172 research outputs found
Learning-based Single-step Quantitative Susceptibility Mapping Reconstruction Without Brain Extraction
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. 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. This inaccuracy has thus hindered the application of QSM for measuring
the susceptibility of tissues near the brain edges, e.g., quantifying cortical
layers and generating superficial venography. To address these challenges, we
propose a learning-based QSM reconstruction method that directly estimates the
magnetic susceptibility from total phase images without the need for brain
extraction and background phase removal, referred to as autoQSM. The neural
network has a modified U-net structure and is trained using QSM maps computed
by a two-step QSM method. 209 healthy subjects with ages ranging from 11 to 82
years were employed for patch-wise network training. The network was validated
on data dissimilar to the training data, e.g. in vivo mouse brain data and
brains with lesions, which suggests that the network has generalized and
learned the underlying mathematical relationship between magnetic field
perturbation and magnetic susceptibility. 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 its potential for
future applications.Comment: 26 page
Quantitative Susceptibility Mapping: Contrast Mechanisms and Clinical Applications.
Quantitative susceptibility mapping (QSM) is a recently developed MRI technique for quantifying the spatial distribution of magnetic susceptibility within biological tissues. It first uses the frequency shift in the MRI signal to map the magnetic field profile within the tissue. The resulting field map is then used to determine the spatial distribution of the underlying magnetic susceptibility by solving an inverse problem. The solution is achieved by deconvolving the field map with a dipole field, under the assumption that the magnetic field is a result of the superposition of the dipole fields generated by all voxels and that each voxel has its unique magnetic susceptibility. QSM provides improved contrast to noise ratio for certain tissues and structures compared to its magnitude counterpart. More importantly, magnetic susceptibility is a direct reflection of the molecular composition and cellular architecture of the tissue. Consequently, by quantifying magnetic susceptibility, QSM is becoming a quantitative imaging approach for characterizing normal and pathological tissue properties. This article reviews the mechanism generating susceptibility contrast within tissues and some associated applications
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Imaging the Centromedian Thalamic Nucleus Using Quantitative Susceptibility Mapping.
The centromedian (CM) nucleus is an intralaminar thalamic nucleus that is considered as a potentially effective target of deep brain stimulation (DBS) and ablative surgeries for the treatment of multiple neurological and psychiatric disorders. However, the structure of CM is invisible on the standard T1- and T2-weighted (T1w and T2w) magnetic resonance images, which hamper it as a direct DBS target for clinical applications. The purpose of the current study is to demonstrate the use of quantitative susceptibility mapping (QSM) technique to image the CM within the thalamic region. Twelve patients with Parkinson's disease, dystonia, or schizophrenia were included in this study. A 3D multi-echo gradient recalled echo (GRE) sequence was acquired together with T1w and T2w images on a 3-T MR scanner. The QSM image was reconstructed from the GRE phase data. Direct visual inspection of the CM was made on T1w, T2w, and QSM images. Furthermore, the contrast-to-noise ratios (CNRs) of the CM to the adjacent posterior part of thalamus on T1w, T2w, and QSM images were compared using the one-way analysis of variance (ANOVA) test. QSM dramatically improved the visualization of the CM nucleus. Clear delineation of CM compared to the surroundings was observed on QSM but not on T1w and T2w images. Statistical analysis showed that the CNR on QSM was significantly higher than those on T1w and T2w images. Taken together, our results indicate that QSM is a promising technique for improving the visualization of CM as a direct targeting for DBS surgery
Quantitative Susceptibility Mapping by Inversion of a Perturbation Field Model: Correlation With Brain Iron in Normal Aging
