The NMR phased array

Roemer, P. B.; Edelstein, William A.; Hayes, Cecil E.; Souza, S. P.; Mueller, O. M.

doi:10.1002/mrm.1910160203

Cited by 2,119 publications

(2,431 citation statements)

References 11 publications

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“…The acquisition time was circa

36 \min

. After unaliasing the simultaneously acquired slices channel by channel 38, 39, 40, SENSE1 multiple‐coil combination was applied 41 and the magnitude signal was stored. The dataset used in the study came from an adult male in the age group between 25 and 35 years.…”

Section: Methodsmentioning

confidence: 99%

Quantitative mapping of the per‐axon diffusion coefficients in brain white matter

Kaden

Kruggel

Alexander

2015

Magnetic Resonance in Med

209

296

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PurposeThis article presents a simple method for estimating the effective diffusion coefficients parallel and perpendicular to the axons unconfounded by the intravoxel fiber orientation distribution. We also call these parameters the per‐axon or microscopic diffusion coefficients.Theory and MethodsDiffusion MR imaging is used to probe the underlying tissue material. The key observation is that for a fixed b‐value the spherical mean of the diffusion signal over the gradient directions does not depend on the axon orientation distribution. By exploiting this invariance property, we propose a simple, fast, and robust estimator of the per‐axon diffusion coefficients, which we refer to as the spherical mean technique.ResultsWe demonstrate quantitative maps of the axon‐scale diffusion process, which has factored out the effects due to fiber dispersion and crossing, in human brain white matter. These microscopic diffusion coefficients are estimated in vivo using a widely available off‐the‐shelf pulse sequence featuring multiple b‐shells and high‐angular gradient resolution.ConclusionThe estimation of the per‐axon diffusion coefficients is essential for the accurate recovery of the fiber orientation distribution. In addition, the spherical mean technique enables us to discriminate microscopic tissue features from fiber dispersion, which potentially improves the sensitivity and/or specificity to various neurological conditions. Magn Reson Med, 2015. Magn Reson Med 75:1752–1763, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc.

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“…The acquisition time was circa

36 \min

Section: Methodsmentioning

confidence: 99%

Quantitative mapping of the per‐axon diffusion coefficients in brain white matter

Kaden

Kruggel

Alexander

2015

Magnetic Resonance in Med

209

296

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“…COMPOSER reconstructions were compared with the reconstructions from the following methods: 1) the complex sum of coil signals with no phase correction applied; 2) the Hammond method (an image‐based phase‐matching approach based on the subtraction of a channel‐dependent constant 22); 3) the Adaptive Combined method implemented on the scanner console (Syngo baseline version N4_VB17A_LATEST_20090307); 4) MCPC‐3D‐II 26, which calculates the phase offsets from a dual‐echo reference scan (using PRELUDE in 2D 38 to spatially unwrap separate channel data and interslice phase‐jump corrected as described in 26); 5) the Roemer method 9 (one subject only); and 6) the phase difference method (ie, the voxel‐by‐voxel Hermitian inner product (Eq. (3) in 39; see also 40; applied to the multi‐echo data from one subject).…”

Section: Methodsmentioning

confidence: 99%

“…Coil sensitivities can be determined using a homogeneous reference scan 9, 10. At 3 T and lower field strengths, this is generally acquired with a volume coil, such as a body coil.…”

Section: Introductionmentioning

confidence: 99%

Combining phase images from array coils using a short echo time reference scan (COMPOSER)

