Abstract

A novel sequence has been introduced that combines multiband imaging with a multi-echo acquisition for simultaneous high spatial resolution pseudo-continuous arterial spin labeling (ASL) and blood-oxygenation-level dependent (BOLD) echo-planar imaging (MBME ASL/BOLD). Resting-state connectivity in healthy adult subjects was assessed using this sequence. Four echoes were acquired with a multiband acceleration of four, in order to increase spatial resolution, shorten repetition time, and reduce slice-timing effects on the ASL signal. In addition, by acquiring four echoes, advanced multi-echo independent component analysis (ME-ICA) denoising could be employed to increase the signal-to-noise ratio (SNR) and BOLD sensitivity. Seed-based and dual-regression approaches were utilized to analyze functional connectivity. Cerebral blood flow (CBF) and BOLD coupling was also evaluated by correlating the perfusion-weighted timeseries with the BOLD timeseries. These metrics were compared between single echo (E2), multi-echo combined (MEC), multi-echo combined and denoised (MECDN), and perfusion-weighted (PW) timeseries. Temporal SNR increased for the MECDN data compared to the MEC and E2 data. Connectivity also increased, in terms of correlation strength and network size, for the MECDN compared to the MEC and E2 datasets. CBF and BOLD coupling was increased in major resting-state networks, and that correlation was strongest for the MECDN datasets. These results indicate our novel MBME ASL/BOLD sequence, which collects simultaneous high-resolution ASL/BOLD data, could be a powerful tool for detecting functional connectivity and dynamic neurovascular coupling during the resting state. The collection of more than two echoes facilitates the use of ME-ICA denoising to greatly improve the quality of resting state functional connectivity MRI.

Highlights

  • The impact and applications of resting-state functional connectivity magnetic resonance imaging continue to grow

  • Improved over the individual echo cases. tSNR was significantly higher for the multi-echo combined and denoised (MECDN) data (106 +/- 11) compared to the multi-echo combined (MEC) (69 +/- 12) and individual second echo (E2) data (47 +/- 9) and for the MEC data compared to the E2 data (MECDN > E2, P < 0.0001; MECDN > MEC, P = 0.0009; MEC > E2, P = 0.005)

  • Results of the Cerebral blood flow (CBF)/blood-oxygenation-level dependent (BOLD) coupling analysis are shown in Fig 8, which depicts the group CBF/ BOLD coupling for the E2, MEC, and MECDN datasets

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Summary

Objectives

The purpose of this study was to determine the feasibility of using the MBME ASL/BOLD sequence to detect resting-state connectivity; a small subject size was justified

Methods
Results
Conclusion
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