Diffusion tensor imaging of articular cartilage at 3T correlates with histology and biomechanics in a mechanical injury model

Simultaneous multi-slice technique for reducing acquisition times in diffusion tensor imaging of the knee: a feasibility study

OBJECTIVES

To explore the feasibility of simultaneous multi-slice (SMS) technique for reducing acquisition times in readout-segmented echo planar imaging (RESOLVE) for diffusion tensor imaging (DTI) of the knee.

MATERIALS AND METHODS

A total of 30 healthy volunteers and 23 patients with knee acute injury (12 cases with anterior ligament (ACL) tears and 16 cases with patellar cartilage (PC) injury) were enrolled in this prospective study. Three DTI protocols were used: conventional RESOLVE-DTI with 12 directions (protocol 1), SMS-RESOLVE-DTI with 12 directions (protocol 2) and 20 directions (protocol 3). DTI parameters of gastrocnemius, ACL and posterior cruciate ligament (PCL), and PC from three protocols were quantitatively assessed.

RESULTS

For volunteers, protocol 2 significantly reduced acquisition time by 38.6% and 34.2% compared to protocols 1 and 3 while maintaining similar high-quality images and similar diffusive parameters, except for the fractional anisotropy (FA) and axial diffusivity (AD) of the PC between protocols 2 and 1 (P < 0.05). For injured ACL and PC, protocols 1 and 2 showed similar accurate diffusive parameters (except for AD, P = 0.025) and similar diagnostic efficacy, which demonstrated significantly lower FA and higher radial diffusivity (RD) in protocols 1 and 2 compared to volunteers (P < 0.05).

CONCLUSIONS

The 12-direction SMS-RESOLVE-DTI demonstrated a favorable balance between acquisition time and image quality, making it a promising alternative to conventional DTI for evaluating ligament and cartilage injuries.

ADVANCES IN KNOWLEDGE

The SMS technique greatly reduces acquisition time while maintaining image quality, which signified the possibility of DTI's clinical application.

Assessment of Mechanically Induced Changes in Helical Fiber Microstructure Using Diffusion Tensor Imaging

Noninvasive methods to detect microstructural changes in collagen-based fibrous tissues are necessary to differentiate healthy from damaged tissues in vivo but are sparse. Diffusion Tensor Imaging (DTI) is a noninvasive imaging technique used to quantitatively infer tissue microstructure with previous work primarily focused in neuroimaging applications. Yet, it is still unclear how DTI metrics relate to fiber microstructure and function in musculoskeletal tissues such as ligament and tendon, in part because of the high heterogeneity inherent to such tissues. To address this limitation, we assessed the ability of DTI to detect microstructural changes caused by mechanical loading in tissue-mimicking helical fiber constructs of known structure. Using high-resolution optical and micro-computed tomography imaging, we found that static and fatigue loading resulted in decreased sample diameter and a re-alignment of the macro-scale fiber twist angle similar with the direction of loading. However, DTI and micro-computed tomography measurements suggest microstructural differences in the effect of static versus fatigue loading that were not apparent at the bulk level. Specifically, static load resulted in an increase in diffusion anisotropy and a decrease in radial diffusivity suggesting radially uniform fiber compaction. In contrast, fatigue loads resulted in increased diffusivity in all directions and a change in the alignment of the principal diffusion direction away from the constructs' main axis suggesting fiber compaction and microstructural disruptions in fiber architecture. These results provide quantitative evidence of the ability of DTI to detect mechanically induced changes in tissue microstructure that are not apparent at the bulk level, thus confirming its potential as a noninvasive measure of microstructure in helically architected collagen-based tissues, such as ligaments and tendons.

T2 Mapping of Patellar Cartilage After a Single First-Time Episode of Traumatic Lateral Patellar Dislocation

BACKGROUND

In most cases, lateral patellar dislocation (LPD) is accompanied by chondral injury and may initiate gradual degeneration of patellar cartilage, which might be detected with a T2 mapping, a well-established method for cartilage lesions assessment.

PURPOSE

To examine short-term consequences of single first-time LPD in teenagers by T2 mapping of the patellar-cartilage state.

STUDY TYPE

Prospective.

POPULATION

95 patients (mean age: 15.1 ± 2.3; male/female: 46/49) with first-time, complete, traumatic LPD and 51 healthy controls (mean age: 14.7 ± 2.2, male/female: 29/22).

