Comparison of Cardiac Strain Values across SSFP and FGRE Sequences using Tissue TrackingPatrick Young, Ela Chamera, Bharath Ambale-Venkatesh, Joao A.C. Lima M.D.

1 Department of Cardiology and Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA

• Global longitudinal strain is a strong, prognosticative risk factor for heart failure and cardiomyopathy. • Feature tracking is an attractive novel technique to easily obtain myocardial strain from MR CINE images. • When comparing steady-state free precession (SSFP) and fast gradient echo (FGRE) MR cine images, there are considerable discrepancies in image contrast of the myocardial edges that make it difficult to easily translate one to the other.• When cardiovascular cine images run by SSFP and FGRE are juxtaposed, there are also quantitative discrepancies. Understanding these is important for clinical translation.

• To compare the feature tracking strain values by SSFP with that of FGRE cine images and to identify the reasons for any discrepancies, if any.

Objectives

Introduction

Materials and Methods

• The MESA (Multi-Ethnic Study of Atherosclerosis) study enrolled 6000+ healthy men and women from six communities from the U.S. • In the MESA follow-up study (2010), 50 participants had an MRI scan run by SSFP and FGRE cine sequence. Each image had horizontal long axis projections in standard 4 chamber view and 2 chamber view of the participant’s heart. • The cardiovascular MR images were uploaded on to the software Multimodality Tissue Tracking (MTT). Contours lines were drawn for the endocardium and epicardium at end diastolic time frame by the user. • MTT automatically tracked these contours throughout the cardiac cycle to obtain global displacement and strain curves. •The individual peak strain variables (maximum strain) of each study was calculated in both SSFP and FGRE in all four heart chambers. • Longitudinal strain values of the two sequences was compared using linear regression analysis in order to measure correlation.

Results

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f(x) = 0.653101893550083 x − 3.52847773796476R² = 0.29842112938431

Right VentricleStrain by SSFP (x-axis)

Strain by FGR

E (y-axis)

Mean SSFP: -28.2 ± 7.1 Mean FGRE: -23.7 ± 7.1

Conclusion• There is a strong correlation despite the varying average differences in strain for each chamber of the heart; the absolute myocardial strain values obtained from cine SSFP images are greater than those found in FGRE images. •Calibration of measurements to compare measures from the two sequences is important.

Figure 1 –MTT utilizes pixel-to-pixel matching by defining angle-independent motion vectors from multiple tracking points to find voxels in successive frames. In order to maximize similarity between pixel squares, the software propagates the borders across the cardiac cycle using a template matching algorithm.

Figure 2 – Linear Regression Models comparing the longitudinal strain in SSFP images to FGRE images.

Figure 3 a and 3b – Left figures show a cine image run by SSFP and a strain curve, indicating maximum strain during the cycle. Right figures show a cine image run by FGRE and a strain curve, indicating maximum strain during the cycle.

Tem

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f(x) = 0.663242596929306 x + 0.783737643889168R² = 0.396263191551035

Left VentricleStrain by SSFP (x-axis)

Strain by FGR

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f(x) = 0.761859935418588 x − 4.55157114759534R² = 0.834628632242995

Right Atrium

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f(x) = 0.681864920023589 x + 3.7343058313133R² = 0.715767281436593

Left Atrium

Strain by SSFP (x-axis)

Strain by FGR

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Mean SSFP: 32.2 ± 18.4 Mean FGRE: 25.7 ± 14.9

Multimodality Tissue Tracking (MTT)

SSFP vs. FGRE

Strain by FGR

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Mean SSFP: 54.8 ± 37.4 Mean FGRE: 37.2 ± 31.2

Mean SSFP: -20.5 ± 5.1 Mean FGRE: -12.8 ± 5.3