on behalf of International Society for Magnetic Resonance in Medicine. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. Conclusion: In the human torso, at frequencies >49 MHz, data-driven combination is preferable to using computed coil sensitivities. These new apodized WSVD methods gave higher SNRs than other data-driven methods. 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). Results: Combined spectral SNRs from simulations, phantoms, and humans showed the same trends. Validation used phantoms and cardiac 31P spectra from five subjects at 3T. The combined spectra were then assessed in terms of their SNR. Methods: Radiofrequency fields from an array were simulated and used to make synthetic spectra. 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. 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.

We test whether data-driven combination methods are better than using computed coil sensitivities.

Purpose: Combining spectra from receive arrays, particularly X-nuclear spectra with low signal-to-noise ratios (SNRs), is challenging. Coil Combination for Receive Array Spectroscopy: Are Data-Driven Methods Superior to Methods Using Computed Field Maps?Ĭhristopher T.

Cst studio suite coil function