An MRI-compatible loading device to assess knee joint cartilage deformation: Effect of preloading and inter-test repeatability

In vivo human knee varus-valgus loading apparatus for analysis of MRI-based intratissue strain and relaxometry

The diagnosis of early-stage osteoarthritis remains as an unmet challenge in medicine and a roadblock to evaluating the efficacy of disease-modifying treatments. Recent studies demonstrate that unique patterns of intratissue cartilage deformation under cyclic loading can serve as potential biomarkers to detect early disease pathogenesis. However, a workflow to obtain deformation, strain maps, and quantitative MRI metrics due to the loading of articular cartilage in vivo has not been fully developed. In this study, we characterize and demonstrate an apparatus that is capable of applying a varus-valgus load to the human knee in vivo within an MRI environment to enable the measurement of cartilage structure and mechanical function. The apparatus was first tested in a lab environment, then the functionality and utility of the apparatus were examined during varus loading in a clinical 3T MRI system for human imaging. We found that the device enables quantitative MRI metrics for biomechanics and relaxometry data acquisition during joint loading leading to compression of the medial knee compartment. Integration with spiral DENSE MRI during cyclic loading provided time-dependent displacement and strain maps within the tibiofemoral cartilage. The results from these procedures demonstrate that the performance of this loading apparatus meets the design criteria and enables a simple and practical workflow for future studies of clinical cohorts, and the identification and validation of imaging-based biomechanical biomarkers.

Acute Repair of Meniscus Root Tear Partially Restores Joint Displacements as Measured With Magnetic Resonance Images and Loading in a Cadaveric Porcine Knee

The meniscus serves important load-bearing functions and protects the underlying articular cartilage. Unfortunately, meniscus tears are common and impair the ability of the meniscus to distribute loads, increasing the risk of developing osteoarthritis. Therefore, surgical repair of the meniscus is a frequently performed procedure; however, repair does not always prevent osteoarthritis. This is hypothesized to be due to altered joint loading post-injury and repair, where the functional deficit of the meniscus prevents it from performing its role of distributing forces. The objective of this study was to quantify joint kinematics in an intact joint, after a meniscus root tear, and after suture repair in cadaveric porcine knees, a frequently used in vivo model. We utilized an magnetic resonance images-compatible loading device and novel use of a T1 vibe sequence to measure meniscus and femur displacements under physiological axial loads. We found that anterior root tear led to large meniscus displacements under physiological axial loading and that suture anchor repair reduced these displacements but did not fully restore intact joint kinematics. After tear and repair, the anterior region of the meniscus moved posteriorly and medially as it was forced out of the joint space under loading, while the posterior region had small displacements as the posterior attachment acted as a hinge about which the meniscus pivoted in the axial plane. Methods from this study can be applied to assess altered joint kinematics following human knee injuries and evaluate repair strategies aimed to restore joint kinematics.

Immediate and Delayed Effects of Joint Loading Activities on Knee and Hip Cartilage: A Systematic Review and Meta-analysis

BACKGROUND

The impact of activity-related joint loading on cartilage is not clear. Abnormal loading is considered to be a mechanical driver of osteoarthritis (OA), yet moderate amounts of physical activity and rehabilitation exercise can have positive effects on articular cartilage. Our aim was to investigate the immediate effects of joint loading activities on knee and hip cartilage in healthy adults, as assessed using magnetic resonance imaging. We also investigated delayed effects of activities on healthy cartilage and the effects of activities on cartilage in adults with, or at risk of, OA. We explored the association of sex, age and loading duration with cartilage changes.

METHODS

A systematic review of six databases identified studies assessing change in adult hip and knee cartilage using MRI within 48 h before and after application of a joint loading intervention/activity. Studies included adults with healthy cartilage or those with, or at risk of, OA. Joint loading activities included walking, hopping, cycling, weightbearing knee bends and simulated standing within the scanner. Risk of bias was assessed using the Newcastle-Ottawa Scale. Random-effects meta-analysis estimated the percentage change in compartment-specific cartilage thickness or volume and composition (T2 relaxation time) outcomes. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system evaluated certainty of evidence.

RESULTS

Forty studies of 653 participants were included after screening 5159 retrieved studies. Knee cartilage thickness or volume decreased immediately following all loading activities investigating healthy adults; however, GRADE assessment indicated very low certainty evidence. Patellar cartilage thickness and volume reduced 5.0% (95% CI 3.5, 6.4, I² = 89.3%) after body weight knee bends, and tibial cartilage composition (T2 relaxation time) decreased 5.1% (95% CI 3.7, 6.5, I² = 0.0%) after simulated standing within the scanner. Hip cartilage data were insufficient for pooling. Secondary outcomes synthesised narratively suggest knee cartilage recovers within 30 min of walking and 90 min of 100 knee bends. We found contrasting effects of simulated standing and walking in adults with, or at risk of, OA. An increase of 10 knee bend repetitions was associated with 2% greater reduction in patellar thickness or volume.

CONCLUSION

There is very low certainty evidence that minimal knee cartilage thickness and volume and composition (T2 relaxation time) reductions (0-5%) occur after weightbearing knee bends, simulated standing, walking, hopping/jumping and cycling, and the impact of knee bends may be dose dependent. Our findings provide a framework of cartilage responses to loading in healthy adults which may have utility for clinicians when designing and prescribing rehabilitation programs and providing exercise advice.

