskeletal finite element model of rat knee joint for evaluating cartilage biomechanics during gait.

[This corrects the article DOI: 10.1371/journal.pcbi.1009398.].

Assessing post-traumatic changes in cartilage using T1ρ dispersion parameters.

Degeneration of cartilage can be studied non-invasively with quantitative MRI. A promising parameter for detecting early osteoarthritis in articular cartilage is T1ρ, which can be tuned via the amplitude of the spin-lock pulse. By measuring T1ρ at several spin-lock amplitudes, the dispersion of T1ρ is obtained. The aim of this study is to find out if the dispersion contains diagnostically relevant information complementary to a T1ρ measurement at a single spin-lock amplitude. To this end, five differently acquired dispersion parameters are utilized; A, B, τc, T1ρ/T2, and R2 - R1ρ. An open dataset of an equine model of post-traumatic cartilage was utilized to assess the T1ρ dispersion parameters for the evaluation of cartilage degeneration. Firstly, the parameters were compared for their sensitivity in detecting degenerative changes. Secondly, the relationship of the dispersion parameters to histological and biomechanical reference parameters was studied. Parameters A, T1ρ/T2, and R2 - R1ρ were found to be sensitive to lesion-induced changes in the cartilage within sample. Strong correlations of several dispersion parameters with optical density, as well as with collagen fibril angle were found. Most of the dispersion parameters correlated strongly with individual T1ρ values. The results suggest that dispersion parameters can in some cases provide a more accurate description of the biochemical composition of cartilage as compared to conventional MRI parameters. However, in most cases the information given by the dispersion parameters is more of a refinement than complementary to conventional quantitative MRI.

Deep-Learning-Based Contrast Synthesis From MRF Parameter Maps in the Knee Joint.

BACKGROUND: Magnetic resonance fingerprinting (MRF) is a method to speed up acquisition of quantitative MRI data. However, MRF does not usually produce contrast-weighted images that are required by radiologists, limiting reachable total scan time improvement. Contrast synthesis from MRF could significantly decrease the imaging time. PURPOSE: To improve clinical utility of MRF by synthesizing contrast-weighted MR images from the quantitative data provided by MRF, using U-nets that were trained for the synthesis task utilizing L1- and perceptual loss functions, and their combinations. STUDY TYPE: Retrospective. POPULATION: Knee joint MRI data from 184 subjects from Northern Finland 1986 Birth Cohort (ages 33-35, gender distribution not available). FIELD STRENGTH AND SEQUENCE: A 3 T, multislice-MRF, proton density (PD)-weighted 3D-SPACE (sampling perfection with application optimized contrasts using different flip angle evolution), fat-saturated T2-weighted 3D-space, water-excited double echo steady state (DESS). ASSESSMENT: Data were divided into training, validation, test, and radiologist's assessment sets in the following way: 136 subjects to training, 3 for validation, 3 for testing, and 42 for radiologist's assessment. The synthetic and target images were evaluated using 5-point Likert scale by two musculoskeletal radiologists blinded and with quantitative error metrics. STATISTICAL TESTS: Friedman's test accompanied with post hoc Wilcoxon signed-rank test and intraclass correlation coefficient. The statistical cutoff P <0.05 adjusted by Bonferroni correction as necessary was utilized. RESULTS: The networks trained in the study could synthesize conventional images with high image quality (Likert scores 3-4 on a 5-point scale). Qualitatively, the best synthetic images were produced with combination of L1- and perceptual loss functions and perceptual loss alone, while L1-loss alone led to significantly poorer image quality (Likert scores below 3). The interreader and intrareader agreement were high (0.80 and 0.92, respectively) and significant. However, quantitative image quality metrics indicated best performance for the pure L1-loss. DATA CONCLUSION: Synthesizing high-quality contrast-weighted images from MRF data using deep learning is feasible. However, more studies are needed to validate the diagnostic accuracy of these synthetic images. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 1.

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 T1ρ and T2ρ , continuous-wave T1ρ and relaxation along a fictitious field (TRAFF ) 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.

