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      Determination of detection sensitivity for cerebral microbleeds using susceptibility-weighted imaging : Detection and Quantification of CMBs

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          <p class="first" id="P1">Cerebral microbleeds (CMBs) are small chronic brain hemorrhages which are likely caused by structural abnormalities of the small vessels of the brain. Owing to the paramagnetic properties of blood degradation products, CMBs can be detected in vivo by using specific magnetic resonance imaging (MRI) sequences. Susceptibility weighted imaging (SWI) can be used to not only detect iron changes and CMBs, but also differentiate them from calcifications, both of which may be important MR based biomarkers for neurodegenerative diseases. Moreover, SWI can be used to quantify the iron in CMBs. SWI and gradient echo (GE) imaging are the two most common methods to detect iron deposition and CMBs. This study provides a comprehensive analysis for the number of voxels detected in the presence of a CMB on gradient-echo magnitude, phase and SWI composite images as a function of resolution, signal-to-noise, echo time, field strength and susceptibility using <i>in silico</i> experiments. Susceptibility maps were used to quantify the bias in effective susceptibility value and to determine the optimal echo time (TE) for CMB quantification. We observed a non-linear trend with susceptibility for CMB detection from the magnitude images while a linear trend with that from the phase and SWI composite images. The optimal TE value for CMB quantification was found to be 3ms at 7T, 7ms at 3T and 14ms at 1.5T for a CMB of 1 voxel diameter with an SNR of 20:1. The simulations of signal loss and detectability are used to generate theoretical formulae for predictions. </p>

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          Susceptibility weighted imaging (SWI).

          Susceptibility differences between tissues can be utilized as a new type of contrast in MRI that is different from spin density, T1-, or T2-weighted imaging. Signals from substances with different magnetic susceptibilities compared to their neighboring tissue will become out of phase with these tissues at sufficiently long echo times (TEs). Thus, phase imaging offers a means of enhancing contrast in MRI. Specifically, the phase images themselves can provide excellent contrast between gray matter (GM) and white matter (WM), iron-laden tissues, venous blood vessels, and other tissues with susceptibilities that are different from the background tissue. Also, for the first time, projection phase images are shown to demonstrate tissue (vessel) continuity. In this work, the best approach for combining magnitude and phase images is discussed. The phase images are high-pass-filtered and then transformed to a special phase mask that varies in amplitude between zero and unity. This mask is multiplied a few times into the original magnitude image to create enhanced contrast between tissues with different susceptibilities. For this reason, this method is referred to as susceptibility-weighted imaging (SWI). Mathematical arguments are presented to determine the number of phase mask multiplications that should take place. Examples are given for enhancing GM/WM contrast and water/fat contrast, identifying brain iron, and visualizing veins in the brain. Copyright 2004 Wiley-Liss, Inc.
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            Susceptibility-weighted imaging: technical aspects and clinical applications, part 2.

            Susceptibility-weighted imaging (SWI) has continued to develop into a powerful clinical tool to visualize venous structures and iron in the brain and to study diverse pathologic conditions. SWI offers a unique contrast, different from spin attenuation, T1, T2, and T2* (see Susceptibility-Weighted Imaging: Technical Aspects and Clinical Applications, Part 1). In this clinical review (Part 2), we present a variety of neurovascular and neurodegenerative disease applications for SWI, covering trauma, stroke, cerebral amyloid angiopathy, venous anomalies, multiple sclerosis, and tumors. We conclude that SWI often offers complementary information valuable in the diagnosis and potential treatment of patients with neurologic disorders.
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              Magnetic susceptibility mapping of brain tissue in vivo using MRI phase data.

              Phase images in susceptibility-weighted MRI of brain provide excellent contrast. However, the phase is affected by tissue geometry and orientation relative to the main magnetic field (B(0)), and phase changes extend beyond areas of altered susceptibility. Magnetic susceptibility, on the other hand, is an intrinsic tissue property, closely reflecting tissue composition. Therefore, recently developed inverse Fourier-based methods were applied to calculate susceptibility maps from high-resolution phase images acquired at a single orientation at 7 T in the human brain (in vivo and fixed) and at 11.7 T in fixed marmoset brain. In susceptibility images, the contrast of cortical layers was more consistent than in phase images and was independent of the structures' orientation relative to B(0). The contrast of iron-rich deep-brain structures (red nucleus and substantia nigra) in susceptibility images agreed more closely with iron-dominated R(2) (*) images than the phase image contrast, which extended outside the structures. The mean susceptibility in these regions was significantly correlated with their estimated iron content. Susceptibility maps calculated using this method overcome the orientation-dependence and non-locality of phase image contrast and seem to reflect underlying tissue composition. Susceptibility images should be easier to interpret than phase images and could improve our understanding of the sources of susceptibility contrast. (c) 2009 Wiley-Liss, Inc.

                Author and article information

                NMR in Biomedicine
                NMR Biomed.
                April 2017
                April 2017
                May 20 2016
                : 30
                : 4
                : e3551
                [1 ]The MRI Institute for Biomedical Research; Waterloo; ON Canada
                [2 ]Department of Radiology; Wayne State University; Detroit MI USA
                [3 ]Imaging, Integrated Science and Technology; AbbVie Inc.; North Chicago, IL USA
                © 2016






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