Auto-segmentation of the tibia and femur from knee MR images via deep learning and its application to cartilage strain and recovery

The ability to efficiently and reproducibly generate subject-specific 3D models of bone and soft tissue is important to many areas of musculoskeletal research. However, methodologies requiring such models have largely been limited by lengthy manual segmentation times. Recently, machine learning, and more specifically, convolutional neural networks, have shown potential to alleviate this bottleneck in research throughput. Thus, the purpose of this work was to develop a modified version of the convolutional neural network architecture U-Net to automate segmentation of the tibia and femur from double echo steady state knee magnetic resonance (MR) images. Our model was trained on a dataset of over 4,000 MR images from 34 subjects, segmented by three experienced researchers, and reviewed by a musculoskeletal radiologist. For our validation and testing sets, we achieved dice coefficients of 0.985 and 0.984, respectively. As further testing, we applied our trained model to a prior study of tibial cartilage strain and recovery. In this analysis, across all subjects, there were no statistically significant differences in cartilage strain between the machine learning and ground truth bone models, with a mean difference of 0.2 ± 0.7 % (mean ± 95 % confidence interval). This difference is within the measurement resolution of previous cartilage strain studies from our lab using manual segmentation. In summary, we successfully trained, validated, and tested a machine learning model capable of segmenting MR images of the knee, achieving results that are comparable to trained human segmenters.

Acute repair of meniscus root tear partially restores joint displacements as measured with MRI and loading in a porcine knee

The meniscus serves important load-bearing functions and protects the underlying articular cartilage. Unfortunately, meniscus tears are common and impair the ability of the meniscus to distribute loads, greatly increasing the risk for developing osteoarthritis. Therefore, surgical repair of the meniscus is a frequently performed procedure; however, this repair does not always prevent osteoarthritis. This is hypothesized to be due to altered joint loading post injury and repair, where the functional deficit of the meniscus prevents it from performing its role of distributing forces. However, many studies of meniscus function required opening the joint, which alters kinematics. The objective of this study was to use novel MRI methods to image the intact joint under axial load and measure the acute meniscus and femur displacements in an intact joint, after a meniscus root tear, and after suture repair in the porcine knee, a frequently used in vivo model. We found that anterior root tear led to large meniscus and femur displacements under physiological axial loading, and that suture anchor repair reduced these displacements, but did not fully restore intact joint kinematics. After tear and repair, the anterior region of the meniscus moved posteriorly and medially as it was forced out of the joint space under loading, while the posterior region had small displacements as the posterior attachment acted as a hinge about which the meniscus rotated in the axial plane. This technique can be applied to evaluate the effect of knee injuries and to develop improved repair strategies to restore joint kinematics.

Creep-recovery behaviors of articular cartilage under uniaxial and biaxial tensile loadings

Creep deformation in cartilage can be observed under physiological loads in daily activities such as standing, single-leg lunge, the stance phase of gait. If not fully recovered in time, it may induce irreversible damage in cartilage and further lead to early osteoarthritis. In this study, 36 cruciform-shape samples in total from 18 bulls were employed to conduct the uniaxial and biaxial creep-recovery tests by using a biaxial cyclic testing system. Effects of stress level (σ = .5, 1.0, 1.5 MPa) and biaxial stress ratio (B = 0, .3, .5, 1.0) on creep-recovery behaviors of cartilage were characterized. And then, a viscoelastic constitutive model was employed to predict its creep-recovery behaviors. The results showed that the creep strain and its three components, namely instantaneous elastic strain, delayed elastic strain and viscous flow strain, increase with the increasing stress level or with the decreasing biaxial stress ratio. Compared with uniaxial creep-recovery, biaxial creep-recovery exhibits a smaller creep strain, a faster recovery rate of creep strain and a smaller residual strain. Besides, the built viscoelastic model can be used to describe the uniaxial creep-recovery behaviors of cartilage as a good correlation between the fitted results and test results is achieved. The findings are expected to provide new insights into understanding normal joint function and cartilage pathology.

Robust automatic hexahedral cartilage meshing framework enables population-based computational studies of the knee