FIELD STRENGTH/SEQUENCE

3.0 T; axial T2 mapping acquired using a 2D turbo spin-echo sequence.

ASSESSMENT

MRI examination was conducted 2-4 months after first LPD. T2 values were calculated in manually segmented cartilage area via averaging over three middle level slices in six cartilage regions: deep, intermediate, superficial layers, and medial lateral parts.

STATISTICAL TESTS

ANOVA analysis with Tukey's multiple comparison test, one-vs.-rest logistic regression analysis. The threshold of significance was set at P < 0.05.

RESULTS

In lateral patellar cartilage, a significant increase in T2 values was found in deep and intermediate layers in both patient groups with mild (deep: 34.7 vs. 31.3 msec, intermediate: 38.7 vs. 34.6 msec, effect size = 0.55) and severe (34.8 vs. 31.3 msec, 39.1 vs. 34.6 msec, 0.55) LPD consequences as compared to controls. In the medial facet, only severe cartilage damage showed significant prolongation of T2 times in the deep layer (34.3 vs. 30.7 msec, 0.55). No significant changes in T2 values were found in the lateral superficial layer (P = 0.99), whereas mild chondromalacia resulted in a significant decrease of T2 in the medial superficial layer (41.0 vs. 43.8 msec, 0.55).

DATA CONCLUSION

The study revealed substantial difference in T2 changes after LPD between medial and lateral areas of patellar cartilage.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY STAGE: 2.

Value of 3.0T MRI T2 mapping combined with SWI for the assessment of early lesions in hemophilic arthropathy

PURPOSE

To explore the value of magnetic resonance imaging (MRI) T2 mapping combined with susceptibility-weighted imaging (SWI) in detecting early cartilage damage and joint bleeding in the hemophilic arthropathy (HA).

METHODS

147 patients and 56 healthy controls were prospectively recruited. The knees were divided into groups A and B according to the criteria of the International Cartilage Repair Society (ICRS). The Regions of Interest (ROIs) of T2 mapping were drawn for the patella, lateral and medial femoral condyle, and lateral and medial tibial condyle. The T2 values were compared between the patients and control group using one-way ANOVA. The joint count data of International Prophylaxis Study Group (IPSG) scores of conventional and SWI sequences were statistically described using the composition ratio, and the rank sum test was used for the difference analysis.

RESULTS

Finally, there were 99 joints in the control group, 135 knees in group A, and 94 knees in group B. There was a significant difference between the T2 value in each subgroup. Comparison of T2 value groups in each cartilage partition, except for group A and group B of the patella, revealed significant differences (all P<0.05). SWI was likely more sensitive than conventional sequences in detecting hemosiderin deposits in hemophilic joints. In addition, the IPSG scores detected by the SWI were generally higher than those of conventional sequences.

CONCLUSIONS

MR T2 mapping combined with SWI has great potential to be used for detecting early cartilage damage and micro-hemosiderin deposition in hemophiliac arthropathies and developing preventative treatment plans.

Validating the accuracy of multispectral metal artifact suppressed diffusion-weighted imaging

BACKGROUND

Diffusion-weighted imaging (DWI) provides quantitative measurement of random water displacement in tissue as calculated by the apparent diffusion coefficient (ADC). While heavily utilized in stroke and oncology applications, DWI is a promising tool to map microstructural changes in musculoskeletal applications including evaluation of synovial reactions resulting from total hip arthroplasty (THA). One major challenge facing the application of DWI in THA is the significant artifacts related to the conventional echo-planar imaging (EPI) readout used. Multispectral imaging (MSI) techniques, including the multiacquisition with variable resonance image combination (MAVRIC), have been shown to effectively reduce metallic susceptibility artifacts around total joint replacements to render clinically useful images. Recently, a 2D periodically rotated overlapping parallel line with enhanced reconstruction (PROPELLER) FSE acquisition that incorporates a diffusion preparation pulse with 2D-MAVRIC has been developed to mitigate both distortion and dropout artifacts. While there have been some preliminary assessments of DWI-MAVRIC, the repeatability of DWI-MAVRIC and the effects of key parameters, such as the number of spectral bins, are unknown.

PURPOSE

To evaluate the quantitative accuracy of DWI-MAVRIC as compared to conventional diffusion sequences.

