Change in knee cartilage T2 in response to mechanical loading

Nishii, Takashi; Kuroda, Kagayaki; Matsuoka, Yuichiro; Sahara, Tomohiro; Yoshikawa, Hideki

doi:10.1002/jmri.21418

Cited by 108 publications

(114 citation statements)

References 26 publications

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“…CBCT equipped with flat panels is advantageous over conventional CT in that it has high spatial resolution (e.g., 150 μm isotropic for flat-panel angiographic CT). Considering cartilage contact area 45 and thickness 46,47 changes on the order of submillimeter as loads were applied, conventional CT could lead to inaccurate measurements of soft tissue structures and alignment of the bones (e.g., patella, femur, and tibia) in knee. Thus, flat panel CBCT could extract useful information of the knee joint under loading conditions which was not currently achievable.…”

Section: Discussionmentioning

confidence: 99%

Fiducial marker‐based correction for involuntary motion in weight‐bearing C‐arm CT scanning of knees. Part I. Numerical model‐based optimization

et al. 2013

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Purpose: Human subjects in standing positions are apt to show much more involuntary motion than in supine positions. The authors aimed to simulate a complicated realistic lower body movement using the four-dimensional (4D) digital extended cardiac-torso (XCAT) phantom. The authors also investigated fiducial marker-based motion compensation methods in two-dimensional (2D) and threedimensional (3D) space. The level of involuntary movement-induced artifacts and image quality improvement were investigated after applying each method. Methods: An optical tracking system with eight cameras and seven retroreflective markers enabled us to track involuntary motion of the lower body of nine healthy subjects holding a squat position at 60• of flexion. The XCAT-based knee model was developed using the 4D XCAT phantom and the optical tracking data acquired at 120 Hz. The authors divided the lower body in the XCAT into six parts and applied unique affine transforms to each so that the motion (6 degrees of freedom) could be synchronized with the optical markers' location at each time frame. The control points of the XCAT were tessellated into triangles and 248 projection images were created based on intersections of each ray and monochromatic absorption. The tracking data sets with the largest motion (Subject 2) and the smallest motion (Subject 5) among the nine data sets were used to animate the XCAT knee model. The authors defined eight skin control points well distributed around the knees as pseudofiducial markers which functioned as a reference in motion correction. Motion compensation was done in the following ways: (1) simple projection shifting in 2D, (2) deformable projection warping in 2D, and (3) rigid body warping in 3D. Graphics hardware accelerated filtered backprojection was implemented and combined with the three correction methods in order to speed up the simulation process. Correction fidelity was evaluated as a function of number of markers used (4-12) and marker distribution in three scenarios. Results: Average optical-based translational motion for the nine subjects was 2.14 mm (±0.69 mm) and 2.29 mm (±0.63 mm) for the right and left knee, respectively. In the representative central slices of Subject 2, the authors observed 20.30%, 18.30%, and 22.02% improvements in the structural similarity (SSIM) index with 2D shifting, 2D warping, and 3D warping, respectively. The performance of 2D warping improved as the number of markers increased up to 12 while 2D shifting and 3D warping were insensitive to the number of markers used. The minimum required number of markers for 2D shifting, 2D warping, and 3D warping was 4-6, 12, and 8, respectively. An even distribution of markers over the entire field of view provided robust performance for all three correction methods. Conclusions:The authors were able to simulate subject-specific realistic knee movement in weightbearing positions. This study indicates that involuntary motion can seriously degrade the image quality. The proposed three methods were evaluated with the...

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Section: Discussionmentioning

confidence: 99%

Fiducial marker‐based correction for involuntary motion in weight‐bearing C‐arm CT scanning of knees. Part I. Numerical model‐based optimization

et al. 2013

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“…Smaller T2 decrease was observed in the intermediate cartilage layer, and no change was observed in the deep cartilage layer. Nishii et al reported similar results with a mechanical loading system [46]. T2 maps were acquired from 22 healthy volunteers under static loading conditions by applying axial compression force of 50% of body weight during imaging.…”

Section: Association Of T2 Measurements With Physical Activitymentioning

confidence: 93%

“…Significantly elevated T2 values were reported after 30 min of unloading the knee due to decompression of the cartilage and consequently increasing cartilage water content [45]. Loading and unloading the knee joint considerably affect the T2 values [46]. Therefore, physical activity before the scan and the time point of the T2 sequence within the MR protocol are important.…”

