# Optimization of Magnetic Resonance Fingerprintingusing Quantum Inspired Algorithms

> **NIH NIH R21** · CASE WESTERN RESERVE UNIVERSITY · 2022 · $201,250

## Abstract

Abstract
Magnetic resonance fingerprinting (MRF) is a quantitative technique that is able to produce maps of tissue
property values in a single and rapid acquisition. MRF has been shown to be sensitive to subtle changes in both
normal and diseased tissues in the brain, prostate, breast, and abdomen, yet increased sensitivity is desired for
clinical applications. A comprehensive optimization of the MRF acquisition is required to achieve higher
sensitivity and faster acquisitions. We propose to apply quantum inspired optimization (QIO) techniques to solve
the problem of MRF optimization. QIO methods are effective in handling large and nonconvex problems such as
this one, and we propose to apply these algorithms to optimize both sequence parameters such as flip angle,
repetition time, and echo time, as well as the sampling trajectories. The objective function to be optimized will
be designed to include characteristics such as signal magnitude, pattern matching metrics, and T1 and T2 errors.
Sequences will be tested in phantom and in vivo, and compared to current literature on MRF optimization. Such
a comprehensive optimization of MRF has not been performed, and by applying these novel computational
methods, we will achieve a MRF sequence that is faster and is more sensitive to changes in tissue properties
for the purposes of disease detection, characterization, and monitoring.

## Key facts

- **NIH application ID:** 10428464
- **Project number:** 5R21EB029658-02
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** Debra McGivney
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $201,250
- **Award type:** 5
- **Project period:** 2021-06-15 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10428464

## Citation

> US National Institutes of Health, RePORTER application 10428464, Optimization of Magnetic Resonance Fingerprintingusing Quantum Inspired Algorithms (5R21EB029658-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10428464. Licensed CC0.

---

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