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Aims Speckle tracking echocardiography has already demonstrated its clinical potential. However, its use in routine practice is jeopardized by recent reports on high inter-vendor variability of the measurements. As such, the European Association of CardioVascular Imaging (EACVI) and the American Society of Echocardiography (ASE) set up a standardization task force, which was joined by all manufacturers of echocardiographic equipment as well as by companies offering software solutions only, with the ambition to tackle this problem by standardization and quality assurance (QA). Methods and results In this study, a first step towards QA of all commercially available tracking solutions based on computer-generated ultrasound images is presented. The accuracy of the products was acceptable with relative errors below 10% and intra-vendor reproducibility within 5%. Conclusion Whether these results can be extrapolated to the clinical setting is the topic of an ongoing study of the EACVI/ASE/Industry Task Force to standardize deformation imaging. This study was an important first step in the development of generally accepted tools for QA of speckle tracking echocardiography.

Purpose. We previously re-validated noninvasive estimation of pulmonary wedge pressure (PWP) measuring the CW pulmonary valve regurgitation end-diastolic pressure gradient (PWPecho). Using the latter as surrogate of PWP, we sought to test accuracy of left ventricular (LV) filling pressures estimation by the EAE guidelines algorithm (EAEalg) in a large non-selected population. Methods. We studied 1019 patients in sinus rhythm with GE Vivid7/9 systems (age: 10-93 y.; EF%: 13-83%, normal, n= 827 and reduced <50%, n= 192), in whom PWPecho could be measured (feasibility 75%), with normal pulmonary vascular resistances (WU< 2). The EAEalg combined E/e' (average), left atrial volume (LAV), E/A, Edec, pulmonary venous systolic fraction (SF), and echo-derived pulmonary systolic pressure (PSPe) to obtain 3 groups: normal, high PWP and not classifiable. These were compared to the PWPecho estimate. Results: Feasibility was high for all variables (E/E' 90%, LAV 93%, E/A 95%, Edec 90%, SF 91%, PSPe 92%), and for the EAEAlg (94%). Using the EAEAlg, 17% (n=137) of patients with normal in contrast to 10% (n=19) of patients with EF<50% were not classifiable, in the former secondary to the combination of a E/E'= 9-13 range, and LAV≥ 34ml/m2. In the remaining (classified, 84%) patients, utility of EAEalg even when limited to patients with EF<50% was still hampered by a low positive predictive value (PPV) (Table). Further, when only E/e' was tested in the same patients at ROC analysis (cutoff= 15; AUC=0.72, CI:0.6-0.8), accuracy was still impaired by a low PPV (53%), albeit a fair negative predictive value (NPV) (79%). Correlation between PWPecho and E/e' was modest even in patients with EF<50% (r=0.4, p<0.001), and at multiple regression analysis, E/e' was independently determined by age and mitral regurgitation in all patients, and by LV end-diastolic volume in EF<50% (r= 0.7, p<0.001) and by LV mass index in EF>50% (r= 0.64, p<.001). Conclusions. Noninvasive estimation of PWP by EAE guidelines is limited by a low PPV in both patients with and without reduced LV EF. In this setting, utility of the E/e' is limited, it being influenced by patient age, preload and LV mass. 1 SensitivitySpecificityPPVNPVEF≥50%72%78%18%98%EF<50%71%80%65%84%

Aims Assessing the quality of wall motion (WM) on echocardiograms remains a challenge. Previously, we validated an automated application used by experienced echocardiographers for WM classification based on longitudinal two-dimensional (2D) strain. The aim of this study was to show that the use of this automatic application was independent of the users experience. Methods and results We compared the WM classifications obtained by the application when used by 12 highly experienced readers (Exp-R) vs. 11 inexperienced readers (InExp-R). Both classifications were compared with expert consensus classifications using the standard visual method. Digitized clips of cardiac cycles from three apical views in 105 patients were used for these analyses. Reproducibility of both groups was high (overall intra-class correlation coefficient: InExp-R = 0.89, Exp-R = 0.83); the lowest was noted for hypokinetic segments (InExp-R = 0.79, Exp-R = 0.72). InExp-R scores were concordant with Exp-R mode scores in 88.8% of segments; they were overestimated in 5.8% and underestimated in 3.2%. The sensitivity, specificity, and accuracy of InExp-R vs. Exp-R for classifying segments as normal/abnormal were identical (87, 85, and 86%, respectively). Conclusion Classification of WM from apical views with an automatic application based on longitudinal 2D strain by InExp-R vs. Exp-R was similar to visual classification by Exp-R. This application may be useful for inexperienced echocardiographers/technicians and may serve as an automated ‘second opinion’ for experienced echocardiographers.