METHODS

A diffusion phantom with different reference diffusivities (ADC = 113-1123 μm2 /s) was used. Scans were performed on two 1.5T MRI scanners. DWI-EPI and DWI-MAVRIC were acquired in both the axial and coronal planes. Three spatial offsets (0 cm, 10 cm left, and 10 cm right off iso-center) were used to evaluate effects of off-isocenter positioning. To assess intraday and interday repeatability, DWI-EPI and DWI-MAVRIC acquisitions were repeated on one scanner at same-day and 9-month intervals. To assess inter-scanner repeatability, DWI-EPI and DWI-MAVRIC acquisitions were compared between two scanners. ADC maps were generated with and without gradient nonlinearity correction (GNC). Linear regression, correlation, and error statistics were determined between calculated and reference ADC values. Bland-Altman plots were generated to evaluate intraday, interday, and interscanner repeatability.

RESULTS

DWI-MAVRIC had excellent correlation to reference values but at reduced linearity (r = 1.00, slope = 0.91-0.94) as compared to DWI-EPI (r = 1.00, slope = 0.99-1.01). A greater than 5% ADC bias was observed at the lowest ADC values, predominantly in the DWI-MAVRIC scans. ADC values did not vary with DWI-MAVRIC parameters. DWI-EPI acquisitions had intraday, interday, and interscanner repeatability of 3.18 μm2 /s, 19.2 μm2 /s, and 20.2 μm2 /s, respectively. DWI-MAVRIC acquisitions had inferior intraday, interday, and interscanner repeatability of 13.3 μm2 /s, 44.7 μm2 /s, 110 μm2 /s, respectively. Lower ADC errors were found at isocenter, as compared to the left and right positions. GNC reduced the absolute error by 0.31% ± 0.89%, 3.6% ± 1.4%, 0.65% ± 2.4% for the center, left, and right positions, respectively.

CONCLUSIONS

DWI-MAVRIC provides good linearity with respect to reference values and good intra- and interday repeatability.

The Mechanism and Role of ADAMTS Protein Family in Osteoarthritis

Osteoarthritis (OA) is a principal cause of aches and disability worldwide. It is characterized by the inflammation of the bone leading to degeneration and loss of cartilage function. Factors, including diet, age, and obesity, impact and/or lead to osteoarthritis. In the past few years, OA has received considerable scholarly attention owing to its increasing prevalence, resulting in a cumbersome burden. At present, most of the interventions only relieve short-term symptoms, and some treatments and drugs can aggravate the disease in the long run. There is a pressing need to address the safety problems due to osteoarthritis. A disintegrin-like and metalloprotease domain with thrombospondin type 1 repeats (ADAMTS) metalloproteinase is a kind of secretory zinc endopeptidase, comprising 19 kinds of zinc endopeptidases. ADAMTS has been implicated in several human diseases, including OA. For example, aggrecanases, ADAMTS-4 and ADAMTS-5, participate in the cleavage of aggrecan in the extracellular matrix (ECM); ADAMTS-7 and ADAMTS-12 participate in the fission of Cartilage Oligomeric Matrix Protein (COMP) into COMP lyase, and ADAMTS-2, ADAMTS-3, and ADAMTS-14 promote the formation of collagen fibers. In this article, we principally review the role of ADAMTS metalloproteinases in osteoarthritis. From three different dimensions, we explain how ADAMTS participates in all the following aspects of osteoarthritis: ECM, cartilage degeneration, and synovial inflammation. Thus, ADAMTS may be a potential therapeutic target in osteoarthritis, and this article may render a theoretical basis for the study of new therapeutic methods for osteoarthritis.

