# Improved detection of coronary artery disease in atrial fibrillation patients using ungated perfusion MRI methods

> **NIH NIH R01** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2024 · $538,794

## Abstract

Summary
Coronary artery disease (CAD) is a major healthcare problem that affects over 20 million Americans and costs
an estimated $82.8 billion each year. Atrial Fibrillation (AFIB) is a related epidemic that is estimated to affect 12
million Americans by 2030 with costs of ~$26 billion each year. Up to 38% of AFIB patients also have CAD and
they have a worse prognosis than patients with CAD alone. In order to prioritize and treat this vulnerable
population, clinicians need clear diagnostic tools that point toward specific treatments. Computed Tomography
Angiography (CTA) can be used to detect anatomical blockages in the coronaries; however, the hemodynamic
significance of the blockage cannot be accurately determined. Myocardial perfusion imaging is a proven tool to
detect and characterize CAD by determining the hemodynamic significance of coronary blockages on the
myocardium. While Single Photon Emission Computed Tomography (SPECT) perfusion imaging is widely used
in the U.S., the specificity of SPECT is low in patients with AFIB and CAD. Positron Emission Tomography (PET)
perfusion imaging is less widely available for CAD assessment but offers quantitative myocardial blood flow
maps and has superior image resolution compared to SPECT. Magnetic Resonance Imaging (MRI) offers
myocardial perfusion imaging with in-plane spatial resolution superior to PET imaging and without the ionizing
radiation. However, MR imaging has a few limitations in the context of AFIB patients, (1) MRI relies on good
and consistent ECG-gating signals to achieve diagnostic quality images. AFIB patients’ inconsistent R-R
intervals result in poor image quality with randomly changing cardiac phases for a given slice and hence are
often excluded from MR studies. (2) Quantifying MR perfusion images requires accurate measurement of the
arterial input function with a high temporal sampling rate, something challenging in AFIB patients due to changing
R-R intervals. (3) MR perfusion has limited slice coverage compared to SPECT and PET and is exacerbated in
AFIB patients. Increased slice coverage is desirable for improved confidence and accuracy in perfusion defect
assessment. A myocardial perfusion MRI method that (i) does not rely on ECG gating, (ii) has whole-heart
coverage and (iii) is quantitative would be extremely valuable in AFIB patients to detect CAD. Specific aims of
the project are (I) to develop a flow and motion insensitive steady-state (FAMISS) ungated quantitative
simultaneous multi-slice acquisition methods along with novel constrained and deep learning reconstruction
techniques for rapid, whole-heart quantitative perfusion MRI, (II) to rigorously compare the quantitative flow
values from the FAMISS framework with existing dual-bolus quantitative MRI measures, and (III) to validate the
FAMISS framework by comparing it to the gold standard for quantification, PET imaging, and the gold standard
for diagnostic accuracy using invasive fractional flow measures. Our team ...

## Key facts

- **NIH application ID:** 10853832
- **Project number:** 1R01HL172853-01
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Ganesh Adluru
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $538,794
- **Award type:** 1
- **Project period:** 2024-07-01 → 2028-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10853832

## Citation

> US National Institutes of Health, RePORTER application 10853832, Improved detection of coronary artery disease in atrial fibrillation patients using ungated perfusion MRI methods (1R01HL172853-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10853832. Licensed CC0.

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