New methods for robust continuous wave T1ρ relaxation preparation.

Measurement of the longitudinal relaxation time in the rotating frame of reference (T1ρ ) is sensitive to the fidelity of the main imaging magnetic field (B0 ) and that of the RF pulse (B1 ). The purpose of this study was to introduce methods for producing continuous wave (CW) T1ρ contrast with improved robustness against field inhomogeneities and to compare the sensitivities of several existing and the novel T1ρ contrast generation methods with the B0 and B1 field inhomogeneities. Four hard-pulse and four adiabatic CW-T1ρ magnetization preparations were investigated. Bloch simulations and experimental measurements at different spin-lock amplitudes under ideal and non-ideal conditions, as well as theoretical analysis of the hard-pulse preparations, were conducted to assess the sensitivity of the methods to field inhomogeneities, at low (ω1 << ΔB0 ) and high (ω1 >> ΔB0 ) spin-locking field strengths. In simulations, previously reported single-refocus and new triple-refocus hard-pulse and double-refocus adiabatic preparation schemes were found to be the most robust. The mean normalized absolute deviation between the experimentally measured relaxation times under ideal and non-ideal conditions was found to be smallest for the refocused preparation schemes and broadly in agreement with the sensitivities observed in simulations. Experimentally, all refocused preparations performed better than those that were non-refocused. The findings promote the use of the previously reported hard-pulse single-refocus ΔB0 and B1 insensitive T1ρ as a robust method with minimal RF energy deposition. The double-refocus adiabatic B1 insensitive rotation-4 CW-T1ρ preparation offers further improved insensitivity to field variations, but because of the extra RF deposition, may be preferred for ex vivo applications.

Relaxation anisotropy of quantitative MRI parameters in biological tissues.

Quantitative MR relaxation parameters vary in the sensitivity to the orientation of the tissue in the magnetic field. In this study, the orientation dependence of multiple relaxation parameters was assessed in various tissues. Ex vivo samples of each tissue type were prepared either from bovine knee (tendon, cartilage) or mouse (brain, spinal cord, heart, kidney), and imaged at 9.4 T MRI with T1, T2, continuous wave (CW-) T1ρ, adiabatic T1ρ and T2ρ, and Relaxation along fictitious field (RAFF2-4) sequences at five different orientations with respect to the main magnetic field. Relaxation anisotropy of the measured parameters was quantified and compared. The highly ordered collagenous tissues, i.e. cartilage and tendon, presented the highest relaxation anisotropy for T2, CW-T1ρ with spin-lock power < 1 kHz, Ad-T2ρ and RAFF2-4. Maximally anisotropy was 75% in cartilage and 30% in tendon. T1 and adiabatic T1ρ did not exhibit observable anisotropy. In the other measured tissue types, anisotropy was overall less than 10% for all the parameters. The results confirm that highly ordered collagenous tissues have properties that induce very clearly observable relaxation anisotropy, whereas in other tissues the effect is not as prominent. Quantitative comparison of anisotropy of different relaxation parameters highlights the importance of sequence choice and design in MR imaging.

Embedded Quantitative MRI T1ρ Mapping Using Non-Linear Primal-Dual Proximal Splitting.

Quantitative MRI (qMRI) methods allow reducing the subjectivity of clinical MRI by providing numerical values on which diagnostic assessment or predictions of tissue properties can be based. However, qMRI measurements typically take more time than anatomical imaging due to requiring multiple measurements with varying contrasts for, e.g., relaxation time mapping. To reduce the scanning time, undersampled data may be combined with compressed sensing (CS) reconstruction techniques. Typical CS reconstructions first reconstruct a complex-valued set of images corresponding to the varying contrasts, followed by a non-linear signal model fit to obtain the parameter maps. We propose a direct, embedded reconstruction method for T1ρ mapping. The proposed method capitalizes on a known signal model to directly reconstruct the desired parameter map using a non-linear optimization model. The proposed reconstruction method also allows directly regularizing the parameter map of interest and greatly reduces the number of unknowns in the reconstruction, which are key factors in the performance of the reconstruction method. We test the proposed model using simulated radially sampled data from a 2D phantom and 2D cartesian ex vivo measurements of a mouse kidney specimen. We compare the embedded reconstruction model to two CS reconstruction models and in the cartesian test case also the direct inverse fast Fourier transform. The T1ρ RMSE of the embedded reconstructions was reduced by 37-76% compared to the CS reconstructions when using undersampled simulated data with the reduction growing with larger acceleration factors. The proposed, embedded model outperformed the reference methods on the experimental test case as well, especially providing robustness with higher acceleration factors.