Robinson

Dymerska

Bogner

et al. 2015

Magnetic Resonance in Med

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PurposeTo develop a simple method for combining phase images from multichannel coils that does not require a reference coil and does not entail phase unwrapping, fitting or iterative procedures.Theory and MethodsAt very short echo time, the phase measured with each coil of an array approximates to the phase offset to which the image from that coil is subject. Subtracting this information from the phase of the scan of interest matches the phases from the coils, allowing them to be combined. The effectiveness of this approach is quantified in the brain, calf and breast with coils of diverse designs.ResultsThe quality of phase matching between coil elements was close to 100% with all coils assessed even in regions of low signal. This method of phase combination was similar in effectiveness to the Roemer method (which needs a reference coil) and was superior to the rival reference‐coil‐free approaches tested.ConclusionThe proposed approach—COMbining Phase data using a Short Echo‐time Reference scan (COMPOSER)—is a simple and effective approach to reconstructing phase images from multichannel coils. It requires little additional scan time, is compatible with parallel imaging and is applicable to all coils, independent of configuration. Magn Reson Med 77:318–327, 2017. © 2015 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine

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“…As a result of periodic k-space sampling with spacing Dk y between phase encode lines, f(x,y) ¼ f(x,y-FOV y ), where FOV y ¼ 1/Dk y is the full field-of-view in the phase encode direction. Equation (1) may be used to model a wide range of ghost mechanisms which create a periodic variation in k-space weighting, such as EPI acquisition or transient approach to interrupted steady state (21). However, the practical ability to eliminate ghosts using the parallel imaging method is set by the number and spacing of ghosts and the coil sensitivity profiles which together determine the performance of the inverse solution.…”

Section: Methods Theorymentioning

confidence: 99%

“…Phased array reconstruction (1), which employs coil sensitivity (B1) maps as weights for phased array combining, has been shown to optimize SNR, and, in addition, provide a degree of artifact suppression for alias ghosts. Phased array combining based on parallel imaging may be applied to cancel ghosts caused by a variety of distortion mechanisms, including distortions such as offresonance or local flow, which are space variant.…”

Section: Introduction Backgroundmentioning

confidence: 99%

Phased array ghost elimination

Kellman

McVeigh

2006

NMR Biomed.

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Parallel imaging may be applied to cancel ghosts caused by a variety of distortion mechanisms, including distortions such as off-resonance or local flow, which are space variant. Phased array combining coefficients may be calculated that null ghost artifacts at known locations based on a constrained optimization, which optimizes SNR subject to the nulling constraint. The resultant phased array ghost elimination (PAGE) technique is similar to the method known as sensitivity encoding (SENSE) used for accelerated imaging; however, in this formulation is applied to full field-of-view (FOV) images. The phased array method for ghost elimination may result in greater flexibility in designing acquisition strategies. For example, in multi-shot EPI applications ghosts are typically mitigated by the use of an interleaved phase encode acquisition order. An alternative strategy is to use a sequential, non-interleaved phase encode order and cancel the resultant ghosts using PAGE parallel imaging. Cancellation of ghosts by means of phased array processing makes sequential, non-interleaved phase encode acquisition order practical, and permits a reduction in repetition time, TR, by eliminating the need for echo-shifting. Sequential, non-interleaved phase encode order has benefits of reduced distortion due to offresonance, in-plane flow and EPI delay misalignment. Furthermore, the use of EPI with PAGE has inherent fat-water separation and has been used to provide off-resonance correction using a technique referred to as lipid elimination with an echo-shifting N/2-ghost acquisition (LEENA), and may further generalized using the multi-point Dixon method. Other applications of PAGE include cancelling ghosts which arise due to amplitude or phase variation during the approach to steady state. Parallel imaging requires estimates of the complex coil sensitivities. In vivo estimates may be derived by temporally varying the phase encode ordering to obtain a full k-space dataset in a scheme similar to the autocalibrating TSENSE method. This scheme is a generalization of the UNFOLD method used for removing aliasing in undersampled acquisitions. The more general scheme may be used to modulate each EPI ghost image to a separate temporal frequency as described in this paper.

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The NMR phased array

Cited by 2,119 publications

References 11 publications

Quantitative mapping of the per‐axon diffusion coefficients in brain white matter

Quantitative mapping of the per‐axon diffusion coefficients in brain white matter

Combining phase images from array coils using a short echo time reference scan (COMPOSER)

Phased array ghost elimination

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