Fully automatic left ventricular myocardial strain estimation in 2D short-axis tagged magnetic resonance imaging

Cardiovascular diseases are among the leading causes of death and frequently result in local myocardial dysfunction. Among the numerous imaging modalities available to detect these dysfunctional regions, cardiac deformation imaging through tagged magnetic resonance imaging (t-MRI) has been an attractive approach. Nevertheless, fully automatic analysis of these data sets is still challenging. In this work, we present a fully automatic framework to estimate left ventricular myocardial deformation from t-MRI. This strategy performs automatic myocardial segmentation based on B-spline explicit active surfaces, which are initialized using an annular model. A non-rigid image-registration technique is then used to assess myocardial deformation. Three experiments were set up to validate the proposed framework using a clinical database of 75 patients. First, automatic segmentation accuracy was evaluated by comparing against manual delineations at one specific cardiac phase. The proposed solution showed an average perpendicular distance error of 2.35 +/- 1.21 mm and 2.27 +/- 1.02 mm for the endo- and epicardium, respectively. Second, starting from either manual or automatic segmentation, myocardial tracking was performed and the resulting strain curves were compared. It is shown that the automatic segmentation adds negligible differences during the strain-estimation stage, corroborating its accuracy. Finally, segmental strain was compared with scar tissue extent determined by delay-enhanced MRI. The results proved that both strain components were able to distinguish between normal and infarct regions. Overall, the proposed framework was shown to be accurate, robust, and attractive for clinical practice, as it overcomes several limitations of a manual analysis.FCT—Fundacão para a Ciência e a Tecnologia, Portugal, and the European Social Found, European Union, for funding support through the Programa Operacional Capital Humano (POCH) in the scope of the PhD grants SFRH/BD/95438/2013 (P Morais) and SFRH/BD/93443/2013 (S Queirós). This work was supported by the projects NORTE-07-0124-FEDER-000017 and NORTE-01-0145-FEDER-000013, co-funded by Programa Operacional Regional do Norte, Quadro de Referência Estratégico Nacional, through Fundo Europeu de Desenvolvimento Regional (FEDER). The authors would also like to acknowledge the EU (FP7) framework program, for the financial support of the DOPPLER-CIP project (grant no. 223615)info:eu-repo/semantics/publishedVersio

A head-to-head comparison of myocardial strain by fast-strain encoding and feature tracking imaging in acute myocardial infarction

BackgroundMyocardial infarction (MI) is a major cause of heart failure. Left ventricular adverse remodeling is common post-MI. Several studies have demonstrated a correlation between reduced myocardial strain and the development of adverse remodeling. Cardiac magnetic resonance (CMR) with fast-strain encoding (fast-SENC) or feature tracking (FT) enables rapid assessment of myocardial deformation. The aim of this study was to establish a head-to-head comparison of fast-SENC and FT in post-ST-elevated myocardial infarction (STEMI) patients, with clinical 2D speckle tracking echocardiography (2DEcho) as a reference.MethodsThirty patients treated with primary percutaneous coronary intervention for STEMI were investigated. All participants underwent CMR examination with late gadolinium enhancement, cine-loop steady-state free precession, and fast-SENC imaging using a 1.5T scanner as well as a 2DEcho. Global longitudinal strain (GLS), segmental longitudinal strain (SLS), global circumferential strain (GCS), and segmental circumferential strain (SCS) were assessed along with the MI scar extent.ResultsThe GCS measurements from fast-SENC and FT were nearly identical: the mean difference was 0.01 (2.5)% (95% CI – 0.92 to 0.95). For GLS, fast-SENC values were higher than FT, with a mean difference of 1.8 (1.4)% (95% CI 1.31–2.35). Tests of significance for GLS did not show any differences between the MR methods and 2DEcho. Average strain in the infarct-related artery (IRA) segments compared to the remote myocardium was significantly lower for the left anterior descending artery and right coronary artery culprits but not for the left circumflex artery culprits. Fast-SENC displayed a higher area under the curve for detecting infarcted segments than FT for both SCS and SLS.ConclusionGLS and GCS did not significantly differ between fast-SENC and FT. Both showed acceptable agreement with 2DEcho for longitudinal strain. Segments perfused by the IRA showed significantly reduced strain values compared to the remote myocardium. Fast-SENC presented a higher sensitivity and specificity for detecting infarcted segments than FT