mentioning

confidence: 98%

MR T2 Relaxation Time Measurements for Cartilage and Menisci

Baum

Link²,

Dardzinski³

2011

Cartilage Imaging

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IntroductionMagnetic Resonance Imaging (MRI) can be used not only for morphologic but also for quantitative assessment of knee cartilage. Quantitative T1rho and T2 relaxation time measurements and dGEMRIC (delayed Gadolinium enhanced MRI of the cartilage) have emerged as potential cartilage biomarkers to assess early degenerative disease. This chapter focuses on the T2-technique and clinical applications of hyaline cartilage and meniscal T2 relaxation time measurements in particular at the knee.The chapter is structured into four parts: After a brief background section, image acquisition and processing are outlined. Subsequently, image analysis and clinical applications are presented. BackgroundEarly stages of knee osteoarthritis (OA) are characterized by degradation of components of the extracellular matrix of the cartilage [1,2]. The proteoglycan content decreases and the collagen network shows signs of disorganization. The latter induces higher water mobility and consequentially increased water content within the cartilage. These initial cartilage changes are subclinical, i.e., individuals do not have symptoms of OA. T1rho and T2 relaxation times are affected by these pathophysiological processes [3,4]. Whereas T1rho relaxation time is more sensitive to the proteoglycan content of the cartilage, T2 relaxation time is more sensitive to cartilage hydration and orientation and integrity of the collagen network. Therefore, T1rho and T2 are noninvasive biomarkers for cartilage degeneration. These biomarkers may be used to detect early stages of the disease, quantitatively assess disease severity, sensitively monitor disease progression, and monitor OA therapy. Since they are sensitive to tissue components of cartilage that change before morphologic signs are detectable, they are particularly suited for the early disease stages, which are not accessible with standard morphological MR imaging [5]. In one of the early studies, Dardzinski et al. analyzed T2 measurements in asymptomatic volunteers and found a reproducible pattern of increasing T2 that was proportional to the known spatial variation in cartilage water [6]. Based on these findings, the authors postulated that these regional T2 differences were secondary to the restricted mobility of cartilage water within an anisotropic solid matrix. In a subsequent clinical study, Mosher et al. studied asymptomatic volunteers and individuals with symptoms of patellar chondromalacia using quantitative T2 maps of patellar cartilage and found an asymptomatic increase in T2 with aging as well as an increase in cartilage T2 from the radial zone to the articular surface [7]. Based on these studies and findings, investigators adopted T2 relaxation time measurements to assess cartilage degeneration in clinical studies, which culminated in implementing T2 relaxation time measurements in the NIH sponsored Osteoarthritis Initiative (OAI) multicenter trial. Image Acquisition and Processing Imaging Sequences and Field StrengthQuantitative T2 relaxation time measurements in vivo are t...

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“…Thanks to the calculation and the display of the T2 maps it is possible to detect the changes in the collagen component of the ECM noninvasive and more precisely to detect the changes in the water content (distribution of interstitial water in the solid matrix) which are not normally visible in conventional MRI images (Nishii et al, 2008;Welsch et al, 2008).…”

Section: T2 Relaxation In Cartilage and Meniscimentioning

confidence: 99%

The Evaluation of Changes in The Knee Meniscus in vivo at 3T MRI Scanner

Horňáková¹,

Hadraba²,

Jelen³

2015

Auc Kinanthropologica

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Noninvasive imagining of the knee meniscus without the use of the contrast agents is more difficult compared to articular cartilage. Despite the lower signal intensity of the knee meniscus, MRI is considered the best non-invasive imaging method. Thanks to the lower water content in the meniscus compared to the surrounding tissues, it can be distinguished from the environment, but the determination of the boundaries is more complicated than in articular cartilage. There are many studies dealing with the MR imaging of the loaded and also unloaded knee, but they have mainly observed quantitative and geometric changes (movement or deformation of tissue), not targeted qualitative changes in the extracellular matrix (ECM). These changes can be evaluated with T2 relaxation times, which are more sensitive to the interaction of water molecules and the concentration of macromolecules and structures of the ECM, especially in the interaction based on the content, orientation and anisotropy of collagen fibers. Fluid and tissues with the higher water content level have long relaxation time T2. In the healthy meniscus these times are shorter; the reason is a highly organized structure of collagen and lower content of proteoglycans. To quantitatively detect changes, it is necessary to assure a sufficiently high resolution of images throughout choosing appropriate pulse sequences. After that, the acquired data can be processed to produce the T2 maps, to portray non-invasive collagen content, architecture of the ROI, changes in the water content (distribution of interstitial water in the solid matrix) and the spatial variation in depth. The aim of this work is firstly to introduce the meaning of T2 relaxation and methods for calculating T2 relaxation times. Further, the aim of this work is to give a brief description of the current pulse sequences used to display menisci.

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Change in knee cartilage T2 in response to mechanical loading

Cited by 108 publications

References 26 publications

Fiducial marker‐based correction for involuntary motion in weight‐bearing C‐arm CT scanning of knees. Part I. Numerical model‐based optimization

Fiducial marker‐based correction for involuntary motion in weight‐bearing C‐arm CT scanning of knees. Part I. Numerical model‐based optimization

MR T2 Relaxation Time Measurements for Cartilage and Menisci

The Evaluation of Changes in The Knee Meniscus in vivo at 3T MRI Scanner

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