Diffusion Tensor Imaging of the Knee to Predict Childhood Growth

Background Accurate and precise methods to predict growth remain lacking. Diffusion tensor imaging (DTI) depicts the columnar structure of the physis and metaphyseal spongiosa and provides measures of tract volume and length that may help predict growth. Purpose To validate physeal DTI metrics as predictors of height velocity (1-year height gain from time of MRI examination) and total height gain (height gain from time of MRI examination until growth stops) and compare the prediction accuracy with bone age-based models. Materials and Methods Femoral DTI studies (b values = 0 and 600 sec/mm2; directions = 20) of healthy children who underwent MRI of the knee between February 2012 and December 2016 were retrospectively analyzed. Children with height measured at MRI and either 1 year later (height velocity) or after growth cessation (total height gain, mean = 34 months from MRI) were included. Physeal DTI tract volume and length were correlated with height velocity and total height gain. Multilinear regression was used to assess the potential of DTI metrics in the prediction of both parameters. Bland-Altman plots were used to compare root mean square error (RMSE) and bias in height prediction using DTI versus bone age methods. Results Eighty-nine children (mean age, 13 years ± 3 [SD]; 47 boys) had height velocity measured, and 70 (mean age, 14 years ± 1; 36 girls) had total height gain measured. Tract volumes correlated with height velocity (r2 = 0.49) and total height gain (r2 = 0.46) (P < .001 for both) after controlling for age and sex. Tract volume was the strongest predictor for height velocity and total height gain. An optimal multilinear model including tract volume improved prediction of height velocity (R2 = 0.63, RMSE = 1.7 cm) and total height gain (R2 = 0.59, RMSE = 1.8 cm) compared with bone age-based methods (height velocity: R2 = 0.32, RMSE = 2.9 cm; total height gain: R2 = 0.42, RMSE = 5.0 cm). Conclusion Models using tract volume derived from diffusion tensor imaging may perform better than bone age-based models in children for the prediction of height velocity and total height gain. © RSNA, 2022.

An in silico Framework of Cartilage Degeneration That Integrates Fibril Reorientation and Degradation Along With Altered Hydration and Fixed Charge Density Loss

Injurious mechanical loading of articular cartilage and associated lesions compromise the mechanical and structural integrity of joints and contribute to the onset and progression of cartilage degeneration leading to osteoarthritis (OA). Despite extensive in vitro and in vivo research, it remains unclear how the changes in cartilage composition and structure that occur during cartilage degeneration after injury, interact. Recently, in silico techniques provide a unique integrated platform to investigate the causal mechanisms by which the local mechanical environment of injured cartilage drives cartilage degeneration. Here, we introduce a novel integrated Cartilage Adaptive REorientation Degeneration (CARED) algorithm to predict the interaction between degenerative variations in main cartilage constituents, namely collagen fibril disorganization and degradation, proteoglycan (PG) loss, and change in water content. The algorithm iteratively interacts with a finite element (FE) model of a cartilage explant, with and without variable depth to full-thickness defects. In these FE models, intact and injured explants were subjected to normal (2 MPa unconfined compression in 0.1 s) and injurious mechanical loading (4 MPa unconfined compression in 0.1 s). Depending on the mechanical response of the FE model, the collagen fibril orientation and density, PG and water content were iteratively updated. In the CARED model, fixed charge density (FCD) loss and increased water content were related to decrease in PG content. Our model predictions were consistent with earlier experimental studies. In the intact explant model, minimal degenerative changes were observed under normal loading, while the injurious loading caused a reorientation of collagen fibrils toward the direction perpendicular to the surface, intense collagen degradation at the surface, and intense PG loss in the superficial and middle zones. In the injured explant models, normal loading induced intense collagen degradation, collagen reorientation, and PG depletion both on the surface and around the lesion. Our results confirm that the cartilage lesion depth is a crucial parameter affecting tissue degeneration, even under physiological loading conditions. The results suggest that potential fibril reorientation might prevent or slow down fibril degradation under conditions in which the tissue mechanical homeostasis is perturbed like the presence of defects or injurious loading.

