Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Feb 17;19(1):24.
doi: 10.1186/s12968-017-0333-y.

Cardiovascular Magnetic Resonance Myocardial Feature Tracking Using a Non-Rigid, Elastic Image Registration Algorithm: Assessment of Variability in a Real-Life Clinical Setting

Affiliations
Free PMC article

Cardiovascular Magnetic Resonance Myocardial Feature Tracking Using a Non-Rigid, Elastic Image Registration Algorithm: Assessment of Variability in a Real-Life Clinical Setting

Pedro Morais et al. J Cardiovasc Magn Reson. .
Free PMC article

Abstract

Background: Cardiovascular magnetic resonance myocardial feature tracking (CMR-FT) is a promising technique for quantification of myocardial strain from steady-state free precession (SSFP) cine images. We sought to determine the variability of CMR-FT using a non-rigid elastic registration algorithm recently available in a commercial software package (Segment, Medviso) in a real-life clinical setting.

Methods: Firstly, we studied the variability in a healthy volunteer who underwent 10 CMR studies over five consecutive days. Secondly, 10 patients were selected from our CMR database yielding normal findings (normal group). Finally, we prospectively studied 10 patients with known or suspected myocardial pathology referred for further investigation to CMR (patient group). In the patient group a second study was performed respecting an interval of 30 min between studies. All studies were manually segmented at the end-diastolic phase by three observers. In all subjects left ventricular (LV) circumferential and radial strain were calculated in the short-axis direction (EccSAX and ErrSAX, respectively) and longitudinal strain in the long-axis direction (EllLAX). The level of CMR experience of the observers was 2 weeks, 6 months and >20 years.

Results: Mean contouring time was 7 ± 1 min, mean FT calculation time 13 ± 2 min. Intra- and inter-observer variability was good to excellent with an coefficient of reproducibility (CR) ranging 1.6% to 11.5%, and 1.7% to 16.0%, respectively and an intraclass correlation coefficient (ICC) ranging 0.89 to 1.00 and 0.74 to 0.99, respectively. Variability considerably increased in the test-retest setting with a CR ranging 4.2% to 29.1% and an ICC ranging 0.66 to 0.95 in the patient group. Variability was not influenced by level of expertise of the observers. Neither did the presence of myocardial pathology at CMR negatively impact variability. However, compared to global myocardial strain, segmental myocardial strain variability increased with a factor 2-3, in particular for the basal and apical short-axis slices.

Conclusions: CMR-FT using non-rigid, elastic registration is a reproducible approach for strain analysis in patients routinely scheduled for CMR, and is not influenced by the level of training. However, further improvement is needed to reliably depict small variations in segmental myocardial strain.

Figures

Fig. 1
Fig. 1
Feature tracking in a patient belonging to the normal group in short-axis (upper panels) and horizontal long-axis (lower panels). Manual delineation of the endo- and epicardial contour at the end-diastole (left panels). Next, the software automatically deforms these contours using a dense motion field (yellow arrow) estimated between consecutive frames
Fig. 2
Fig. 2
Reproducibility study using the multiple acquisitions of the patient group. Bland-Altman plots for global and segmental ES (a, d) radial, (b, e) circumferential and (c, f) longitudinal strain obtained. Dashed lines represent bias (red) and 95% limits of agreement (b)
Fig. 3
Fig. 3
Mean strain and variability per slice level and per segment in the healthy volunteer (10 acquisitions). a, d represents the global strain components and b, e the segmental strain. c shows the obtained global radial and circumferential strain curves in a mid-ventricular slice for all the 10 acquisitions. f presents the obtained strain curve for the global longitudinal strain
Fig. 4
Fig. 4
Strain curve examples from different subjects in the patient group. The continuous line represents the first acquisition, while the dashed line represent the second acquisition. Blue shows the result obtained by the Expert observer, red the result obtained with skilled observer and green the result achieved by the beginner. In order to ease the visualization, the absolute value of the longitudinal strain along the vertical long axis is used
Fig. 5
Fig. 5
Feature tracking in cardiac short-axis in a subject belonging to the normal group by an expert, a skilled observer, and a beginner. Five time points over the cardiac cycle are shown
Fig. 6
Fig. 6
Feature tracking in cardiac short-axis in a patient with dilated cardiomyopathy by an expert, a skilled observer, and a beginner. Five time points over the cardiac cycle are shown
Fig. 7
Fig. 7
Correlation between myocardial strain (patient and normal group) and LV ejection fraction. a) radial strain, b) circumferential strain, c) longitudinal strain

Similar articles

See all similar articles

Cited by 15 articles

See all "Cited by" articles

References

    1. Smiseth OA, Torp H, Opdahl A, Haugaa KH, Urheim S. Myocardial strain imaging: how useful is it in clinical decision making? Eur Heart J. 2016;37:1196–1207. doi: 10.1093/eurheartj/ehv529. - DOI - PMC - PubMed
    1. Kalam K, Otahal P, Marwick TH. Prognostic implications of global LV dysfunction: a systematic review and meta-analysis of global longitudinal strain and ejection fraction. Heart. 2014;100:1673–1680. doi: 10.1136/heartjnl-2014-305538. - DOI - PubMed
    1. Thavendiranathan P, Poulin F, Lim KD, Plana JC, Woo A, Marwick TH. Use of myocardial strain imaging by echocardiography for the early detection of cardiotoxicity in patients during and after cancer chemotherapy: a systematic review. J Am Coll Cardiol. 2014;63:2751–2768. doi: 10.1016/j.jacc.2014.01.073. - DOI - PubMed
    1. Ichikawa Y, Sakuma H, Kitagawa K, Ishida N, Takeda K, Uemura S, Motoyasu M, Nakano T, Nozaki A. Evaluation of left ventricular volumes and ejection fraction using fast steady-state cine MR imaging: comparison with left ventricular angiography. J Cardiovasc Magn Reson. 2003;5:333–342. doi: 10.1081/JCMR-120019422. - DOI - PubMed
    1. Bogaert J, Rademakers FE. Regional nonuniformity of normal adult human left ventricle. Am J Physiol Heart Circ Physiol. 2001;280:H610–620. - PubMed

Publication types

MeSH terms

LinkOut - more resources

Feedback