Osteoarthritis of the knee is increasingly prevalent as our population ages, representing an increasing financial burden, and severely impacting quality of life. The invasiveness of in vivo procedures and the high cost of cadaveric studies has left computational tools uniquely suited to study knee biomechanics. Developments in deep learning have great potential for efficiently generating large-scale datasets to enable researchers to perform population-sized investigations, but the time and effort associated with producing robust hexahedral meshes has been a limiting factor in expanding finite element studies to encompass a population. Here we developed a fully automated pipeline capable of taking magnetic resonance knee images and producing a working finite element simulation. We trained an encoder-decoder convolutional neural network to perform semantic image segmentation on the Imorphics dataset provided through the Osteoarthritis Initiative. The Imorphics dataset contained 176 image sequences with varying levels of cartilage degradation. Starting from an open-source swept-extrusion meshing algorithm, we further developed this algorithm until it could produce high quality meshes for every sequence and we applied a template-mapping procedure to automatically place soft-tissue attachment points. The meshing algorithm produced simulation-ready meshes for all 176 sequences, regardless of the use of provided (manually reconstructed) or predicted (automatically generated) segmentation labels. The average time to mesh all bones and cartilage tissues was less than 2 min per knee on an AMD Ryzen 5600X processor, using a parallel pool of three workers for bone meshing, followed by a pool of four workers meshing the four cartilage tissues. Of the 176 sequences with provided segmentation labels, 86% of the resulting meshes completed a simulated flexion-extension activity. We used a reserved testing dataset of 28 sequences unseen during network training to produce simulations derived from predicted labels. We compared tibiofemoral contact mechanics between manual and automated reconstructions for the 24 pairs of successful finite element simulations from this set, resulting in mean root-mean-squared differences under 20% of their respective min-max norms. In combination with further advancements in deep learning, this framework represents a feasible pipeline to produce population sized finite element studies of the natural knee from subject-specific models.

[Evaluation of a Bone Coordinate System Constructed Using MR Image Composing]

PURPOSE

To evaluate the accuracy of a bone coordinate system constructed using MR image composing.

METHOD

A femoral coordinate system constructed using image composing of MR images of a whole bovine femur was evaluated using CT images. The MR images were acquired by moving the table and were processed with 3D distortion correction and composing. To evaluate the reproducibility of the measurements, the same operator repeated the construction of the femoral coordinate system. In addition, distortions in the MR images were evaluated in comparison with those in the CT images.

RESULT

The center position of the femoral coordinate system constructed using the MR image composing was 1.6±0.9 mm on the X-axis, 1.5±0.8 mm on the Y-axis, and 0.2±0.3 mm on the Z-axis, and the rotation of each axis was 1° or less. The distortion of the composed MR image was about 0.3%.

CONCLUSION

The femoral coordinate system constructed using MR image composing had the same accuracy as a system constructed with CT images. The effect of MR image composing on the construction of the femoral coordinate system was small.

Design and validation of a semi-automatic bone segmentation algorithm from MRI to improve research efficiency

Segmentation of medical images into different tissue types is essential for many advancements in orthopaedic research; however, manual segmentation techniques can be time- and cost-prohibitive. The purpose of this work was to develop a semi-automatic segmentation algorithm that leverages gradients in spatial intensity to isolate the patella bone from magnetic resonance (MR) images of the knee that does not require a training set. The developed algorithm was validated in a sample of four human participants (in vivo) and three porcine stifle joints (ex vivo) using both magnetic resonance imaging (MRI) and computed tomography (CT). We assessed the repeatability (expressed as mean ± standard deviation) of the semi-automatic segmentation technique on: (1) the same MRI scan twice (Dice similarity coefficient = 0.988 ± 0.002; surface distance = − 0.01 ± 0.001 mm), (2) the scan/re-scan repeatability of the segmentation technique (surface distance = − 0.02 ± 0.03 mm), (3) how the semi-automatic segmentation technique compared to manual MRI segmentation (surface distance = − 0.02 ± 0.08 mm), and (4) how the semi-automatic segmentation technique compared when applied to both MRI and CT images of the same specimens (surface distance = − 0.02 ± 0.06 mm). Mean surface distances perpendicular to the cartilage surface were computed between pairs of patellar bone models. Critically, the semi-automatic segmentation algorithm developed in this work reduced segmentation time by approximately 75%. This method is promising for improving research throughput and potentially for use in generating training data for deep learning algorithms.

Detecting Articular Cartilage and Meniscus Deformation Effects Using Magnetization Transfer Ultrashort Echo Time (MT-UTE) Modeling during Mechanical Load Application: Ex Vivo Feasibility Study

OBJECTIVE

Ultrashort echo time (UTE) magnetic resonance imaging (MRI) sequences have improved imaging of short T2 musculoskeletal (MSK) tissues. UTE-MRI combined with magnetization transfer modeling (UTE-MT) has demonstrated robust assessment of MSK tissues. This study aimed to investigate the variation of UTE-MT measures under mechanical loading in tibiofemoral cartilage and meniscus of cadaveric knee joints.

DESIGN

Fourteen knee joints from young (n = 8, 42 ± 12 years old) and elderly (n = 6, 89 ± 4 years old) donors were scanned on a 3-T scanner under 3 loading conditions: load = 300 N (Load1), load = 500 N (Load2), and load = 0 N (Unload). UTE-MT sequences were performed at each loading condition. Macromolecular proton fraction (MMF) was calculated from UTE-MT modeling. Wilcoxon rank sum test was used to examine the MRI data differences between loading conditions.

RESULTS

For young donors, MMF increased in all grouped regions of interest (meniscus [M], femoral articular cartilage [FAC], tibial articular cartilage [TAC], articular cartilage regions covered by meniscus [AC-MC], and articular cartilage regions uncovered by meniscus [AC-UC]) when the load increased from 300 to 500 N. The increases in MMF were significant for M (13.3%, P < 0.01) and AC-MC (9.2%, P = 0.04). MMF decreased in all studied regions after unloading, which was significant only for AC-MC (-8.9%, P = 0.01). For elderly donors, MRI parameters did not show significant changes by loading or unloading.

