Quantitative Perfusion

1356310 - Diagnostic Accuracy of Global Stress Myocardial Blood Flow and Perfusion Reserve for the Detection of Obstructive Coronary Artery Disease: Preliminary Findings from the Multi-Center AQUA-MBF Study

Wednesday, January 25, 2023

Location: E-POSTER

Presenting Author(s)

SW

Shuo Wang, MD

Postdoctoral Research Associate
University of Virginia Health System
Charlottesville, Virginia, United States

Primary Author(s)

SW

Shuo Wang, MD

Postdoctoral Research Associate
University of Virginia Health System
Charlottesville, Virginia, United States

Co-Author(s)

HW

Haonan Wang, PhD

Lead Scientist, Cardiac MR
GE Healthcare, United States
PK

Paul J. J. Kim, MD

Cardiologist/Assistant Professor of Medicine
University of California, San Diego, California, United States
Ming- Yen Ng, BMBS FRCR FSCMR

Clinical Assistant Professor
The University of Hong Kong
Hong Kong, Hong Kong
Amita Singh, MD

Cardiologist
Central Dupage hospital
Chicago, Illinois, United States
MS

Mushtaq Saima, MD

Cardiologist
Centro Cardiologico Monzin, Italy
TS

Tsun Hei Sin

Research Assistant
The University of Hong Kong, Hong Kong
YT

Yuko Tada, MD, PhD

Bioinfo Analyst
University of California, San Diego
Mountain View, California, United States
EH

Elizabeth Hillier, PhD

Research Scientist
McGill University, University of Alberta
Montreal, Quebec, Canada
Michael Salerno, MD, PhD, MSc

Professor
Stanford University, California, United States
Gianluca Pontone, MD, PhD

Director of Peri Operative Cardiology and Cardiovascular Imaging Department
Centro Cardiologico Monzino
Milan, Lombardia, Italy
JU

Javier Urmeneta, MD

Cardiologist
Hospital Quironsalud Madrid, Spain
Ibrahim M. Saeed, MD, FSCMR

Cardiovascular Consultant
Virginia Heart / INOVA Heart and Vascular Institute
Oak Hill, Virginia, United States
HP

Hena Patel, MD

Caridiologist/Assistant Professor of Medicine
University of Chicago Medicine, Illinois, United States
CM

Christian Mariager, PhD, MSc

MR physicist
Aarhus University Hospital, Denmark
LG

Lars C. Gormsen, MD

professor
Aarhus University Hospital, Denmark
CL

Christoffer Laustsen, MD, PhD

Head of MR Research
Aarhus University Hospital, Denmark
JG

Joseph Gutbrod

BS
Washington University School of Medicine, United States
AF

Ambrose Ho Tung Fong, MD

Assistant Project Manager
The University of Hong Kong, Hong Kong
KC

Ka Man Carmen Cheng, MD

Research Assistant
The University of Hong Kong, Hong Kong
VG

Victor Goh, MD

Cardiologist
Hong Kong Sanatorium & Hospital, Hong Kong
SM

Simon Madsen, MD

PhD student
Aarhus University Hospital
Aarhus N, Denmark
Alexander Hirsch, MD, PhD

Cardiologist
Erasmus MC
Rotterdam, Zuid-Holland, Netherlands
VM

Vicente Martinez, MD

Head of Radiology
Hospital Universitario Quiron Madrid, Spain
ML

Mark Lubberink, PhD

Professor, medical physicist
Uppsala University, Sweden
AM

Alicia M. Maceira, MD, PhD

Director
Directora Médica en ASCIRES Grupo Biomédico, Spain
JM

Jose Monmeneu, MD

Cardiologist
ASCIRES Grupo Biomédico, Spain
AP

Aju P. Pazhenkottil, MD

Senior Consultant Cardialogy / Cardiac Imaging
University Hospital Zürich
Zurich, Zurich, Switzerland
PN

Prashant Nagpal, MD

Associate Professor
University of Wisconsin-Madison, United States
MB

Mitchel Benovoy, PhD

PhD
Area19 Medical Inc, Montreal, Canada, H2V 2X5
Montreal, Quebec, Canada
Martin A. A. Janich, PhD

Director, Cardiac MRI
GE Healthcare
Munich, Bayern, Germany
Andrew E. E. Arai, MD

Cardiologist
NIH
Kensington, Maryland, United States
Matthias G. Friedrich, MD, FSCMR

Senior Author
Research Institute of the McGill University Health Center
Montreal, Quebec, Canada
Amit R. Patel, MD

Professor
University of Virginia Health System
Charlottesville, Virginia, United States

Disclosure(s):

Ming- Yen Ng, BMBS FRCR FSCMR: No relevant disclosure to display

Michael Salerno, MD, PhD, MSc: No relevant disclosure to display

Ibrahim M. Saeed, MD, FSCMR: No financial relationships to disclose

Andrew E. E. Arai, MD: No relevant disclosure to display

Background: Fully quantitative myocardial perfusion analysis using stress cardiac magnetic resonance (CMR) has been shown to detect obstructive coronary artery disease (CAD) in several mostly single-center studies; however, interpretation of findings requires the assessment of regional variation in myocardial perfusion. The AQUA-MBF (Assessment of QUAntitative Myocardial Blood Flow) study is a multicenter study involving 16 centers. The goal of this sub-study is to determine if global myocardial blood flow (MBF) and global myocardial perfusion reserve (MPR) can accurately detect the presence of CAD.

Methods:
Of the 291 individuals referred for a vasodilator stress perfusion CMR using 1.5T and 3.0T MR scanners (GE Healthcare) and enrolled in the AQUA-MBF study, 85 subjects who also had either a coronary CTA (n=27), invasive coronary angiogram (ICA)(n=40), or low pre-test probability for CAD (n=18) were included in this sub-study. CAD was defined as the presence of: (1) a stenosis ≥50% in the left main coronary artery or ≥70% in the 1 major vessel based on ICA or CTA or (2) an invasive fractional flow reserve (FFR) ≤ 0.8. No obstructive coronary disease (NOCAD) was defined as a no history of myocardial infarction and stenosis < 50% by ICA or CTA, 50-70% stenosis with FFR >0.8, or young individual with no cardiac risk factors. Quantitative myocardial perfusion imaging was performed using the dual sequence technique, with a low-resolution image for arterial input function and 2-3 short axis slices for myocardial perfusion. Resting MBF (rMBF), stress MBF (sMBF), and myocardial perfusion reserve (MPR) were measured using Fermi deconvolution (cvi42, Circle CVI Inc. Calgary, Canada). Global rMBF, sMBF, and MPR were calculated for each subject as the average value of the 16 American Heart Association segments after excluding segments with significant artifact (Figure 1). T-test was used to compare CAD vs NOCAD. Receiver-operating characteristics (ROC) curves were used to determine diagnostic performance.

Results:
27 patients had CAD and 58 had NOCAD. Demographics are shown in Figure 2. The global rMBF was similar in both groups; however global sMBF and MPR were significantly lower in the CAD group (Figure 3A). The AUC of sMBF and MPR for detecting CAD were 0.86 and 0.90 with an optimal global cut-off value of 2.2ml/min/g for sMBF and 2.0 for MPR. There was no significant difference between sMBF and MPR for diagnostic performance (p=0.71) (Figure 3B).

Conclusion: In this multicenter study, we show that global sMBF and MPR reported as a single value can accurately identify patients with CAD. Availability of a simple parameter for identifying individuals with CAD may accelerate adoption of stress CMR in clinical practice.