# Longitudinal and quantitative MR plaque imaging for prediction of response to medical management in symptomatic intracranial atherosclerosis

> **NIH NIH R01** · CEDARS-SINAI MEDICAL CENTER · 2020 · $470,303

## Abstract

ABSTRACT
Intracranial atherosclerotic disease (ICAD) is one of the most common causes of ischemic stroke worldwide.
Despite intensive medical management, the current standard of care for secondary stroke prevention, the rate
of recurrent stroke is 13% in the first year and as high as 35% in certain populations by 2 years. Currently, the
initial and follow-up evaluations of these patients rely exclusively on assessments of clinical risk factors and, in
some circumstances, the degree of luminal stenosis on imaging. However, this strategy may overlook subtle
non-luminal changes within ICAD lesions. A tool that can directly probe atherosclerotic plaques and accurately
quantify longitudinal changes of plaque features may help early identify non-responsive patients in whom an
alternative therapy can be initiated. Magnetic resonance (MR) vessel wall imaging (VWI) has the potential to
fulfill this role because of its compacity to directly visualize the vessel wall and characterize plaque features.
However, there are several technical challenges associated with intracranial VWI: small size, tortuous course,
and deep sitting warrant a high-resolution and 3D imaging approach; multiple lesion sites require a large
imaging view; signals arising from neighboring blood and cerebrospinal fluid (CSF) need to be adequately
suppressed; relatively long imaging time and potential image corruption by patient motion; and lack of
dedicated plaque analysis tools particularly for 3D dataset. In this proposal, we will develop a reliable 3D VWI-
based MR plaque imaging (MRPI) strategy for prediction of response to medical management in symptomatic
ICAD. Specifically, we will first develop a whole-brain 3D VWI sequence with intracranial vessel-dedicated
motion compensation and motion-adaptive imaging acceleration (Aim1-Task1) and develop an automated
intracranial vessel wall (IVA) tool integrating 3D vessel wall segmentation and computational algorithms for
deriving quantitative plaque features (Aim1-Task2) followed by a validation study (Aim1-Task3). The validated
techniques will then be used in a cross-sectional study to determine the MRPI-derived quantitative plaque
features that are associated with ICAD lesions within the infarcted territory in patients with acute symptomatic
ICAD (Aim 2). We will finally conduct a longitudinal study to determine the capacity of longitudinal and
quantitative MRPI to predict response to medical management in symptomatic ICAD patients (Aim 3).
Successful completion of the project will validate the compacity of VWI-based MRPI to quantitatively
characterize ICAD and predict response to medical management in symptomatic ICAD patients. This will open
the door to future clinical trials investigating the role of MRPI in developing personalized management
paradigms and assessing new therapies.

## Key facts

- **NIH application ID:** 9898455
- **Project number:** 5R01HL147355-02
- **Recipient organization:** CEDARS-SINAI MEDICAL CENTER
- **Principal Investigator:** Zhaoyang Fan
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $470,303
- **Award type:** 5
- **Project period:** 2019-03-15 → 2020-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9898455

## Citation

> US National Institutes of Health, RePORTER application 9898455, Longitudinal and quantitative MR plaque imaging for prediction of response to medical management in symptomatic intracranial atherosclerosis (5R01HL147355-02). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/9898455. Licensed CC0.

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