CONCLUSION

This study highlights the potential of the UTE-MT modeling combined with knee loading in differentiating between normal and abnormal knees. Average tissue deformation effects were likely higher and more uniformly distributed in the joints of young donors compared with elderly donors.

The MRI-based 3D morphologic changes of knee meniscus under knee weight-bearing and early flexion conditions

There are few studies investigate morphologic changes of knee meniscus in vivo mechanical loading and three-dimensions (3D) deformation and displacement of the whole meniscus between in vivo mechanical loading and unloading conditions are still unclear. To investigate the displacements and 3D morphological changes of the menisci under knee weight-bearing and early flexion conditions in healthy adults using a Magnetic Resonance Imaging (MRI)-compatible loading device (a 3.0 T MR imaging system) combined with a newly developed 3D comparison technique. Fifteen healthy volunteers were recruited in this cross-sectional observational study. Each subject underwent MRIs of their dominant right knee in eight different scanning conditions using a 3.0-T MRI scanner with a custom-made MRI-compatible loading device. The knee meniscus images were 3D reconstructed, and dimensional comparisons were made for each meniscal model with baseline (0°-unloaded model). The morphologic changes of the meniscal-anterior horn (AH), body (BD), and posterior horn (PH) regions were expressed as mean positive and negative deviations. The displacements were further investigated, and the meniscal extrusions of different subregions were measured. The morphologic changing patterns of human meniscus under loading and flexions were presented using 3D chromatic maps. The bilateral menisci were generally shifting laterally and posteriorly in most flexion angles and were changing medially and anteriorly under fully extended knee loading conditions. The mean deviations were more significant with loading at 0° of knee flexion, while the PH region in the lateral side changed further posteriorly with loading in 30° flexion. Most of the differences were not significant in other flexion angles between loading conditions. The extrusion of meniscus’s medial body was greater in full extension compared to any other flexing angles. Mechanical loading can significantly deform the menisci in knee extension; however, this effect is limited during knee flexion. Current study can be used as a reference for the evaluations of the integrity in meniscal functions.

Creep behavior of human knee joint determined with high-speed biplanar video-radiography and finite element simulation

Creep and relaxation of knee cartilage and meniscus have been extensively studied at the tissue level with constitutive laws well established. At the joint level, however, both experimental and model studies have been focused on either elastic or kinematic responses of the knee, where the time-dependent response is typically neglected for simplicity. The objectives of this study were to quantify the in-vivo creep behavior of human knee joints produced by the cartilaginous tissues and to use the relevant data to validate a previously proposed poromechanical model. Two participants with no history of leg injury volunteered for 3T magnetic resonance imaging (MRI) of their unloaded right knees and for biplanar video-radiography (BVR) of the same knees during standing on an instrumented treadmill for 10 min. Approximately 550 temporal data points were obtained for the in-vivo displacement of the right femur relative to the tibia of the knee. Models of the bones and soft tissues were derived from the MRI. The bone models were used to reconstruct the 3D bone kinematics measured using BVR. Ground reaction forces were simultaneously recorded for the right leg, which were used as input for the subject-specific finite element knee models. Cartilaginous tissues were modeled as fluid-saturated fibril-reinforced materials. In-vivo creep of the knee was experimentally observed for both participants, i.e., the joint displacement increased with time while the reaction forces at the foot were approximately constant. The creep displacements obtained from the finite element models compared well with the experimental data when the tissue properties were calibrated (Pearson correlation coefficient = 0.99). The results showed the capacity of the poromechanical knee model to capture the creep response of the joint. The combined experimental and model study may be used to understand the fluid-pressure load support and contact mechanics of the joint using material properties calibrated from the displacement data, which enhance the fidelity of model results.

In-Situ Cartilage Functionality Assessment Based on Advanced MRI Techniques and Precise Compartmental Knee Joint Loading through Varus and Valgus Stress

Stress MRI brings together mechanical loading and MRI in the functional assessment of cartilage and meniscus, yet lacks basic scientific validation. This study assessed the response-to-loading patterns of cartilage and meniscus incurred by standardized compartmental varus and valgus loading of the human knee joint. Eight human cadaveric knee joints underwent imaging by morphologic (i.e., proton density-weighted fat-saturated and 3D water-selective) and quantitative (i.e., T1ρ and T2 mapping) sequences, both unloaded and loaded to 73.5 N, 147.1 N, and 220.6 N of compartmental pressurization. After manual segmentation of cartilage and meniscus, morphometric measures and T2 and T1ρ relaxation times were quantified. CT-based analysis of joint alignment and histologic and biomechanical tissue measures served as references. Under loading, we observed significant decreases in cartilage thickness (p < 0.001 (repeated measures ANOVA)) and T1ρ relaxation times (p = 0.001; medial meniscus, lateral tibia; (Friedman test)), significant increases in T2 relaxation times (p ≤ 0.004; medial femur, lateral tibia; (Friedman test)), and adaptive joint motion. In conclusion, varus and valgus stress MRI induces meaningful changes in cartilage and meniscus secondary to compartmental loading that may be assessed by cartilage morphometric measures as well as T2 and T1ρ mapping as imaging surrogates of tissue functionality.