There is increasing evidence that iron deposition occurs in specific regions of the brain in normal aging and neurodegenerative disorders such as Parkinson's, Huntington's, and Alzheimer's disease. Iron deposition changes the magnetic susceptibility of tissue, which alters the MR signal phase, and allows estimation of susceptibility differences using quantitative susceptibility mapping (QSM). We present a method for quantifying susceptibility by inversion of a perturbation model, or “QSIP.” The perturbation model relates phase to susceptibility using a kernel calculated in the spatial domain, in contrast to previous Fourier-based techniques. A tissue/air susceptibility atlas is used to estimate B[subscript 0] inhomogeneity. QSIP estimates in young and elderly subjects are compared to postmortem iron estimates, maps of the Field-Dependent Relaxation Rate Increase, and the L1-QSM method. Results for both groups showed excellent agreement with published postmortem data and in vivo FDRI: statistically significant Spearman correlations ranging from Rho=0.905 to Rho=1.00 were obtained. QSIP also showed improvement over FDRI and L1-QSM: reduced variance in susceptibility estimates and statistically significant group differences were detected in striatal and brainstem nuclei, consistent with age-dependent iron accumulation in these regions.National Institutes of Health (U.S.) (Grant P41EB015902)National Institutes of Health (U.S.) (Grant P41RR013218)National Institutes of Health (U.S.) (Grant P41EB015898)National Institutes of Health (U.S.) (Grant P41RR019703)National Institutes of Health (U.S.) (Grant T32EB0011680-06)National Institutes of Health (U.S.) (Grant K05AA017168)National Institutes of Health (U.S.) (Grant R01AA012388
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Magnetic Resonance Imaging of Susceptibility Effects in Carotid Atherosclerosis
This thesis explores the use of susceptibility-weighted imaging (SWI) and quantitative susceptibility mapping (QSM), to characterize carotid artery plaques with and without the use of ultrasmall superparamagnetic iron oxide (USPIO) nanoparticle contrast agents. The overall hypothesis is that QSM can serve to differentiate carotid artery plaque features of different susceptibility and provide a positive contrast mechanism for imaging the uptake of USPIOs.
Chapter 1 describes the pathophysiology of carotid atherosclerosis. Vulnerable plaques, i.e. those at risk of rupture, can be characterized by the presence of a lipid rich necrotic core (LRNC), intraplaque haemorrhage (IPH), and inflammation. In addition, plaques may develop calcifications that may be protective of rupture. The chapter describes the established multi-contrast imaging protocols used for characterizing plaques. Furthermore, the use of USPIO-contrast agents to image inflammation is described.
Chapter 2 describes the physical principles of MR image generation including the sensitivity to magnetic susceptibility. The principles of T2*w imaging, and susceptibility weighted imaging (SWI) are explained.
Chapter 3 reviews the principles and post-processing steps involved in commonly used algorithms for QSM in terms of the underlying physical and mathematical principles which are then demonstrated in the form of numerical simulations.
Chapter 4 presents the application of SWI to a group of patients who underwent USPIO enhanced MRI on a 1.5T MRI system. Images were acquired prior to infusion and 48 hours post infusion. SWI and gradient echo phase images were used to depict the field inhomogeneities generated by diamagnetic and paramagnetic materials within the plaques, calcification and USPIO-uptake. These results were then compared to a conventional carotid multi-contrast protocol, which includes R2*-mapping and T2*w imaging, and, where available, CT and histology.
In chapter 5 QSM is performed in the carotid artery wall of a cohort of normal volunteers on a 1.5T MRI system. Unlike the brain, the neck contains fat which can cause severe errors in the field estimate, which propagate into the susceptibility map.
Therefore, QSM was combined with water-fat separation for application in the neck to correct for these artifacts. This correctly estimated a high fat-fraction in fatty tissue in the neck and allowed for a detailed depiction of the anatomy of healthy volunteers. The susceptibility value measured in fatty tissue agreed with literature values.
Chapter 6 applies QSM with water-fat separation to a subset of the patient group on a 1.5T MRI system. On pre-contrast scans QSM successfully identified calcification as diamagnetic tissue and the water-fat separation identified a lipid core. On the post-contrast susceptibility maps, USPIO-uptake was identified as hyperintense signal. This allows QSM to provide quantitative contrast in carotid imaging that can identify multiple features simultaneously and to simplify the imaging of USPIO-contrast. The results were confirmed using the multi-contrast carotid MRI protocol and, where available, histology and CT.
Chapter 7 discusses the limitations of the current studies and the potential future improvements of the current methodology in terms of MR acquisition, post-processing algorithms and MR protocols.
Future studies could serve to further evaluate the potential of QSM in carotid imaging and use it as a novel tool to quantify USPIO uptake in atherosclerotic carotid arteries
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