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This study introduces a novel multiband multi-echo ASL/BOLD fMRI sequence, enhancing brain coverage and signal quality. The advanced denoising technique significantly improves both BOLD and ASL signals for better task-fMRI results.

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Area of Science:

  • Neuroimaging
  • Functional Magnetic Resonance Imaging (fMRI)
  • Biomedical Engineering

Background:

  • Simultaneous BOLD and ASL fMRI sequences typically use two echoes, limiting spatial resolution and brain coverage for ASL due to T1 decay.
  • Arterial Spin Labeling (ASL) is crucial for measuring cerebral blood flow (CBF), but its application in task-fMRI is constrained by signal quality and coverage limitations.

Purpose of the Study:

  • To introduce and evaluate a novel multiband acquisition with four echoes for simultaneous BOLD and pseudo-continuous ASL (pCASL) echo planar imaging (MBME ASL/BOLD).
  • To assess the efficacy of Multi-echo Independent Component Analysis (MEICA) for denoising both BOLD and ASL signals in a task-fMRI setting.
  • To investigate improvements in signal characteristics, brain coverage, and activation detection using the MBME ASL/BOLD sequence with MEICA denoising.

Main Methods:

  • Implementation of a multiband acceleration factor of four for simultaneous BOLD and pCASL acquisition (MBME ASL/BOLD).
  • Application of Multi-echo Independent Component Analysis (MEICA) for automated denoising of BOLD and ASL signals.
  • Evaluation of signal quality (tSNR, BOLD sensitivity) and activation statistics in a finger-tapping task fMRI experiment.

Main Results:

  • MEICA denoising significantly enhanced BOLD signal quality, increasing BOLD sensitivity, tSNR, and activation statistics compared to conventional single-echo BOLD.
  • Denoised perfusion-weighted (PW) ASL data exhibited improved tSNR and activation statistics over non-denoised data.
  • The MBME ASL/BOLD sequence with MEICA denoising improved CBF/BOLD coupling and overall data quality for whole-brain task-fMRI.

Conclusions:

  • The MBME ASL/BOLD sequence offers improved whole-brain coverage and data quality for simultaneous BOLD and ASL fMRI.
  • MEICA-based denoising is effective in enhancing both BOLD and ASL signals, leading to more robust task-fMRI results.
  • This advanced sequence and processing pipeline holds promise for more sensitive and reliable block-design task-fMRI studies.