Device for Assessing Knee Joint Dynamics During Magnetic Resonance Imaging

BACKGROUND

Knee assessment with and without load using magnetic resonance imaging (MRI) can provide information on knee joint dynamics and improve the diagnosis of knee joint diseases. Performing such studies on a routine MRI-scanner require a load-exerting device during scanning. There is a need for more studies on developing loading devices and evaluating their clinical potential.

PURPOSE

Design and develop a portable and easy-to-use axial loading device to evaluate the knee joint dynamics during the MRI study.

STUDY TYPE

Prospective study.

SUBJECTS

Nine healthy subjects.

FIELD STRENGTH/SEQUENCE

A 0.25 T standing-open MRI and 3.0 T MRI. PD-T₂ -weighted FSE, 3D-fast-spoiled-gradient-echo, FS-PD, and CartiGram sequences.

ASSESSMENT

Design and development of loading device, calibration of loads, MR safety assessment (using projectile angular displacement, torque, and temperature tests). Scoring system for ease of doing. Qualitative (by radiologist) and quantitative (using structural similarity index measure [SSIM]) image-artifact assessment. Evaluation of repeatability, comparison with various standing stances load, and loading effect on knee MR parameters (tibiofemoral bone gap [TFBG], femoral cartilage thickness [FCT], tibial cartilage thickness [TCT], femoral cartilage T₂ -value [FCT2], and tibia cartilage T₂ -value [TCT2]). The relative percentage change (RPC) in parameters due to the device load was computed.

STATISTICAL TEST

Pearson's correlation coefficient (r).

RESULTS

The developed device is conditional-MR safe (details in the manuscript and supplementary materials), 15 × 15 × 45 cm³ dimension, and <3 kg. The ease of using the device was 4.9/5. The device introduced no visible image artifacts, and SSIM of 0.9889 ± 0.0153 was observed. The TFBG intraobserver variability (absolute difference) was <0.1 mm. Interobserver variability of all regions of interest was <0.1 mm. The load exerted by the device was close to the load during standing on both legs in 0.25 T scanner with r > 0.9. Loading resulted in RPC of 1.5%-11.0%, 7.9%-8.5%, and -1.5% to 13.0% in the TFBG, FCT, and TCT, respectively. FCT2 and TCT2 were reduced in range of 1.5-2.7 msec and 0.5-2.3 msec due to load.

DATA CONCLUSION

The proposed device is conditionally MR safe, low cost (material cost < INR 6000), portable, and effective in loading the knee joint with up to 50% of body weight.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 1.

Model for in-vivo estimation of stiffness of tibiofemoral joint using MR imaging and FEM analysis

BACKGROUND

Appropriate structural and material properties are essential for finite-element-modeling (FEM). In knee FEM, structural information could extract through 3D-imaging, but the individual subject's tissue material properties are inaccessible.

PURPOSE

The current study's purpose was to develop a methodology to estimate the subject-specific stiffness of the tibiofemoral joint using finite-element-analysis (FEA) and MRI data of knee joint with and without load.

METHODS

In this study, six Magnetic Resonance Imaging (MRI) datasets were acquired from 3 healthy volunteers with axially loaded and unloaded knee joint. The strain was computed from the tibiofemoral bone gap difference (ΔmBGFT) using the knee MR images with and without load. The knee FEM study was conducted using a subject-specific knee joint 3D-model and various soft-tissue stiffness values (1 to 50 MPa) to develop subject-specific stiffness versus strain models.

RESULTS

Less than 1.02% absolute convergence error was observed during the simulation. Subject-specific combined stiffness of weight-bearing tibiofemoral soft-tissue was estimated with mean values as 2.40 ± 0.17 MPa. Intra-subject variability has been observed during the repeat scan in 3 subjects as 0.27, 0.12, and 0.15 MPa, respectively. All subject-specific stiffness-strain relationship data was fitted well with power function (R² = 0.997).

CONCLUSION

The current study proposed a generalized mathematical model and a methodology to estimate subject-specific stiffness of the tibiofemoral joint for FEM analysis. Such a method might enhance the efficacy of FEM in implant design optimization and biomechanics for subject-specific studies. Trial registration The institutional ethics committee (IEC), Indian Institute of Technology, Delhi, India, approved the study on 20th September 2017, with reference number P-019; it was a pilot study, no clinical trail registration was recommended.

Ultrashort echo time adiabatic T1ρ (UTE-Adiab-T1ρ) is sensitive to human cadaveric knee joint deformation induced by mechanical loading and unloading

PURPOSE

The development of ultrashort echo time (UTE) MRI sequences has led to improved imaging of tissues with short T2 relaxation times, such as the deep layer cartilage and meniscus. UTE combined with adiabatic T1ρ preparation (UTE-Adiab-T1ρ) is an MRI measure with low sensitivity to the magic angle effect. This study aimed to investigate the sensitivity of UTE-Adiab-T1ρ to mechanical load-induced deformations in the tibiofemoral cartilage and meniscus of human cadaveric knee joints.

