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Simultaneous QSM and metabolic imaging of the brain using SPICE.

ABSTRACT: PURPOSE:To map brain metabolites and tissue magnetic susceptibility simultaneously using a single three-dimensional 1 H-MRSI acquisition without water suppression. METHODS:The proposed technique builds on a subspace imaging method called spectroscopic imaging by exploiting spatiospectral correlation (SPICE), which enables ultrashort echo time (TE)/short pulse repetition time (TR) acquisitions for 1 H-MRSI without water suppression. This data acquisition scheme simultaneously captures both the spectral information of brain metabolites and the phase information of the water signals that is directly related to tissue magnetic susceptibility variations. In extending this scheme for simultaneous QSM and metabolic imaging, we increase k-space coverage by using dual density sparse sampling and ramp sampling to achieve spatial resolution often required by QSM, while maintaining a reasonable signal-to-noise ratio (SNR) for the spatiospectral data used for metabolite mapping. In data processing, we obtain high-quality QSM from the unsuppressed water signals by taking advantage of the larger number of echoes acquired and any available anatomical priors; metabolite spatiospectral distributions are reconstructed using a union-of-subspaces model. RESULTS:In vivo experimental results demonstrate that the proposed method can produce susceptibility maps at a resolution higher than 1.8?×?1.8?×?2.4?mm3 along with metabolite spatiospectral distributions at a nominal spatial resolution of 2.4?×?2.4?×?2.4?mm3 from a single 7-min MRSI scan. The estimated susceptibility values are consistent with those obtained using the conventional QSM method with 3D multi-echo gradient echo acquisitions. CONCLUSION:This article reports a new capability for simultaneous susceptibility mapping and metabolic imaging of the brain from a single 1 H-MRSI scan, which has potential for a wide range of applications. Magn Reson Med 79:13-21, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

SUBMITTER: Peng X

PROVIDER: S-EPMC5744903 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Simultaneous QSM and metabolic imaging of the brain using SPICE.

Peng Xi X Lam Fan F Li Yudu Y Clifford Bryan B Liang Zhi-Pei ZP

Magnetic resonance in medicine 20171024 1

<h4>Purpose</h4>To map brain metabolites and tissue magnetic susceptibility simultaneously using a single three-dimensional <sup>1</sup> H-MRSI acquisition without water suppression.<h4>Methods</h4>The proposed technique builds on a subspace imaging method called spectroscopic imaging by exploiting spatiospectral correlation (SPICE), which enables ultrashort echo time (TE)/short pulse repetition time (TR) acquisitions for <sup>1</sup> H-MRSI without water suppression. This data acquisition schem ...[more]

PMID: 29067730

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Project description:PurposeTo develop data acquisition and image reconstruction methods to enable high-resolution (1) H MR spectroscopic imaging (MRSI) of the brain, using the recently proposed subspace-based spectroscopic imaging framework called SPICE (SPectroscopic Imaging by exploiting spatiospectral CorrElation).Theory and methodsSPICE is characterized by the use of a subspace model for both data acquisition and image reconstruction. For data acquisition, we propose a novel spatiospectral encoding scheme that provides hybrid data sets for determining the subspace structure and for image reconstruction using the subspace model. More specifically, we use a hybrid chemical shift imaging /echo-planar spectroscopic imaging sequence for two-dimensional (2D) MRSI and a dual-density, dual-speed echo-planar spectroscopic imaging sequence for three-dimensional (3D) MRSI. For image reconstruction, we propose a method that can determine the subspace structure and the high-resolution spatiospectral reconstruction from the hybrid data sets generated by the proposed sequences, incorporating field inhomogeneity correction and edge-preserving regularization.ResultsPhantom and in vivo brain experiments were performed to evaluate the performance of the proposed method. For 2D MRSI experiments, SPICE is able to produce high-SNR spatiospectral distributions with an approximately 3 mm nominal in-plane resolution from a 10-min acquisition. For 3D MRSI experiments, SPICE is able to achieve an approximately 3 mm in-plane and 4 mm through-plane resolution in about 25 min.ConclusionSpecial data acquisition and reconstruction methods have been developed for high-resolution (1) H-MRSI of the brain using SPICE. Using these methods, SPICE is able to produce spatiospectral distributions of (1) H metabolites in the brain with high spatial resolution, while maintaining a good SNR. These capabilities should prove useful for practical applications of SPICE. Magn Reson Med 76:1059-1070, 2016. © 2015 Wiley Periodicals, Inc.

Project description:ObjectiveThe goal of this study is to investigate the performance, merits and limitations of source imaging using intracranial EEG (iEEG) recordings and to compare its accuracy to the results of EEG source imaging. Accuracy in this study, is measured both by determining the location and inter-nodal connectivity of underlying brain networks.MethodsSystematic computer simulation studies are conducted to evaluate iEEG-based source imaging vs. EEG-based source imaging, and source imaging using both EEG and iEEG. To test the source imaging models, networks of inter-connected nodes (in terms of activity) are simulated. The location of the network nodes is randomly selected within a realistic geometry head model and a connectivity link is created among these nodes based on a multi-variate auto-regressive (MVAR) model. Then the forward problem is solved to calculate the potentials at the electrodes and noise (white and correlated) is added to these simulated potentials to simulate realistic measurements. Subsequently, the inverse problem is solved and an algorithm based on principle component analysis is performed on the estimated source activities to determine the location of the simulated network nodes. The activity of these nodes (over time), is then extracted, and used to estimate the connectivity links among the mentioned nodes using Granger causality analysis.ResultsSource imaging based on iEEG recordings may or may not improve the accuracy in localization, depending on the number and location of active nodes relative to iEEG electrodes and to other nodes within the network. However, our simulation results suggest that combining EEG and iEEG modalities (simultaneous scalp and intracranial recordings) can improve the imaging accuracy significantly.ConclusionsWhile iEEG source imaging is useful in estimating the exact location of sources near the iEEG electrodes, combining EEG and iEEG recordings can achieve a more accurate imaging due to the high spatial coverage of the scalp electrodes and the added near field information provided by the iEEG electrodes.SignificanceThe present results suggest the feasibility of localizing brain electrical sources from iEEG recordings and improving EEG source localization using simultaneous EEG and iEEG recordings to cover the whole brain. The hybrid EEG and iEEG source imaging can assist the clinicians when unequivocal decisions about determining the epileptogenic zone cannot be reached using a single modality.

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Simultaneous QSM and metabolic imaging of the brain using SPICE.

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Simultaneous QSM and metabolic imaging of the brain using SPICE.

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