Collagen fibres determine the crack morphology in articular cartilage

Cracks in articular cartilage compromise tissue integrity and mechanical properties and lead to chondral lesions if untreated. An understanding of the mechanics of cracked cartilage may help in the prevention of cartilage deterioration and the development of tissue-engineered substitutes. The degeneration of cartilage in the presence of cracks may depend on the ultrastructure and composition of the tissue, which changes with aging, disease and habitual loading. It is unknown if the structural and compositional differences between immature and mature cartilage affect the mechanics of cartilage cracks, possibly predisposing one to a greater risk of degeneration than the other. We used a fibre-reinforced poro-viscoelastic swelling material model that accounts for large deformations and tension-compression non-linearity, and the finite element method to investigate the role of cartilage structure and composition on crack morphology and tissue mechanics. We demonstrate that the crack morphology predicted by our theoretical model agrees well with the histo-morphometric images of young and mature cracked cartilages under indentation loading. We also determined that the crack morphology was primarily dependent on collagen fibre orientation which differs as a function of cartilage depth and tissue maturity. The arcade-like collagen fibre orientation, first discussed by Benninghoff in his classical 1925 paper, appears to be beneficial for slowing the progression of tissue cracks by 'sealing' the crack and partially preserving fluid pressure during loading. Preservation of the natural load distribution between solid and fluid constituents of cartilage may be a key factor in slowing or preventing the propagation of tissue cracks and associated tissue matrix damage. STATEMENT OF SIGNIFICANCE: Cracks in articular cartilage can be detrimental to joint health if not treated, but it is not clear how they propagate and lead to tissue degradation. We used an advanced numerical model to determine the role of cartilage structure and composition on crack morphology under loading. Based on the structure and composition found in immature and mature cartilages, our model successfully predicts the crack morphology in these cartilages and determines that collagen fibre as the major determinant of crack morphology. The arcade-like Benninghoff collagen fibre orientation appears to be crucial in 'sealing' the tissue crack and preserves normal fluid-solid load distribution in cartilage. Inclusion of the arcade-like fibre orientation in tissue-engineered construct may help improve its integration within the host tissue.

Accuracy of collagen fibre estimation under noise using directional MR imaging

In tissues containing significant amounts of organised collagen, such as tendons, ligaments, menisci and articular cartilage, MR imaging exhibits a strong signal intensity variation caused by the angle between the collagen fibres and the magnetic field. By obtaining scans at different field orientations it is possible to determine the unknown fibre orientations and to deduce the underlying tissue microstructure. Our previous work demonstrated how this method can detect ligament injuries and maturity-related changes in collagen fibre structures. Practical application in human diagnostics will demand minimisation of scanning time and likely use of open low-field scanners that can allow re-orienting of the main field. This paper analyses the performance of collage fibre estimation for various image SNR values, and in relation to key parameters including number of scanning directions and parameters of the reconstruction algorithm. The analysis involved Monte Carlo simulation studies which provided benchmark performance measures, and studies using MR images of caprine knee samples with increasing levels of synthetic added noise. Tractography plots in the form of streamlines were performed, and an Alignment Index (AI) was employed as a measure of the detected orientation distribution. The results are highly encouraging, showing high accuracy and robustness even for low image SNR values.

Diffusion Tensor Imaging for Quantitative Assessment of Anterior Cruciate Ligament Injury Grades and Graft

BACKGROUND

As the need for quantitative assessment of anterior cruciate ligament (ACL) injuries and ACL graft increases, diffusion tensor imaging (DTI) becomes a more valuable measuring tool. However, DTI changes in differing injury grades of ACL and longitudinal graft remain unclear.

PURPOSE

To investigate the diagnostic performance of DTI in quantitatively assessing ACL injury severity and the development of ACL grafts within 6 months of surgery.

STUDY TYPE

A cohort study.

SUBJECTS

Thirty-five patients diagnosed with grades I-IV ACL injuries and 20 volunteers as controls were recruited.

FIELD STRENGTH/SEQUENCE

T₁ -weighted, T₂ -weighted, proton density (PD)-weighted, and DTI at 3.0T MRI.

ASSESSMENT

ACL injury grades in arthroscopic images and DTI quantitative data were evaluated from July 2016 to July 2018.

STATISTICAL TESTS

Chi-square test, analysis of variance, Spearman correlation analysis, and receiver operator characteristic (ROC) curves.

RESULTS

Both fractional anisotropy (FA) (r = -0.898, P < 0.05) and apparent diffusion coefficient (ADC) (r = 0.851, P < 0.05) were significantly correlated with the severity of ACL injuries. The area under the curve (AUC) values for differentiation between low- and high-grade ACL injuries with FA and ADC were 0.973 and 0.963, respectively. Although there were no significant differences in FA (P > 0.05) and ADC (P > 0.05) between grades I and II ACL injuries or in ADC (P > 0.05) between grades III and IV, there were significant differences in FA and ADC between two grades (P < 0.05). There were significant differences in FA (P < 0.05) and ADC (P < 0.05) between normal ACL and 3-month graft postoperation, as well as in ADC values between 3-month and 6-month graft postoperation (P < 0.05).

