# Ultra-fast cerebral blood flow imaging for quantifying brain dynamics

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA RIVERSIDE · 2022 · $623,315

## Abstract

Abstract/Project Summary
Blood oxygenation level dependent (BOLD) fMRI is widely used in neuroscience studies. Technical
advancement in the recently years has enabled BOLD signals to be acquired at sub-second temporal
resolution, opening a new window for examining functional dynamics of the human brain, e.g. resting-
state fMRI. The BOLD signal originates from the mismatch between cerebral blood flow (CBF) and
metabolism changes, and is complex; it serves as an indirect measure of neural activities. A direct
observation of CBF changes can provide information that is more closely coupled to neural activities.
Arterial spin labeling (ASL) fMRI measures CBF changes noninvasively and quantitatively, therefore
may provide valuable dynamic information that is not readily measured with BOLD alone. Currently
the existing ASL fMRI methods are limited by low temporal resolution and signal-to-noise ratio (SNR),
mainly due to acquisition delays required for the labeled blood to reach the brain tissue. Velocity-
selective (VS) ASL shows promises in reducing the delays, but the existing labeling strategies are not
optimal for imaging CBF at high temporal resolution, such as below 2 s, or do not have sufficient
coverage of the brain. In this proof-of-concept development project, we propose a completely new VS
labeling strategy to overcome the problems of existing labeling methods, aiming for functional CBF
measurements with substantially increased temporal resolution (~ 1.5 s), SNR efficiency and a good
coverage. The ultra-fast and quantitative CBF imaging method developed in this project should help
advance our understanding of brain dynamics under healthy and diseased conditions, and may be an
imaging tool of choice for individual comparison and/or longitudinal studies.

## Key facts

- **NIH application ID:** 10481324
- **Project number:** 1R01EB033210-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA RIVERSIDE
- **Principal Investigator:** Jia Guo
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $623,315
- **Award type:** 1
- **Project period:** 2022-08-08 → 2026-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10481324

## Citation

> US National Institutes of Health, RePORTER application 10481324, Ultra-fast cerebral blood flow imaging for quantifying brain dynamics (1R01EB033210-01). Retrieved via AI Analytics 2026-05-29 from https://api.ai-analytics.org/grant/nih/10481324. Licensed CC0.

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