Achieving sufficient spectral bandwidth for volumetric 1 H echo‐planar spectroscopic imaging at 4 Tesla

PurposeFull‐slice magnetic resonance spectroscopic imaging at ≥7 T is especially vulnerable to lipid contaminations arising from regions close to the skull. This contamination can be mitigated by improving the point spread function via higher spatial resolution sampling and k‐space filtering, but this prolongs scan times and reduces the signal‐to‐noise ratio (SNR) efficiency. Currently applied parallel imaging methods accelerate magnetic resonance spectroscopic imaging scans at 7T, but increase lipid artifacts and lower SNR‐efficiency further. In this study, we propose an SNR‐efficient spatial‐spectral sampling scheme using concentric circle echo planar trajectories (CONCEPT), which was adapted to intrinsically acquire a Hamming‐weighted k‐space, thus termed density‐weighted‐CONCEPT. This minimizes voxel bleeding, while preserving an optimal SNR.Theory and MethodsTrajectories were theoretically derived and verified in phantoms as well as in the human brain via measurements of five volunteers (single‐slice, field‐of‐view 220 × 220 mm2, matrix 64 × 64, scan time 6 min) with free induction decay magnetic resonance spectroscopic imaging. Density‐weighted‐CONCEPT was compared to (a) the originally proposed CONCEPT with equidistant circles (here termed e‐CONCEPT), (b) elliptical phase‐encoding, and (c) 5‐fold Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase‐encoding.ResultsBy intrinsically sampling a Hamming‐weighted k‐space, density‐weighted‐CONCEPT removed Gibbs‐ringing artifacts and had in vivo +9.5%, +24.4%, and +39.7% higher SNR than e‐CONCEPT, elliptical phase‐encoding, and the Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase‐encoding (all P < 0.05), respectively, which lead to improved metabolic maps.ConclusionDensity‐weighted‐CONCEPT provides clinically attractive full‐slice high‐resolution magnetic resonance spectroscopic imaging with optimal SNR at 7T. Magn Reson Med 79:2874–2885, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

“…EPSI at

B_{0} = 3

Section: Discussionmentioning

confidence: 99%

\leq 10

) 15 and lipid contamination is aggravated, which calls for additional lipid suppression techniques 2, 18, 19.…”

Section: Introductionmentioning

confidence: 99%

Density‐weighted concentric circle trajectories for high resolution brain magnetic resonance spectroscopic imaging at 7T

Hingerl

Bogner

Moser

et al. 2017

“…Accordingly, image reconstruction can be done by estimating C m and C ns , which can be formulated into the following regularized least-squares problem [7] where measures the data consistency and Ψ 1 (·) and Ψ 1 (·) represent the regularization functionals for metabolite and nuisance signals, respectively, with regularization parameters λ 1 and λ 2 . Many choices can be made for Ψ 1,2 (·) to incorporate prior information about the unknown spatiospectral/spatiotemporal function (e.g., those in (19,23)).…”

Section: Image Reconstructionmentioning

confidence: 99%

“…A number of efficient algorithms can be used to solve the problem in Eq. [7] with the non-quadratic regularization in Eq. [8].…”

Section: Image Reconstructionmentioning

confidence: 99%

“…Significant efforts have been made in the last several decades to achieve fast, high-resolution MR spectroscopic imaging (MRSI), through the development of fast sequences (1)(2)(3)(4)(5)(6)(7)(8)(9)(10) and advanced image reconstruction methods (11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25). SPICE (SPectroscopic Imaging by exploiting spatiospectral CorrElation) is a relatively new approach that we recently proposed to achieve high-resolution MRSI with good signal-to-noise ratio (SNR) and speed (26).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

High‐resolution ¹H‐MRSI of the brain using SPICE: Data acquisition and image reconstruction

Lam

Clifford

et al. 2016

Purpose-To develop data acquisition and image reconstruction methods to enable highresolution 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 Methods-SPICE 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 (CSI)/echo-planar spectroscopic imaging (EPSI) sequence for two-dimensional (2D) MRSI and a dual-density, dual-speed EPSI sequence for three-dimensional (3D) MRSI. For image reconstruction, we propose a method that can determine the subspace structure and the highresolution spatiospectral reconstruction from the hybrid data sets generated by the proposed sequences, incorporating field inhomogeneity correction and edge-preserving regularization.Results-Phantom 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 inplane and 4 mm through-plane resolution in about 25 min.Conclusion-Special data acquisition and reconstruction methods have been developed for highresolution 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.

Spectral phase‐corrected GRAPPA reconstruction of three‐dimensional echo‐planar spectroscopic imaging (3D‐EPSI)

Zhu

Ebel

et al. 2007

Self Cite

MR spectroscopic (MRS) images from a large volume of brain can be obtained using a 3D echo-planar spectroscopic imaging (3D-EPSI) sequence. However, routine applications of 3D-EPSI are still limited by a long scan time. In this communication, a new approach termed "spectral phase-corrected generalized autocalibrating partially parallel acquisitions" (SPC-GRAPPA) is introduced for the reconstruction of 3D-EPSI data to accelerate data acquisition while preserving the accuracy of quantitation of brain metabolites. In SPC-GRAPPA, voxel-by-voxel spectral phase alignment between metabolite 3D-EPSI from individual coil elements is performed in the frequency domain, utilizing the whole spectrum from interleaved water reference 3D-EPSI for robust estimation of the zero-order phase correction. The performance of SPC-GRAPPA was compared with that of fully encoded 3D-EPSI and conventional GRAPPA. Analysis of whole-brain 3D-EPSI data reconstructed by SPC-GRAPPA demonstrates that SPC-GRAPPA with an acceleration factor of 1. Key words: phase correction; partial parallel imaging; echoplanar spectroscopic imaging; brain metabolites; short echo time Volumetric echo-planar spectroscopic imaging (3D-EPSI) is currently the most efficient strategy to obtain 3D maps of brain metabolite distributions (1). Compared to conventional spectroscopic imaging, sampling efficiency is gained with EPSI by simultaneously encoding the spectral dimension together with one spatial dimension, thus reducing the time-consuming spatial encoding in spectroscopic imaging to two dimensions. Although the acquisition speed of 3D-EPSI is one order of magnitude faster than that of conventional spectroscopic imaging methods, applications of 3D-EPSI are still limited by relatively long scan times, especially when high spatial resolution is desired. With the advent of multichannel phased-array coils, faster acquisition has become possible with parallel imaging that requires fewer numbers of phase-encoding (PE) steps for image reconstruction, albeit at the expense of a reduced signal-to-noise ratio (SNR) (2). Parallel imaging was initially applied to 2D spectroscopic imaging employing the sensitivity encoding (SENSE) method (3,4). However, phase cancellations reduced metabolite signal and introduced artifacts (2). To avoid phase cancellation, coherent phase alignment between the EPSI data from the individual coils in a phased array is required. According to the Fourier shift theorem, the phase alignment can be done in either the time domain or the frequency domain. In the time domain, phase alignment can be done by "time-shifting" the free induction decay (FID) signals from different coil elements until the FID signals start with the same phase, which is usually measured from the first sampling point of the FID signal. In the frequency domain, phase alignment can be achieved by maximizing the integral of the real component of each spectrum (5,6) from the different coil elements. Such spectral phase correction (SPC) for resonance peaks, which takes the entire 1 H sp...