DATA CONCLUSION

DTI could be used to quantitatively evaluate the ACL injury grades and the development of ACL grafts. The diagnostic efficiency of FA values was higher than that of ADC values.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 3.

Use of Computational Modeling to Study Joint Degeneration: A Review

Osteoarthritis (OA), a degenerative joint disease, is the most common chronic condition of the joints, which cannot be prevented effectively. Computational modeling of joint degradation allows to estimate the patient-specific progression of OA, which can aid clinicians to estimate the most suitable time window for surgical intervention in osteoarthritic patients. This paper gives an overview of the different approaches used to model different aspects of joint degeneration, thereby focusing mostly on the knee joint. The paper starts by discussing how OA affects the different components of the joint and how these are accounted for in the models. Subsequently, it discusses the different modeling approaches that can be used to answer questions related to OA etiology, progression and treatment. These models are ordered based on their underlying assumptions and technologies: musculoskeletal models, Finite Element models, (gene) regulatory models, multiscale models and data-driven models (artificial intelligence/machine learning). Finally, it is concluded that in the future, efforts should be made to integrate the different modeling techniques into a more robust computational framework that should not only be efficient to predict OA progression but also easily allow a patient’s individualized risk assessment as screening tool for use in clinical practice.

Detection of maturity and ligament injury using magic angle directional imaging

PURPOSE

To investigate whether magnetic field-related anisotropies of collagen may be correlated with postmortem findings in animal models.

METHODS

Optimized scan planning and new MRI data-processing methods were proposed and analyzed using Monte Carlo simulations. Six caprine and 10 canine knees were scanned at various orientations to the main magnetic field. Image intensities in segmented voxels were used to compute the orientation vectors of the collagen fibers. Vector field and tractography plots were computed. The Alignment Index was defined as a measure of orientation distribution. The knees were subsequently assessed by a specialist orthopedic veterinarian, who gave a pathological diagnosis after having dissected and photographed the joints.

RESULTS

Using 50% less scans than reported previously can lead to robust calculation of fiber orientations in the presence of noise, with much higher accuracy. The 6 caprine knees were found to range from very immature (< 3 months) to very mature (> 3 years). Mature specimens exhibited significantly more aligned collagen fibers in their patella tendons compared with the immature ones. In 2 of the 10 canine knees scanned, partial cranial caudal ligament tears were identified from MRI and subsequently confirmed with encouragingly high consistency of tractography, Alignment Index, and dissection results.

CONCLUSION

This method can be used to detect injury such as partial ligament tears, and to visualize maturity-related changes in the collagen structure of tendons. It can provide the basis for new, noninvasive diagnostic tools in combination with new scanner configurations that allow less-restricted field orientations.

Osteoarthritis year in review 2018: mechanics

OBJECTIVE

To review recent biomechanics literature focused on the interactions between biomechanics and articular cartilage health, particularly focused on macro-scale and human studies.

DESIGN

A literature search was conducted in PubMed using the search terms (biomechanics AND osteoarthritis) OR (biomechanics AND cartilage) OR (mechanics AND osteoarthritis) OR (mechanics AND cartilage) for publications from April 2017 to April 2018.

RESULTS

Abstracts from the 559 articles generated from the literature search were reviewed. Due to the wide range of topics, 62 full texts with a focus on in vivo biomechanical studies were included for further discussion. Several overarching themes in the recent literature were identified and are summarized, including 1) new methods to detect early osteoarthritis (OA) development, 2) studies describing healthy and OA cartilage and biomechanics, 3) ACL injury and OA development, 4) meniscus injury and OA development, and 5) OA prevention, treatment, and management.

CONCLUSIONS

Mechanical loading is a critical factor in the maintenance of joint health. Abnormal mechanical loading can lead to the onset and progression of OA. Thus, recent studies have utilized various biomechanical models to better describe the etiology of OA development and the subsequent effects of OA on the mechanics of joint tissues and whole body biomechanics.

Diffusion tractography of the rat knee at microscopic resolution

PURPOSE

To evaluate whole knee joint tractography, including articular cartilage, ligaments, meniscus, and growth plate using diffusion tensor imaging (DTI) at microscopic resolution.

