Global Early Diastolic Strain Rate Correlates with Myocardial Blood Flow Using Stress Cardiac Magnetic Resonance (RF_TH_287)

Thursday, January 30, 2025

6:10 PM – 6:20 PM East Coast USA Time

Location: Blue Room PreFunction

Primary Author(s)

JN

Joseph D. Nguyen, BS

Medical Student
University of Virginia

Presenting Author(s)

CC

Caroline Carter, BSc

Medical Student Researcher
University of Virginia Health System

Co-Author(s)

SW

Shuo Wang, MD, PhD

Research Associate
University of Virginia Health System
HW

Haonan Wang, PhD

Lead Scientist, Cardiac MR
GE Healthcare
SM

Saima Mushtaq, MD

Cardiologist
Centro Cardiologico Monzino IRCCS, Italy
JS

Jason Sin

Research
The University of Hong Kong, Hong Kong
Gianluca Pontone, MD, PhD

Cardiologist
Centro Cardiologico Monzino IRCCS, University of Milan, Italy
HP

Hena Patel, MD

Assistant Professor
University of Chicago Medicine
CD

Cristiane C. De Carvalho Singulane, MD

Postdoctoral Researcher
University of Virginia Health System
JP

Jonathan Pan, MD, MBA

Cardiovascular Imaging Fellow
University of Virginia Medical center
Amit R. Patel, MD

Professor of Medicine
Division of Cardiology, University of Virginia Health System, Charlottesville, Virginia, USA.
Ming-Yen Ng, BMBS FRCR FSCMR

Clinical Associate Professor
The University of Hong Kong, Hong Kong

Background: Diastolic dysfunction is one of the first abnormalities that occurs during myocardial ischemia. In addition to quantifying abnormalities in stress myocardial blood flow (sMBF), stress cardiac magnetic resonance (CMR) can quantify markers of diastolic dysfunction, such as left ventricular (LV) early diastolic circumferential and longitudinal strain (CS/LS) and strain rate (CSR/LSR). In this study, we explore the relationship between each of the early diastolic strain parameters and sMBF.

Methods: 40 patients (median age 67 years, 70% male, 70% diabetes, 78% hypertension, 20% smokers) with suspected obstructive coronary artery disease (obCAD) who underwent stress CMR using the dual sequence quantitative MBF technique (GE HealthCare) were retrospectively included in this study. sMBF was quantified using deconvolution (CircleCVI). Short and long axis cine images were obtained following vasodilator injection, and feature tracking (SuiteHeart) was used to generate full cardiac cycle strain and strain rate curves. Each strain curve was graphed in R (R Statistical Software, v 4.3.1), and early diastolic CSR, LSR, CS, and LS were identified visually (Figure 1). obCAD was defined as stenosis ≥70% on coronary angiogram. Spearman correlations (ρ) were determined between sMBF and early diastolic CSR, LSR, CS, and LS. Student's t-test was used to compare sMBF and early diastolic CSR, LSR, CS, and LS between patients with and without obCAD.

Results: 26 of 40 patients had obCAD. Mean LV ejection fraction was 56% ± 8%, mean LV early diastolic volume was 153 ± 39mL, and mean LV mass was 111 ± 27g. sMBF was significantly higher in patients without obCAD (2.5 ± 0.4 vs 1.4 ± 0.4 ml/g/min, p=9.3e-8). sMBF significantly correlated with early diastolic CSR and LSR (ρ=0.31, p=0.049 and ρ=0.37, p=0.019, Figures 2A/B) but not with early diastolic CS or LS (ρ=-0.15, p=0.35 and ρ=-0.26, p=0.11, Figures 2C/D). Patients without obCAD had numerically, but not significantly, higher early diastolic CSR (75.3s^-1 vs 66.5s^-1 , p=0.30), LSR (65.8s^-1 vs 55.5s^-1 , p=0.16), CS (-11.8% vs -10.8%, p=0.21), and LS (-10.9% vs -9.6%, p=0.05).

Conclusion: Early diastolic strain rate, but not early diastolic strain, correlates with sMBF. Future studies are needed to determine if the combination of early diastolic strain rate with abnormalities in myocardial blood flow can improve the diagnosis of obCAD or help identify higher-risk patients undergoing stress CMR.