A musculoskeletal finite element model of rat knee joint for evaluating cartilage biomechanics during gait.

Abnormal loading of the knee due to injuries or obesity is thought to contribute to the development of osteoarthritis (OA). Small animal models have been used for studying OA progression mechanisms. However, numerical models to study cartilage responses under dynamic loading in preclinical animal models have not been developed. Here we present a musculoskeletal finite element model of a rat knee joint to evaluate cartilage biomechanical responses during a gait cycle. The rat knee joint geometries were obtained from a 3-D MRI dataset and the boundary conditions regarding loading in the joint were extracted from a musculoskeletal model of the rat hindlimb. The fibril-reinforced poroelastic (FRPE) properties of the rat cartilage were derived from data of mechanical indentation tests. Our numerical results showed the relevance of simulating anatomical and locomotion characteristics in the rat knee joint for estimating tissue responses such as contact pressures, stresses, strains, and fluid pressures. We found that the contact pressure and maximum principal strain were virtually constant in the medial compartment whereas they showed the highest values at the beginning of the gait cycle in the lateral compartment. Furthermore, we found that the maximum principal stress increased during the stance phase of gait, with the greatest values at midstance. We anticipate that our approach serves as a first step towards investigating the effects of gait abnormalities on the adaptation and degeneration of rat knee joint tissues and could be used to evaluate biomechanically-driven mechanisms of the progression of OA as a consequence of joint injury or obesity.

Dipolar Relaxation of Water Protons in the Vicinity of a Collagen-like Peptide.

Quantitative magnetic resonance imaging is one of the few available methods for noninvasive diagnosis of degenerative changes in articular cartilage. The clinical use of the imaging data is limited by the lack of a clear association between structural changes at the molecular level and the measured magnetic relaxation times. In anisotropic, collagen-containing tissues, such as articular cartilage, the orientation dependency of nuclear magnetic relaxation can obscure the content of the images. Conversely, if the molecular origin of the phenomenon would be better understood, it would provide opportunities for diagnostics as well as treatment planning of degenerative changes in these tissues. We study the magnitude and orientation dependence of the nuclear magnetic relaxation due to dipole-dipole coupling of water protons in anisotropic, collagenous structures. The water-collagen interactions are modeled with molecular dynamics simulations of a small collagen-like peptide dissolved in water. We find that in the vicinity of the collagen-like peptide, the dipolar relaxation of water hydrogen nuclei is anisotropic, which can result in orientation-dependent relaxation times if the water remains close to the peptide. However, the orientation-dependency of the relaxation is different from the commonly observed magic-angle phenomenon in articular cartilage MRI.

Dual-contrast computed tomography enables detection of equine posttraumatic osteoarthritis in vitro.