METHODS

Three rat knee joints were scanned using a modified 3D diffusion-weighted spin echo pulse sequence with 90- and 45-μm isotropic spatial resolution at 9.4T. The b values varied from 250 to 1250 s/mm² with 4 times undersampling in phase directions. Fractional anisotropy (FA) and mean diffusivity (MD) were compared at different spatial resolution and b values. Tractography was evaluated at multiple b values and angular resolutions in different connective tissues, and compared with conventional histology. The mean tract length and tract volume in various types of tissues were also quantified.

RESULTS

DTI metrics (FA and MD) showed consistent quantitative results at 90- and 45-μm isotropic spatial resolutions. Tractography of various connective tissues was found to be sensitive to the spatial resolution, angular resolution, and diffusion weightings. Higher spatial resolution (45 μm) supported tracking the cartilage collagen fiber tracts from the superficial zone to the deep zone, in a continuous and smooth progression in the transitional zone. Fiber length and fiber volume in the growth plate were strongly dependent on angular resolution and b values, whereas tractography in ligaments was found to be less dependent on spatial resolution.

CONCLUSION

High spatial and angular resolution DTI and diffusion tractography can be valuable for knee joint research because of its visualization capacity for collagen fiber orientations and quantitative evaluation of tissue's microscopic properties.

Diffusion tensor imaging of articular cartilage using a navigated radial imaging spin-echo diffusion (RAISED) sequence

OBJECTIVE

To validate a radial imaging spin-echo diffusion tensor (RAISED) sequence for high-resolution diffusion tensor imaging (DTI) of articular cartilage at 3 T.

METHODS

The RAISED sequence implementation is described, including the used non-linear motion correction algorithm. The robustness to eddy currents was tested on phantoms, and accuracy of measurement was assessed with measurements of temperature-dependent diffusion of free water. Motion correction was validated by comparing RAISED with single-shot diffusion-weighted echo-planar imaging (EPI) measures. DTI was acquired in asymptomatic subjects (n = 6) and subjects with doubtful (Kellgren-Lawrence [KL] grade 1, n = 9) and mild (KL = 2, n = 9) symptomatic knee osteoarthritis (OA). MD and FA values without correction, and after all corrections, were calculated. A test-retest evaluation of the DTI acquisition on three asymptomatic and three OA subjects was also performed.

RESULTS

The root mean squared coefficient of variation of the global test-restest reproducibility was 3.54% for MD and 5.34% for FA. MD was significantly increased in both femoral condyles (7-9%) of KL 1 and in the medial (11-17%) and lateral (10-12%) compartments of KL 2 subjects. Averaged FA presented a trend of lower values with increasing KL grade, which was significant for the medial femoral condyle (-11%) of KL 1 and all three compartments in KL 2 subjects (-18 to -11%). Group differences in MD and FA were only significant after motion correction.

CONCLUSION

The RAISED sequence with the proposed reconstruction framework provides reproducible assessment of DTI parameters in vivo at 3 T and potentially the early stages of the disease in large regions of interest.

KEY POINTS

• DTI of articular cartilage is feasible at 3T with a multi-shot RAISED sequence with non-linear motion correction. • RAISED sequence allows estimation of the diffusion indices MD and FA with test-retest errors below 4% (MD) and 6% (FA). • RAISED-based measurement of DTI of articular cartilage with non-linear motion correction holds potential to differentiate healthy from OA subjects.

A computational algorithm to simulate disorganization of collagen network in injured articular cartilage

Cartilage defects are a known risk factor for osteoarthritis. Estimation of structural changes in these defects could help us to identify high risk defects and thus to identify patients that are susceptible for the onset and progression of osteoarthritis. Here, we present an algorithm combined with computational modeling to simulate the disorganization of collagen fibril network in injured cartilage. Several potential triggers for collagen disorganization were tested in the algorithm following the assumption that disorganization is dependent on the mechanical stimulus of the tissue. We found that tensile tissue stimulus alone was unable to preserve collagen architecture in intact cartilage as collagen network reoriented throughout the cartilage thickness. However, when collagen reorientation was based on both tensile tissue stimulus and tensile collagen fibril strains or stresses, the collagen network architecture was preserved in intact cartilage. Using the same approach, substantial collagen reorientation was predicted locally near the cartilage defect and particularly at the cartilage-bone interface. The developed algorithm was able to predict similar structural findings reported in the literature that are associated with experimentally observed remodeling in articular cartilage. The proposed algorithm, if further validated, could help to predict structural changes in articular cartilage following post-traumatic injury potentially advancing to impaired cartilage function.

