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Medical Physics / Volume 35 / Issue 12 / ANATOMY AND PHYSIOLOGY

Med. Phys. 35, 5584 (2008); http://dx.doi.org/10.1118/1.3005598 (11 pages)

Implications of resolution and noise for in vivo micro-MRI of trabecular bone

Charles Q. Li, Jeremy F. Magland, Chamith S. Rajapakse, Branimir Vasilic, and Felix W. Wehrli

Laboratory for Structural NMR Imaging, Department of Radiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104

X. Edward Guo and X. Henry Zhang

Bone Bioengineering Laboratory, Department of Biomedical Engineering, Columbia University, New York, New York 10027

(Received 9 June 2008; accepted 1 October 2008; revised 2 September 2008; published online 17 November 2008)

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Osteoporotic bone loss is accompanied by impaired structural integrity of the trabecular network, leading to a decrease in the overall mechanical properties of the bone. The development of the “virtual bone biopsy” (VBB), a method combining magnetic resonance microimaging (μMRI) and digital image processing techniques, has previously been shown to quantify topology and scale of human trabecular bone noninvasively. The aim of this work was to determine the extent to which structural parameters derived from images acquired in the limited spatial resolution regime of in vivo imaging are sensitive to resolution and noise and further, whether under these conditions, a small amount of bone loss and its associated structural manifestations can be detected. Toward these goals 3D models of trabecular bone representing multiple anatomic locations were generated on the basis of μCT images of human cadaveric bone cores. These images were binarized and the resulting data arrays representing pure bone (proton density=0) and pure marrow (proton density=255) subjected to simulated MR imaging by Cartesian sampling of k space, yielding, after 3D Fourier reconstruction, voxel sizes currently achievable in vivo. Subsequently, realistic levels of Gaussian noise were superimposed on the complex data and magnitude images were computed. The resulting images were subsequently VBB processed for a range of signal-to-noise ratio (SNR) values and image voxel sizes. For comparison of the predicted behavior to in vivo data, images from a recent patient study were evaluated as well. Systematic changes of the derived structural parameters changing progressively with decreasing SNR were noted, and it is shown that the errors are correctable using simple linear transformations, thereby allowing the data to be normalized. The predicted dependence of the structural parameters on SNR also closely parallel those observed in vivo. Finally, in order to assess the sensitivity of the VBB processing algorithms to detect bone loss during disease progression or regression in response to treatment, the high-resolution specimen data were subjected to 5% bone loss either by homogeneous or heterogeneous erosion and μMR images simulated at in vivo resolution and SNR. At typical in vivo SNR (SNR=12) and effective image resolution (160 μm isotropic and 137×137×410 μm3), VBB algorithms were able to detect the structural implications of a 5% loss in bone volume fraction with high statistical significance.

© 2008 American Association of Physicists in Medicine

Digital Object Identifier
http://dx.doi.org/10.1118/1.3005598

KEYWORDS and PACS

Keywords

biomechanics, biomedical MRI, bone, diseases, Fourier analysis, Gaussian noise, image reconstruction, image resolution, image sampling, medical image processing, orthopaedics, trabecular bone imaging, noise and resolution, osteodegeneration

PACS

PUBLICATION DATA

ISSN

0094-2405 (print)  

Publisher

$abstract.society.value is a Member of CrossRef American Association of Physicists in Medicine

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