METHODS

Eight knee joints from young (42 ± 12 years at death) donors were evaluated on a 3 T scanner using the UTE-Adiab-T1ρ sequence under four sequential loading conditions: load = 0 N (Load0), load = 300 N (Load1), load = 500 N (Load2), and load = 0 N (Unload). UTE-Adiab-T1ρ was measured in the meniscus (M), femoral articular cartilage (FAC), tibial articular cartilage (TAC), articular cartilage regions uncovered by meniscus (AC-UC), and articular cartilage regions covered by meniscus (AC-MC) within region of interests (ROIs) manually selected by an experienced MR scientist. The Kruskal-Wallis test, with corrected significance level for multiple comparisons, was used to examine the UTE-Adiab-T1ρ differences between different loading conditions.

RESULTS

UTE-Adiab-T1ρ decreased in all grouped ROIs under both Load1 and Load2 conditions (-18.7% and - 16.9% for M, -18.8% and - 12.6% for FAC, -21.4% and - 10.7% for TAC, -26.2% and - 13.9% for AC-UC, and - 16.9% and - 10.7% for AC-MC). After unloading, average UTE-Adiab-T1ρ increased across all ROIs and within a lower range compared with the average UTE-Adiab-T1ρ decreases induced by the two previous loading conditions. The loading-induced differences were statistically non-significant.

CONCLUSIONS

While UTE-Adiab-T1ρ reduction by loading is likely an indication of tissue deformation, the increase of UTE-Adiab-T1ρ within a lower range by unloading implies partial tissue restoration. This study highlights the UTE-Adiab-T1ρ technique as an imaging marker of tissue function for detecting deformation patterns under loading.

Degeneration Affects Three-Dimensional Strains in Human Menisci: In situ MRI Acquisition Combined With Image Registration

Degenerative changes of menisci contribute to the evolution of osteoarthritis in the knee joint, because they alter the load transmission to the adjacent articular cartilage. Identifying alterations in the strain response of meniscal tissue under compression that are associated with progressive degeneration may uncover links between biomechanical function and meniscal degeneration. Therefore, the goal of this study was to investigate how degeneration effects the three-dimensional (3D; axial, circumferential, radial) strain in different anatomical regions of human menisci (anterior and posterior root attachment; anterior and posterior horn; pars intermedia) under simulated compression. Magnetic resonance imaging (MRI) was performed to acquire image sequences of 12 mild and 12 severe degenerated knee joints under unloaded and loaded [25%, 50% and 100% body weight (BW)] conditions using a customized loading device. Medial and lateral menisci as well as their root attachments were manually segmented. Intensity-based rigid and non-rigid image registration were performed to obtain 3D deformation fields under the respective load levels. Finally, the 3D voxels were transformed into hexahedral finite-element models and direction-dependent local strain distributions were determined. The axial compressive strain in menisci and meniscal root attachments significantly increased on average from 3.1% in mild degenerated joints to 7.3% in severe degenerated knees at 100% BW (p ≤ 0.021). In severe degenerated knee joints, the menisci displayed a mean circumferential strain of 0.45% (mild: 0.35%) and a mean radial strain of 0.41% (mild: 0.37%) at a load level of 100% BW. No significant changes were observed in the circumferential or radial directions between mild and severe degenerated knee joints for all load levels (p > 0.05). In conclusion, high-resolution MRI was successfully combined with image registration to investigate spatial strain distributions of the meniscus and its attachments in response to compression. The results of the current study highlight that the compressive integrity of the meniscus decreases with progressing tissue degeneration, whereas the tensile properties are maintained.

An MRI-compatible varus-valgus loading device for whole-knee joint functionality assessment based on compartmental compression: a proof-of-concept study

OBJECTIVE

Beyond static assessment, functional techniques are increasingly applied in magnetic resonance imaging (MRI) studies. Stress MRI techniques bring together MRI and mechanical loading to study knee joint and tissue functionality, yet prototypical axial compressive loading devices are bulky and complex to operate. This study aimed to design and validate an MRI-compatible pressure-controlled varus-valgus loading device that applies loading along the joint line.

METHODS

Following the device's thorough validation, we demonstrated proof of concept by subjecting a structurally intact human cadaveric knee joint to serial imaging in unloaded and loaded configurations, i.e. to varus and valgus loading at 7.5 kPa (= 73.5 N), 15 kPa (= 147.1 N), and 22.5 kPa (= 220.6 N). Following clinical standard (PDw fs) and high-resolution 3D water-selective cartilage (WATSc) sequences, we performed manual segmentations and computations of morphometric cartilage measures. We used CT and radiography (to quantify joint space widths) and histology and biomechanics (to assess tissue quality) as references.

RESULTS

We found (sub)regional decreases in cartilage volume, thickness, and mean joint space widths reflective of areal pressurization of the medial and lateral femorotibial compartments.

DISCUSSION

Once substantiated by larger sample sizes, varus-valgus loading may provide a powerful alternative stress MRI technique.

