Application of parallel imaging to fMRI at 7 tesla utilizing a high 1D reduction factor

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Abstract

Gradient-echo EPI, blood oxygenation level-dependent (BOLD) functional MRI (fMRI) using parallel imaging (PI) is demonstrated at 7 Tesla with 16 channels, a fourfold 1D reduction factor (R), and fourfold maximal aliasing. The resultant activation detection in finger-tapping fMRI studies was robust, in full agreement with expected activation patterns based on prior knowledge, and with functional maps generated from full field of view (FOV) coverage of k-space using segmented acquisition. In all aspects the functional maps acquired with PI outperformed segmented coverage of full k-space. With a 1D R of 4, fMRI activation based on PI had higher statistical significance, up to 1.6-fold in an individual case and 1.25 ± .25 (SD) fold when averaged over six studies, compared to four-segment/full-FOV data in which the √R reduction in the image signal-to-noise ratio (SNR) due to k-space undersampling was compensated for by acquiring additional repetitions of the undersampled k-space. When this compensation for √R loss in SNR was not performed, the effect of PI was determined by the ratio of physiologically induced vs. intrinsic (thermal) noise in the fMRI time series and the extent to which physiological "noise" was amplified by the use of segmentation in the full-FOV data. The results demonstrate that PI is particularly beneficial at this ultrahigh field strength, where both the intrinsic image SNR and temporal signal fluctuations due to physiological processes are large.

Original languageEnglish (US)
Pages (from-to)118-129
Number of pages12
JournalMagnetic resonance in medicine
Volume56
Issue number1
DOIs
StatePublished - Jul 1 2006

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Signal-To-Noise Ratio
Magnetic Resonance Imaging
Noise
Physiological Phenomena
R Factors
Fingers
Hot Temperature

Keywords

  • 7 Tesla
  • Parallel imaging
  • Sensitivity calibration
  • fMRI
  • k-space

Cite this

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abstract = "Gradient-echo EPI, blood oxygenation level-dependent (BOLD) functional MRI (fMRI) using parallel imaging (PI) is demonstrated at 7 Tesla with 16 channels, a fourfold 1D reduction factor (R), and fourfold maximal aliasing. The resultant activation detection in finger-tapping fMRI studies was robust, in full agreement with expected activation patterns based on prior knowledge, and with functional maps generated from full field of view (FOV) coverage of k-space using segmented acquisition. In all aspects the functional maps acquired with PI outperformed segmented coverage of full k-space. With a 1D R of 4, fMRI activation based on PI had higher statistical significance, up to 1.6-fold in an individual case and 1.25 ± .25 (SD) fold when averaged over six studies, compared to four-segment/full-FOV data in which the √R reduction in the image signal-to-noise ratio (SNR) due to k-space undersampling was compensated for by acquiring additional repetitions of the undersampled k-space. When this compensation for √R loss in SNR was not performed, the effect of PI was determined by the ratio of physiologically induced vs. intrinsic (thermal) noise in the fMRI time series and the extent to which physiological {"}noise{"} was amplified by the use of segmentation in the full-FOV data. The results demonstrate that PI is particularly beneficial at this ultrahigh field strength, where both the intrinsic image SNR and temporal signal fluctuations due to physiological processes are large.",
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