Quantitative evaluation of knee cartilage and meniscus destruction in patients with rheumatoid arthritis using T1ρ and T2 mapping

OBJECTIVE

To calculate T1ρ and T2 values of articular cartilage and menisci in knee joints of patients with RA, and compare the values between RA patients and healthy volunteers, to gain insight into the pathogenesis of cartilage and meniscus degradation in patients with RA.

MATERIALS AND METHODS

Nine patients with RA and knee joints symptoms were enrolled in the study, twenty healthy volunteers without knee joint diseases were included as controls. Sagittal fat-saturated T1ρ and T2 mapping images were obtained on a 3T MR scanner (GE750, GE Healthcare, Waukesha, WI), using a dedicated 8-channel knee coil. In the T1rho mapping sequence, the amplitude of the spin-lock pulse was 500Hz, spin lock durations=10/20/30/50ms. In the T2 mapping sequence,TR/TE were 1794/6.5, 13.4, 27, 40.7ms. Both sequences were performed with the following parameters: flip angle (FA)=90°, matrix: 320×256, FOV: 16×16cm², slice thickness: 3mm, bandwidth: 62.5kHZ, and a total scan time of 5:11min. T1ρ- and T2-mapping images were used for the segmentation of the articular cartilage of the patella, femoral trochlea, medial and lateral femoral condyle, medial and lateral tibial plateau. These images were also used for the segmentation of the anterior and posterior horns of the medial and lateral menisci with livewire semi-automatic segmentation algorithm of MATLAB. A Mann-Whitney U test was performed to compare the T1ρ and T2 values of the above mentioned regions between the two groups.

RESULTS

T1ρ (Z=-3.913 to -2.121, P=0.000-0.034) and T2 (Z=-3.866 to -2.216, P=0.000-0.026) values of knee cartilage in patients with RA were higher than that in healthy volunteers, except the cartilage of the patella (T1ρ: Z=-1.273, P=0.203,T2: Z=-0.236, P=0.814) and lateral tibial plateau (T1ρ:Z=-1.037, P=0.317). The T1ρ (Z=-1.462 to 0.572, P=0.095-0.908) and T2 (Z=-1.461 to 0.278, P=0.153-0.764) values of medial and lateral menisci showed no difference between the two groups.

CONCLUSION

Patients with RA exhibit diffuse knee cartilage destruction in the medial and lateral tibiofemoral joints and in the femoral trochlea. However, we found no increase in T1ρ and T2 values in menisci, this finding warrants further investigation.

A robust diffusion tensor model for clinical applications of MRI to cartilage

PURPOSE

Diffusion tensor imaging (DTI) of articular cartilage is a promising technique for the early diagnosis of osteoarthritis (OA). However, in vivo diffusion tensor (DT) measurements suffer from low signal-to-noise ratio (SNR) that can result in bias when estimating the six parameters of the full DT, thus reducing sensitivity. This study seeks to validate a simplified four-parameter DT model (zeppelin) for obtaining more robust and sensitive in vivo DTI biomarkers of cartilage.

METHODS

We use simulations in a substrate to mimic changes during OA; and analytic simulations of the DT drawn from a range of fractional anisotropies (FA) measured with high-quality DT data from ex vivo human cartilage. We also use in vivo data from the knees of a healthy subject and two OA patients with Kellgren-Lawrence (KL) grades 1 and 2.

RESULTS

For simulated in vivo cartilage SNR (∼25) and anisotropy levels, the estimated mean values of MD from the DT and zeppelin models were identical to the ground truth values. However, zeppelin's FA is more accurate in measuring water restriction. More specifically, the FA estimations of the DT model were additionally biased by between +2% and +48% with respect to zeppelin values. Additionally, both mean diffusivity (MD) and FA of the zeppelin had lower parameter variance compared to the full DT (F-test, P < 0.05). We observe the same trends from in vivo values of patient data.

CONCLUSION

The zeppelin is more robust than the full DT for cartilage diffusion anisotropy and SNR at levels typically encountered in clinical applications of articular cartilage. Magn Reson Med 79:1157-1164, 2018. © 2017 International Society for Magnetic Resonance in Medicine.