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Single-step quantitative susceptibility mapping with variational penalties.

ABSTRACT: Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from the gradient echo (GRE) phase signal through background phase removal and dipole inversion steps. Each of these steps typically requires the solution of an ill-posed inverse problem and thus necessitates additional regularization. Recently developed single-step QSM algorithms directly relate the unprocessed GRE phase to the unknown susceptibility distribution, thereby requiring the solution of a single inverse problem. In this work, we show that such a holistic approach provides susceptibility estimation with artifact mitigation and develop efficient algorithms that involve simple analytical solutions for all of the optimization steps. Our methods employ total variation (TV) and total generalized variation (TGV) to jointly perform the background removal and dipole inversion in a single step. Using multiple spherical mean value (SMV) kernels of varying radii permits high-fidelity background removal whilst retaining the phase information in the cortex. Using numerical simulations, we demonstrate that the proposed single-step methods reduce the reconstruction error by up to 66% relative to the multi-step methods that involve SMV background filtering with the same number of SMV kernels, followed by TV- or TGV-regularized dipole inversion. In?vivo single-step experiments demonstrate a dramatic reduction in dipole streaking artifacts and improved homogeneity of image contrast. These acquisitions employ the rapid three-dimensional echo planar imaging (3D EPI) and Wave-CAIPI (controlled aliasing in parallel imaging) trajectories for signal-to-noise ratio-efficient whole-brain imaging. Herein, we also demonstrate the multi-echo capability of the Wave-CAIPI sequence for the first time, and introduce an automated, phase-sensitive coil sensitivity estimation scheme based on a 4-s calibration acquisition. Copyright © 2016 John Wiley & Sons, Ltd.

SUBMITTER: Chatnuntawech I

PROVIDER: S-EPMC5179325 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Single-step quantitative susceptibility mapping with variational penalties.

Chatnuntawech Itthi I McDaniel Patrick P Cauley Stephen F SF Gagoski Borjan A BA Langkammer Christian C Martin Adrian A Grant P Ellen PE Wald Lawrence L LL Setsompop Kawin K Adalsteinsson Elfar E Bilgic Berkin B

NMR in biomedicine 20160622 4

Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from the gradient echo (GRE) phase signal through background phase removal and dipole inversion steps. Each of these steps typically requires the solution of an ill-posed inverse problem and thus necessitates additional regularization. Recently developed single-step QSM algorithms directly relate the unprocessed GRE phase to the unknown susceptibility distribution, thereby requiring the solution of ...[more]

PMID: 27332141

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Project description: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. This inaccuracy has thus hindered the application of QSM for measuring 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 generalized and learned the underlying mathematical relationship between magnetic field perturbation and magnetic susceptibility. 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.

Project description:BACKGROUND:Accurate measurement of the liver iron concentration (LIC) is needed to guide iron-chelating therapy for patients with transfusional iron overload. In this work, we investigate the feasibility of automated quantitative susceptibility mapping (QSM) to measure the LIC. PURPOSE:To develop a rapid, robust, and automated liver QSM for clinical practice. STUDY TYPE:Prospective. POPULATION:13 healthy subjects and 22 patients. FIELD STRENGTH/SEQUENCES:1.5 T and 3 T/3D multiecho gradient-recalled echo (GRE) sequence. ASSESSMENT:Data were acquired using a 3D GRE sequence with an out-of-phase echo spacing with respect to each other. All odd echoes that were in-phase (IP) were used to initialize the fat-water separation and field estimation (T2 *-IDEAL) before performing QSM. Liver QSM was generated through an automated pipeline without manual intervention. This IP echo-based initialization method was compared with an existing graph cuts initialization method (simultaneous phase unwrapping and removal of chemical shift, SPURS) in healthy subjects (n = 5). Reproducibility was assessed over four scanners at two field strengths from two manufacturers using healthy subjects (n = 8). Clinical feasibility was evaluated in patients (n = 22). STATISTICAL TESTS:IP and SPURS initialization methods in both healthy subjects and patients were compared using paired t-test and linear regression analysis to assess processing time and region of interest (ROI) measurements. Reproducibility of QSM, R2 *, and proton density fat fraction (PDFF) among the four different scanners was assessed using linear regression, Bland-Altman analysis, and the intraclass correlation coefficient (ICC). RESULTS:Liver QSM using the IP method was found to be ~5.5 times faster than SPURS (P < 0.05) in initializing T2 *-IDEAL with similar outputs. Liver QSM using the IP method were reproducibly generated in all four scanners (average coefficient of determination 0.95, average slope 0.90, average bias 0.002 ppm, 95% limits of agreement between -0.06 to 0.07 ppm, ICC 0.97). DATA CONCLUSION:Use of IP echo-based initialization enables robust water/fat separation and field estimation for automated, rapid, and reproducible liver QSM for clinical applications. LEVEL OF EVIDENCE:1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:725-732.

Project description:Background and purposeQuantitative susceptibility mapping using MR imaging can assess changes in brain tissue structure and composition. This report presents preliminary results demonstrating changes in tissue magnetic susceptibility after sports-related concussion.Materials and methodsLongitudinal quantitative susceptibility mapping metrics were produced from imaging data acquired from cohorts of concussed and control football athletes. One hundred thirty-six quantitative susceptibility mapping datasets were analyzed across 3 separate visits (24 hours after injury, 8 days postinjury, and 6 months postinjury). Longitudinal quantitative susceptibility mapping group analyses were performed on stability-thresholded brain tissue compartments and selected subregions. Clinical concussion metrics were also measured longitudinally in both cohorts and compared with the measured quantitative susceptibility mapping.ResultsStatistically significant increases in white matter susceptibility were identified in the concussed athlete group during the acute (24 hour) and subacute (day 8) period. These effects were most prominent at the 8-day visit but recovered and showed no significant difference from controls at the 6-month visit. The subcortical gray matter showed no statistically significant group differences. Observed susceptibility changes after concussion appeared to outlast self-reported clinical recovery metrics at a group level. At an individual subject level, susceptibility increases within the white matter showed statistically significant correlations with return-to-play durations.ConclusionsThe results of this preliminary investigation suggest that sports-related concussion can induce physiologic changes to brain tissue that can be detected using MR imaging-based magnetic susceptibility estimates. In group analyses, the observed tissue changes appear to persist beyond those detected on clinical outcome assessments and were associated with return-to-play duration after sports-related concussion.

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Single-step quantitative susceptibility mapping with variational penalties.

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Single-step quantitative susceptibility mapping with variational penalties.

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