On the Significance of Motion Degradation in High-resolution 3D μMRI of Trabecular Bone

Rationale and Objectives

Subtle subject movement during high-resolution three-dimensional micro–magnetic resonance imaging of trabecular bone (TB) causes blurring, thereby rendering the data unreliable for quantitative analysis. In this work, the effects of translational and rotational motion displacements were evaluated qualitatively and quantitatively.

Materials and Methods

In experiment 1, motion was induced by applying various simulated and previously observed in vivo trajectories as phase shifts to k-space or rotation angles to k-space segments of a virtually motion-free data set. In experiment 2, images that were visually free of motion artifacts from two groups of 10 healthy individuals, differing in age, were selected to probe the effects of motion on TB parameters. In both experiments, images were rated for motion severity, and the scores were compared to a focus criterion, the normalized gradient squared.

Results

Strong correlations were observed between the motion quality scores and the corresponding normalized gradient squared values ( R 2 = 0.52–0.64, P < .01). The results from experiment 1 demonstrated consistently lower image quality and alterations in structural parameters of 9% to 45% with increased amplitude of displacements. In experiment 2, the significant differences in structural parameter group means of the motion-free images were lost upon motion degradation. Autofocusing, a postprocessing correction method, partially recovered the sharpness of the original motion-free images in 13 of 20 subjects.

Conclusions

Quantitative TB structural measures are highly sensitive to subtle motion-induced degradation, which adversely affects precision and statistical power. The results underscore the influence of subject movement in high-resolution three-dimensional micro–magnetic resonance imaging and its correction for TB structure analysis.

Osteoporosis, a disorder of bone remodeling imbalance, is usually assessed on the basis of bone mineral density, a surrogate marker of bone strength, typically obtained by dual-energy x-ray absorptiometry . Despite its ubiquity in the assessment of bone integrity, bone mineral density does not yield insights into bone quality, a somewhat elusive physical property based on the integrity of trabecular and cortical bone microstructure . Three-dimensional micro–magnetic resonance imaging (μMRI) acquisition and processing techniques enable direct visualization and quantification of trabecular bone (TB) architecture in response to aging or drug treatment of osteoporosis . One such suite of three-dimensional (3D) image acquisition and processing methods, the virtual bone biopsy (VBB) , has demonstrated reproducible and accurate quantification of TB architectural measures at peripheral locations. A number of investigators have performed structural analysis in patients at the distal radius , tibia , and calcaneus in vivo. The structural changes at these peripheral sites are strongly associated with similar changes occurring elsewhere in the skeleton , can be predictive of fracture status , and serve as useful markers for monitoring disease status.

The ability to accurately retrieve the 3D architectural features of TB depends on several parameters that include signal-to-noise ratio (SNR), voxel size, accurate coregistration of baseline and follow-up images in longitudinal studies, and motion during data acquisition . Motion degradation on MR images can be attributed to macroscopic motion that encompasses both physiologic motion, from respiration, cardiac pulsations, or peristalsis and involuntary subject movement during the scan. Although the former probably have minor effects, the latter are the key source of loss of image sharpness in μMRI of the distal extremities . The problem is exacerbated by the high resolution necessary for accurate retrieval of the 3D architecture of trabecular networks, which demand relatively long scan times (about 10–15 minutes), even though parallel imaging has the potential to substantially shorten acquisition times . Given image pixel sizes on the order of 100 μm, even submillimeter displacements arising from involuntary motion can be detrimental for TB microimages, and they are difficult to prevent despite using tight immobilization .

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Materials and methods

Motion Simulation Theory

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s˜(kx,ky)=e−i(kx,ky)s(kx,ky), s

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Here, Δ x and Δ y are the applied translational shifts in the x and y directions, respectively, for each k-space line.

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Image Acquisition, Reconstruction, and Preprocessing

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Postprocessing and Analysis

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Experiment 1

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Table 1

Range of Retrospective in Vivo Translational Motion Trajectories Providing Displacements Along x and y for Each of the Five Trajectories

Trajectory_x_ Motion, Pixels (Range)y Motion, Pixels (Range) 1 4.0 (−1.0 to 3.0) 4.0 (−1.8 to 2.2) 2 6.0 (−4.5 to 1.5) 4.4 (−2.2 to 2.2) 3 8.0 (−2.5 to 5.5) 5.3 (−2.2 to 3.1) 4 7.0 (−3.5 to 3.5) 4.5 (−3.1 to 1.4) 5 2.8 (−1.3 to 1.5) 2.3 (−1.3 to 1.0)

Table 2

Synthetic Translational Motion Trajectories

x Motion_y_ Motion Trajectory Pixels k y Interval Pixels k y Interval 1 3.0 1–150 0.0 0 2 6.0 1–150 0.0 0 3 9.0 1–150 0.0 0 4 0.0 0 3.0 200–350 5 0.0 0 6.0 200–350 6 0.0 0 9.0 200–350 7 1.0 1–150 3.0 1–150 8 3.0 200–350 3.0 200–350 9 6.0 1–200 9.0 200–350

The step-function displacements (in pixels) along x and y are given for different k y intervals.

Table 3

Simulated Rotational Motional Trajectories

Trajectory Rotation k y Interval 1 0.05° 0–150 2 0.10° 0–150 3 0.20° 0–150 4 0.05° 151–300 5 0.10° 151–300 6 0.20° 151–300 7 0.35° 0–150 8 0.70° 0–150 9 1.25° 0–150 10 2.0° 0–150 11 3.0° 0–150 12 5.0° 0–150 13 0.35° 151–300 14 0.70° 151–300 15 1.25° 151–300 16 2.0° 151–300 17 3.0° 151–300 18 5.0° 151–300

In-plane rotations are given for various k y intervals.

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NGS=∑i,j(|Gi,j|2)(∑i,j|Gi,j|)2, NGS

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Experiment 2

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Statistical Analysis

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Results

Experiment 1

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Experiment 2

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Discussion

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Conclusions

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