MR Susceptibility Weighted Imaging And Its Clinical Applications

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2007-08-23T01:56:11Z

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Biomedical Engineering

Abstract

Susceptibility Weighted Imaging (SWI) is a new T2* weighted Gradient Echo sequence that exploits the magnetic properties of tissues due to local inhomogeneities in the magnetic field. This technique was originally called 'High-Resolution Blood oxygen level dependent Venography' which, as the name suggests provides an increased visibility of the venous vasculature in the brain, including the minute vessels not seen on conventional imaging techniques. Since its potential is not restricted to venography, it was renamed 'Susceptibility Weighted Imaging ' due to its contrast mechanism being the susceptibility differences between two tissues. The essential feature in this technique is to tap the paramagnetic properties, specifically those of the deoxygenated hemoglobin, in order to make deoxygenated hemoglobin increasingly visible especially on the MRI phase images. To date, SWI is not a scanner derived image and remains to be a post-processed image reconstruction technique using various intermediate images (k-space, real and imaginary images). The processing techniques include filtering the phase data to remove the low frequency components in the background field, generation of a phase mask to enhance the susceptibility contrast seen in the phase images followed by multiplication of this phase mask with the magnitude images to make these phase variations prominent in the resultant susceptibility weighted image. The study also emphasizes the clinical potentials of this high resolution imaging technique, particularly in the case of Diffuse Axonal Injury (DAI) in Traumatic Brain Injury. SWI holds clinical significance in the above mentioned pathology because studies proved that hemorrhagic lesions visible in SWI are significantly higher than those detected by conventional imaging techniques. These findings are primarily because susceptibility weighted imaging is capable of detecting microhemorrhages which are undetected in the case of CT scans and other current MR imaging techniques. This could help in SWI contributing to effective and efficient evaluation of DAI, bringing about a correlation between prognosis and outcome.

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