To prevent the progression of posttraumatic osteoarthritis, assessment of cartilage composition is critical for effective treatment planning. Posttraumatic changes include proteoglycan (PG) loss and elevated water content. Quantitative dual-energy computed tomography (QDECT) provides a means to diagnose these changes. Here, we determine the potential of QDECT to evaluate tissue quality surrounding cartilage lesions in an equine model, hypothesizing that QDECT allows detection of posttraumatic degeneration by providing quantitative information on PG and water contents based on the partitions of cationic and nonionic agents in a contrast mixture. Posttraumatic osteoarthritic samples were obtained from a cartilage repair study in which full-thickness chondral defects were created surgically in both stifles of seven Shetland ponies. Control samples were collected from three nonoperated ponies. The experimental (n = 14) and control samples (n = 6) were immersed in the contrast agent mixture and the distributions of the agents were determined at various diffusion time points. As a reference, equilibrium moduli, dynamic moduli, and PG content were measured. Significant differences (p < 0.05) in partitions between the experimental and control samples were demonstrated with cationic contrast agent at 30 min, 60 min, and 20 h, and with non-ionic agent at 60 and 120 min. Significant Spearman's rank correlations were obtained at 20 and 24 h (ρ = 0.482-0.693) between the partition of cationic contrast agent, cartilage biomechanical properties, and PG content. QDECT enables evaluation of posttraumatic changes surrounding a lesion and quantification of PG content, thus advancing the diagnostics of the extent and severity of cartilage injuries.

Subject-specific biomechanical analysis to estimate locations susceptible to osteoarthritis-Finite element modeling and MRI follow-up of ACL reconstructed patients.

The aims of this case-control study were to: (1) Identify cartilage locations and volumes at risk of osteoarthritis (OA) using subject-specific finite element (FE) models; (2) Quantify the relationships between the simulated biomechanical parameters and T2 and T1ρ relaxation times of magnetic resonance imaging (MRI). We created subject-specific FE models for seven patients with anterior cruciate ligament (ACL) reconstruction and six controls based on a previous proof-of-concept study. We identified locations and cartilage volumes susceptible to OA, based on maximum principal stresses and absolute maximum shear strains in cartilage exceeding thresholds of 7 MPa and 32%, respectively. The locations and volumes susceptible to OA were compared qualitatively and quantitatively against 2-year longitudinal changes in T2 and T1ρ relaxation times. The degeneration volumes predicted by the FE models, based on excessive maximum principal stresses, were significantly correlated (r = 0.711, p < 0.001) with the degeneration volumes determined from T2 relaxation times. There was also a significant correlation between the predicted stress values and changes in T2 relaxation time (r = 0.649, p < 0.001). Absolute maximum shear strains and changes in T1ρ relaxation time were not significantly correlated. Five out of seven patients with ACL reconstruction showed excessive maximum principal stresses in either one or both tibial cartilage compartments, in agreement with follow-up information from MRI. Expectedly, for controls, the FE models and follow-up information showed no degenerative signs. Our results suggest that the presented modelling methodology could be applied to prospectively identify ACL reconstructed patients at risk of biomechanically driven OA, particularly by the analysis of maximum principal stresses of cartilage.

Functional and structural properties of human patellar articular cartilage in osteoarthritis.

Changes in the fibril-reinforced poroelastic (FRPE) mechanical material parameters of human patellar cartilage at different stages of osteoarthritis (OA) are not known. Further, the patellofemoral joint loading is thought to include more sliding and shear compared to other knee joint locations, thus, the relations between structural and functional changes may differ in OA. Thus, our aim was to determine the patellar cartilage FRPE properties followed by associating them with the structure and composition. Osteochondral plugs (n = 14) were harvested from the patellae of six cadavers. Then, the FRPE material properties were determined, and those properties were associated with proteoglycan content, collagen fibril orientation angle, optical retardation (fibril parallelism), and the state of OA of the samples. The initial fibril network modulus and permeability strain-dependency factor were 72% and 63% smaller in advanced OA samples when compared to early OA samples. Further, we observed a negative association between the initial fibril network modulus and optical retardation (r = -0.537, p < 0.05). We also observed positive associations between 1) the initial permeability and optical retardation (r = 0.547, p < 0.05), and 2) the initial fibril network modulus and optical density (r = 0.670, p < 0.01).These results suggest that the reduced pretension of the collagen fibrils, as shown by the reduced initial fibril network modulus, is linked with the loss of proteoglycans and cartilage swelling in human patellofemoral OA. The characterization of these changes is important to improve the representativeness of knee joint models in tissue and cell scale.