# Improved Myocardial Perfusion Assessment using High-Performance Low-Field MRI

> **NIH NIH R21** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2022 · $247,500

## Abstract

PROJECT SUMMARY
This project will develop and evaluate an improved tool for myocardial perfusion assessment, that will be simple,
robust, and provide improved ability to resolve myocardial layers. We will achieve this by leveraging a novel
high-performance low-field (HPLF) magnetic resonance imaging (MRI) platform. Rationale: Coronary artery
disease (CAD) is the leading cause of death in the United States. Myocardial perfusion imaging is an essential
tool in patient management, and prognostication. Myocardial first-pass perfusion (FPP) MRI is the leading non-
invasive and radiation-free technique; however, it suffers from imaging artifact, limited coverage, and limited
ability to resolve myocardial layers. Resolving these issues will improve our ability to detect, manage, and
understand CAD. Innovation: We expect MRI FPP to greatly benefit from the HPLF MRI platform, because it
promises substantially reduced artifacts, and opportunities for improved spatial coverage, spatial resolution, and
temporal resolution. This project will leverage an HPLF system operating at 0.55 Tesla, to achieve improved
myocardial perfusion assessments, compared to what is possible today on 1.5 Tesla and 3 Tesla systems. We
will also apply novel real-time imaging techniques to avoid the need for an electrocardiogram (ECG) signal.
Approach: We will develop 0.55T whole-heart MRI FPP using two contrast generation sequences in combination
with stack-of-spiral (SOS) acquisition—one that uses ECG-gating and saturation recovery preparation, and one
ungated approach that retrospectively identifies stable phases. The SOS sampling pattern will be optimized for
CNR, boundary sharpness, and precision of myocardial perfusion measurements. Achieved spatial coverage,
spatial resolution, temporal resolution, and SNR/CNR will be measured using phantoms, 10 volunteer scans,
and 10 patient scans. The optimized HPLF methods will then be tested in a cohort of patients (N=20) with known
non-transmural scar, and compared with standard 3T multi-slice MRI FPP, to technically validate the ability to
detect non-transmural patterns of hypoperfusion, and to evaluate relative artifact levels. Broader Impact: This
project will provide 0.55T MRI FPP with reduced artifact and improved spatial information, compared to what is
possible at conventional MRI field strengths. In the long term, this approach could improve the diagnosis and
assessment of CAD. The imaging methods developed in this project will broadly benefit cardiac and dynamic
imaging on HPLF MRI platforms.

## Key facts

- **NIH application ID:** 10453361
- **Project number:** 1R21HL159533-01A1
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Krishna Shrinivas Nayak
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $247,500
- **Award type:** 1
- **Project period:** 2022-06-01 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10453361

## Citation

> US National Institutes of Health, RePORTER application 10453361, Improved Myocardial Perfusion Assessment using High-Performance Low-Field MRI (1R21HL159533-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10453361. Licensed CC0.

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