Dataset Information

Coil combination for receive array spectroscopy: Are data-driven methods superior to methods using computed field maps?

ABSTRACT:

Purpose

Combining spectra from receive arrays, particularly X-nuclear spectra with low signal-to-noise ratios (SNRs), is challenging. We test whether data-driven combination methods are better than using computed coil sensitivities.

Theory

Several combination algorithms are recast into the notation of Roemer's classic formula, showing that they differ primarily in their estimation of coil receive sensitivities. This viewpoint reveals two extensions of the whitened singular-value decomposition (WSVD) algorithm, using temporal or temporal + spatial apodization to improve the coil sensitivities, and thus the combined spectral SNR.

Methods

Radiofrequency fields from an array were simulated and used to make synthetic spectra. These were combined with 10 algorithms. The combined spectra were then assessed in terms of their SNR. Validation used phantoms and cardiac (31) P spectra from five subjects at 3T.

Results

Combined spectral SNRs from simulations, phantoms, and humans showed the same trends. In phantoms, the combined SNR using computed coil sensitivities was lower than with WSVD combination whenever the WSVD SNR was >14 (or >11 with temporal apodization, or >9 with temporal + spatial apodization). These new apodized WSVD methods gave higher SNRs than other data-driven methods.

Conclusion

In the human torso, at frequencies ?49 MHz, data-driven combination is preferable to using computed coil sensitivities. Magn Reson, 2015. © 2015 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. Magn Reson Med 75:473-487, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

SUBMITTER: Rodgers CT

PROVIDER: S-EPMC4744755 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Coil combination for receive array spectroscopy: Are data-driven methods superior to methods using computed field maps?

Rodgers Christopher T CT Robson Matthew D MD

Magnetic resonance in medicine 20150328 2

<h4>Purpose</h4>Combining spectra from receive arrays, particularly X-nuclear spectra with low signal-to-noise ratios (SNRs), is challenging. We test whether data-driven combination methods are better than using computed coil sensitivities.<h4>Theory</h4>Several combination algorithms are recast into the notation of Roemer's classic formula, showing that they differ primarily in their estimation of coil receive sensitivities. This viewpoint reveals two extensions of the whitened singular-value d ...[more]

PMID: 25820303

Similar Datasets

Project description:Parallel imaging using phased array coils facilitates accelerated magnetic resonance imaging (MRI) and spectroscopy (MRS). Parallel data reconstruction requires the combination of data from individual coil elements, but limited combination algorithms currently exist for higher-order phased arrays and MRS data. Here, we present a systematic framework for identifying coil proximity-related signal inhomogeneities and noise levels in phased array coils that may affect sensitivity of parallel MRS. Single-voxel MRS was acquired in nine voxel positions in a brain spectroscopy phantom on a 3T whole-body MR scanner using commercially available 64-, 32-, and 20-channel phased array coils. Spectra produced by individual coil elements were combined using both a signal-to-noise ratio (SNR) threshold and based on the position of individual coil elements. SNR and metabolite Cramer-Rao lower bounds (CRLBs) from the final combined spectra were used as metrics to compare combination strategies and the effects of the phased array geometry and individual coil proximity. Comparisons were performed using one-way repeated measures ANOVA and post-hoc Tukey's range test (p<0.05). The 32-channel phased array coil produced the highest overall SNR compared to the 64-channel (p=0.0009) or 20-channel coils (p=0.003). Low SNR spectra from individual coil elements in the 64-channel coil can reduce the overall SNR when simply combining spectra from all elements. SNR varied significantly as a function of voxel position (F=58.3, p<0.0001) and SNR threshold for all phased arrays (p<0.05 for 64-, 32-, and 20-channel coils). Metabolite CRLBs were dependent on the combination strategy. We demonstrate the importance of the sampling voxel position and coil proximity on overall SNR in parallel MRS data acquisition, with significant SNR improvements after selectively filtering individual spectra based on pre-determined SNR thresholds which must be optimized for each phased array coil element and volume of interest.

Dataset Information

Coil combination for receive array spectroscopy: Are data-driven methods superior to methods using computed field maps?

Purpose

Theory

Methods

Results

Conclusion

Publications

Coil combination for receive array spectroscopy: Are data-driven methods superior to methods using computed field maps?

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets