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

Ferizi, Uran; Rossi, Ignacio; Lee, Youjin; Lendhey, Matin; Teplensky, Jason; Kennedy, Oran D.; Kirsch, Thorsten; Bencardino, Jenny T.; Raya, José G.

doi:10.1002/mrm.26336

Cited by 21 publications

(16 citation statements)

References 45 publications

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“…This experimental remodeling in goats was found to be consistent with the direction and magnitude of cartilage strain resulting collagen network remodeling from the orientation angles of ~85° in non-operated controls closer to 45° orientation angle in repaired tissue near the bonecartilage interface, and below and next to the defect (repair area). Moreover, diffusion tensor MRI based measurements in injured cartilage have shown a decrease of fractional anisotropy (Ferizi et al 2016) that can be related to the more disorganized collagen architecture, i.e., reorientation closer to the 45° orientation angles in the current model. Yet, it is not certain whether this experimentally observed decrease in the fractional anisotropy results from either disorganization/reorientation of collagen network or loss of proteoglycans or both.…”

Section: Comparison To Literaturementioning

confidence: 68%

“…Injurious loading of cartilage can induce physical lesions in cartilage (Rolauffs et al 2010;Alexander et al 2012;Virén et al 2012;Myller et al 2016;Ferizi et al 2016). It has been suggested that the damage and disorganization of the collagen network could progress following an injury which may further accelerate cartilage degradation (Ferizi et al 2016). However, it is not known which mechanical signals of cartilage tissue change around a focal cartilage defect that could affect collagen disorganization and possible progression of OA.…”

Section: Introductionmentioning

confidence: 99%

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

Tanska

Julkunen

Korhonen

2017

Biomech Model Mechanobiol

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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.

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Section: Comparison To Literaturementioning

confidence: 68%

Section: Introductionmentioning

confidence: 99%

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

Tanska

Julkunen

Korhonen

2017

Biomech Model Mechanobiol

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“…Roya et al reported that these scalar metrics detect early cartilage damage and are useful in diagnosis of osteoarthritis . These metrics are sensitive in tracking early changes after mechanical injury, and the changes that correlate with variations in biomechanics and histology …”

Section: Discussionmentioning

confidence: 99%

Diffusion tractography of the rat knee at microscopic resolution

Wang

Mirando

Cofer

et al. 2019

Magnetic Resonance in Med

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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.

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“…The proposed magic angle directional imaging represents an alternative method to the DTI, which is a widely used technique for fiber tractography. The present study did not involve a direct comparison with DTI, although it would be useful to perform such an investigation in the future.…”

Section: Discussionmentioning

confidence: 99%

Detection of maturity and ligament injury using magic angle directional imaging

Chappell

Brujić

Straeten

et al. 2019

Magnetic Resonance in Med

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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. K E Y W O R D Scollagen, magic angle effect, musculoskeletal imaging

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

Abstract: DTI is sensitive in tracking early changes after mechanical injury, and its changes correlate with changes in biomechanics and histology. Magn Reson Med 78:69-78, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Cited by 21 publications

References 45 publications

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

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

Diffusion tractography of the rat knee at microscopic resolution

Detection of maturity and ligament injury using magic angle directional imaging

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