Functional MRI Mapping of Human Meniscus Functionality and its Relation to Degeneration

Meniscus pathology may promote early osteoarthritis. This study assessed human meniscus functionality (i.e. its response to loading) ex vivo based on quantitative T1, T1ρ, and T2 mapping as a function of histological degeneration and loading. Forty-five meniscus samples of variable degeneration were harvested from the lateral meniscus body region of 45 patients during total knee arthroplasties. Samples underwent serial mapping on a 3.0-T MRI scanner (Achieva, Philips) using a force-controlled and torque-inducing compressive loading device. Samples were measured at three loading positions, i.e. unloaded, loaded to 2 bar (compression force 37 N) and 4 bar (69 N). Histology (Pauli classification) and biomechanics (Elastic Modulus) served as references. Based on histology, samples were trichotomized as grossly intact (n = 14), mildly degenerative (n = 16), and moderate-to-severely degenerative (n = 15) and analyzed using appropriate parametric and non-parametric tests. For T1, we found loading-induced decreases in all samples, irrespective of degeneration. For T1ρ, zonal increases in intact (apex) and decreases in degenerative samples (base) were found, while for T2, changes were ambiguous. In conclusion, force-controlled loading and serial MR imaging reveal response-to-loading patterns in meniscus. Zonal T1ρ response-to-loading patterns are most promising in differentiating degeneration, while T1 and T2 aren’t clearly related to degeneration.and may provide an imaging-based indication of functional tissue properties.

Magnetic resonance imaging (MRI) studies of knee joint under mechanical loading: Review

Osteoarthritis (OA) is a very common disease that affects the human knee joint, particularly the articular cartilage and meniscus components which are regularly under compressive mechanical loads. Early-stage OA diagnosis is essential as it allows for timely intervention. The primary non-invasive approaches currently available for OA diagnosis include magnetic resonance imaging (MRI), which provides excellent soft tissue contrast at high spatial resolution. MRI-based knee investigation is usually performed on joints at rest or in a non-weight-bearing condition that does not mimic the actual physiological condition of the joint. This discrepancy may lead to missed detections of early-stage OA or of minor lesions. The mechanical properties of degenerated musculoskeletal (MSK) tissues may vary markedly before any significant morphological or structural changes detectable by MRI. Recognizing distinct deformation characteristics of these tissues under known mechanical loads may reveal crucial joint lesions or mechanical malfunctions which result from early-stage OA. This review article summarizes the large number of MRI-based investigations on knee joints under mechanical loading which have been reported in the literature including the corresponding MRI measures, the MRI-compatible devices employed, and potential challenges due to the limitations of clinical MRI sequences.

Low field magnetic resonance imaging of the equine distal interphalangeal joint: Comparison between weight-bearing and non-weight-bearing conditions

This descriptive study aimed to compare the magnetic resonance appearance of the distal interphalangeal joint articular cartilage between standing weight-bearing and non-weight-bearing conditions. Ten forefeet of live horses were scanned in a standing low-field magnetic resonance system (0.27 T). After euthanasia for reasons unrelated to the study, the non-weight-bearing isolated feet were scanned in a vertical positioning reproducing limb orientation in live horses. The same acquisition settings as during the weight-bearing examination were used. Thickness and cross-sectional area of the distal interphalangeal articular cartilage and joint space were measured on tridimensional T1-weighted gradient echo high resolution frontal and sagittal images at predetermined landmarks in both conditions and were compared using a linear mixed-effects model. Frontal images were randomized and submitted to 9 blinded readers with 3 different experience levels for identification of weight-bearing versus non-weight-bearing acquisitions based on cartilage appearance. Weight-bearing limbs had significantly thinner distal interphalangeal cartilage (p = 0.0001) than non-weight-bearing limbs. This change was greater in the distal phalanx cartilage than that of the middle phalanx. Blinded readers correctly identified 83% (range 65 to 95%) of the images as weight-bearing or non-weight-bearing acquisitions, with significantly different results observed among the different readers (p < 0.001) and groups (p < 0.001). These results indicate that distal interphalangeal articular cartilage and particularly cartilage of the distal phalanx thins when weight-bearing compared to the non-weight-bearing standing postmortem conditions and suggest that cartilage abnormalities may be more difficult to identify on weight-bearing standing magnetic resonance imaging.

Reducing uncertainty when using knee-specific finite element models by assessing the effect of input parameters

Little is known about knee-specific factors that influence contact mechanics. Finite Element (FE) models offer a powerful tool to study contact mechanics, but there often exists ambiguity in the exact values of the inputs (e.g., tissue properties), which can result in a range of output values. Our objective was to quantify the reduction in the range of output values (defined herein as "uncertainty") from FE models of the human knee joint when known pre-defined values are used for clinically measurable inputs. To achieve this goal, we applied a statistically augmented FE approach to three human cadaveric knees for which full geometric and kinematic data were available. Two sets of conditions were simulated: All model inputs, clinically measurable or not, were varied to represent a "normal" patient population (Condition 1); subsets of clinically measurable variable inputs were fixed at specific values (called "patient derived inputs," or PDIs) while the other variables were varied over "normal" values (Condition 2). We found that by fixing body mass index and the anterior-posterior position of the meniscal-bony insertion points, model output uncertainty was reduced by one- to three-fifths. The magnitude of uncertainty reduction was strongly influenced by the individual knee. It was observed that knees with great anterior-posterior translation during gait had greater reductions in uncertainty when PDIs were used. This study represents the first step in developing FE models of the human knee joint based on inputs that can be derived from patients in a clinical setting. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2233-2242, 2017.

