NeuroImage
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Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from MRI gradient-echo phase signal and typically requires several processing steps. These steps involve phase unwrapping, brain volume extraction, background phase removal and solving an ill-posed inverse problem relating the tissue phase to the underlying susceptibility distribution. The resulting susceptibility map is known to suffer from inaccuracy near the edges of the brain tissues, in part due to imperfect brain extraction, edge erosion of the brain tissue and the lack of phase measurement outside the brain. ⋯ Quantitative and qualitative comparisons were performed between autoQSM and other two-step QSM methods. AutoQSM was able to recover magnetic susceptibility of anatomical structures near the edges of the brain including the veins covering the cortical surface, spinal cord and nerve tracts near the mouse brain boundaries. The advantages of high-quality maps, no need for brain volume extraction, and high reconstruction speed demonstrate autoQSM's potential for future applications.
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Interest in white matter hyperintensities (WMH), a radiological biomarker of small vessel disease, is continuously increasing. This is, in most part, due to our better understanding of their association with various clinical disorders, such as stroke and Alzheimer's disease, and the overlapping pathology of WMH with these afflictions. Although post-mortem histological studies have reported various underlying pathophysiological substrates, in vivo research has not been specific enough to fully corroborate these findings. ⋯ Edema being an earlier contributing factor to the pathology, as expressed in the elevated water content values in NAWM with increasing severity. In the case of PWMH, an altered fluid dynamic and cerebrospinal fluid leakage exacerbate the changes. It was also found that the pathology, as monitored by qMRI, evolves faster in DWMH than in the PWMH following the severity.
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Edited magnetic resonance spectroscopic imaging (MRSI) is capable of mapping the distribution of low concentration metabolites such as gamma-aminobutyric acid (GABA) or and glutathione (GSH), but is prone to subtraction artifacts due to head motion or other instabilities. In this study, a retrospective motion compensation algorithm for edited MRSI is proposed. The algorithm identifies movement-affected signals by comparing residual water and lipid peaks between different transients recorded at the same point in k-space, and either phase corrects, replaces or removes affected spectra prior to spatial Fourier transformation. ⋯ The normalized Cho area was 5.14 times lower with motion compensation than without motion compensation. A 'removal-only' version of the technique is also shown to be promising in removing motion-corrupted artifacts in a GSH-edited MRSI acquisition acquired in 1 healthy subject. This study introduces a motion compensation technique and demonstrates that retrospective compensation in k-space is possible and significantly reduces the amount of subtraction artifacts in the resulting edited spectra.