# MR fingerprinting (MRF) perfusion imaging in cerebral vascular disease

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2020 · $479,869

## Abstract

Project Summary/Abstract:
 Ischemic stroke is a major health problem worldwide. In the United States, it is the fourth leading cause of
death and the leading cause of major disability. It is estimated that more than 700,000 Americans experience
new or recurrent stroke each year. Perfusion imaging plays an important role in virtually all stages of stroke
and related cerebrovascular diseases.
 At present, most clinical perfusion imaging requires the use of contrast agents, e.g. gadolinium (Gd) in
MRI. However, Gd perfusion MRI cannot be used or fails to be used in 10-20% of patients, due to a variety of
reasons, such as allergic reactions, low glomerular filtration rate, difficulties in placing an intravenous line that
is suitable for a rapid injection, or human errors in the timing of injection. Therefore, an alternative technique to
Gd-perfusion will benefit a substantial number of patients in clinical practice.
 Arterial Spin Labeling (ASL) MRI allows for non-contrast evaluation of cerebral blood flow (CBF). However,
in its current form, it cannot provide information equivalent to that obtained by contrast-agent-based perfusion
imaging. This is because CBF is of limited value in stroke delineation. The most useful parameter in Gd-
perfusion is Tmax or bolus-arrive-time (BAT), yet they cannot be measured reliably with current ASL methods.
 This application will develop a novel non-contrast perfusion technique that applies a new principle of MR
fingerprinting (MRF) to ASL. The major strength of this technique is that it allows for simultaneous estimations
of six parameters, CBF, BAT, T1, B1+, blood volume, and arterial travel time, in a single scan. Aim 1 is the
development of the MRF-ASL MRI technique. We will develop MRF-ASL sequence timing for efficient
encoding of perfusion parameters. We will also develop k-space undersampling strategies to obtain high
spatial resolution perfusion imaging without increasing echo-train length. We will conduct validation of the
technique using Gd-based perfusion MRI. Aim 2 of this project will develop a cloud-based ASL analysis
platform that can provide researchers and clinicians with an installation-free, operating-system independent
tool for ASL analysis (of MRF-ASL as well as all other types of ASL data). Our clinical team at Johns Hopkins
has a long-standing interest in mechanistic and therapeutic studies of sub-acute stroke. Therefore, Aim 3 of the
present project is to demonstrate the initial clinical utility of the technique in sub-acute stroke.
 Finally, it should be emphasized that, although the present project focuses on its clinical applications in
cerebrovascular diseases, the method developed also has important utility in other brain diseases, such
neurodegenerative diseases (e.g. Alzheimer’s, Parkinson’s, Huntington’s diseases), psychiatric diseases (e.g.
schizophrenia, depression, autism, ADHD), and tumor (primary and metastatic brain tumor). Thus, this
technique is expected to have a broad clini...

## Key facts

- **NIH application ID:** 9914352
- **Project number:** 5R01NS106711-03
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Hanzhang Lu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $479,869
- **Award type:** 5
- **Project period:** 2018-07-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9914352

## Citation

> US National Institutes of Health, RePORTER application 9914352, MR fingerprinting (MRF) perfusion imaging in cerebral vascular disease (5R01NS106711-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9914352. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*