Functional in situ assessment of human articular cartilage using MRI: a whole-knee joint loading device

The response to loading of human articular cartilage as assessed by magnetic resonance imaging (MRI) remains to be defined in relation to histology and biomechanics. Therefore, an MRI-compatible whole-knee joint loading device for the functional in situ assessment of cartilage was developed and validated in this study. A formalin-fixed human knee was scanned by computed tomography in its native configuration and digitally processed to create femoral and tibial bone models. The bone models were covered by artificial femoral and tibial articular cartilage layers in their native configuration using cartilage-mimicking polyvinyl siloxane. A standardized defect of 8 mm diameter was created within the artificial cartilage layer at the central medial femoral condyle, into which native cartilage samples of similar dimensions were placed. After describing its design and specifications, the comprehensive validation of the device was performed using a hydraulic force gauge and digital electronic pressure-sensitive sensors. Displacement-controlled quasi-static uniaxial loading to 2.5 mm [Formula: see text] and 5.0 mm [Formula: see text] of the mobile tibia versus the immobile femur resulted in forces of [Formula: see text] N [Formula: see text] and [Formula: see text] N [Formula: see text] (on the entire joint) and local pressures of [Formula: see text] MPa [Formula: see text] and [Formula: see text] MPa [Formula: see text] (at the site of the cartilage sample). Upon confirming the MRI compatibility of the set-up, the response to loading of macroscopically intact human articular cartilage samples ([Formula: see text]) was assessed on a clinical 3.0-T MR imaging system using clinical standard proton-density turbo-spin echo sequences and T2-weighted multi-spin echo sequences. Serial imaging was performed at the unloaded state [Formula: see text] and at consecutive loading positions (i.e. at [Formula: see text] and [Formula: see text]. Biomechanical unconfined compression testing (Young's modulus) and histological assessment (Mankin score) served as the standards of reference. All samples were histologically intact (Mankin score, [Formula: see text]) and biomechanically reasonably homogeneous (Young's modulus, [Formula: see text] MPa). They could be visualized in their entirety by MRI and significant decreases in sample height [[Formula: see text]: [Formula: see text] mm; [Formula: see text]: [Formula: see text] mm; [Formula: see text]: [Formula: see text] mm; [Formula: see text] (repeated-measures ANOVA)] as well as pronounced T2 signal decay indicative of tissue pressurization were found as a function of compressive loading. In conclusion, our compression device has been validated for the noninvasive response-to-loading assessment of human articular cartilage by MRI in a close-to-physiological experimental setting. Thus, in a basic research context cartilage may be functionally evaluated beyond mere static analysis and in reference to histology and biomechanics.

Clinical platform for understanding the relationship between joint contact mechanics and articular cartilage changes after meniscal surgery

Injury to the meniscus of the knee has been implicated as a significant risk factor for the subsequent development of osteoarthritis, but the mechanisms of joint degeneration are unclear. Our objective was to develop a clinically applicable methodology to evaluate the relationship of joint contact mechanics at the time of surgery to biological changes of articular cartilage as a function of time following surgery. A series of pre-, intra-, and post-operative protocols were developed which utilized electronic sensors for the direct measurement of contact mechanics, and advanced imaging to assess cartilage health. The tests were applied to a pilot cohort of young active patients undergoing meniscus allograft transplantation. Our study demonstrated significant variability across patients in terms of contact area and peak contact stress, both before and after transplantation. Nonetheless, the majority of patients exhibited decreased peak contact stress and increased contact area after graft implantation. MR scans at 3-6 months showed decreased T1ρ values in tibial articular cartilage, suggesting an increase in proteoglycan content or concomitant decrease in water content. Prolongation of T2 values was found primarily within the central, cartilage-cartilage contact region of the tibial plateau suggested disruption of the collagen network. Minimal differences were found in cartilage thickness over the short time frame of this preliminary study. With longer clinical follow-up, our platform of clinical tests can be used to better understand the patient-specific mechanical factors that are related to increased risk of OA after meniscus injury and surgery. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:600-611, 2017.

Effect of normal gait on in vivo tibiofemoral cartilage strains

Altered cartilage loading is believed to be associated with osteoarthritis development. However, there are limited data regarding the influence of normal gait, an essential daily loading activity, on cartilage strains. In this study, 8 healthy subjects with no history of knee surgery or injury underwent magnetic resonance imaging of a single knee prior to and following a 20-min walking activity at approximately 1.1m/s. Bone and cartilage surfaces were segmented from these images and compiled into 3-dimensional models of the tibia, femur, and associated cartilage. Thickness changes were measured across a grid of evenly spaced points spanning the models of the articular surfaces. Averaged compartmental strains and local strains were then calculated. Overall compartmental strains after the walking activity were found to be significantly different from zero in all four tibiofemoral compartments, with tibial cartilage strain being significantly larger than femoral cartilage strain. These results provide baseline data regarding the normal tibiofemoral cartilage strain response to gait. Additionally, the technique employed in this study has potential to be used as a "stress test" to understand how factors including age, weight, and injury influence tibiofemoral cartilage strain response, essential information in the development of potential treatment strategies for the prevention of osteoarthritis.