Background— A plethora of echo parameters has been suggested for distinguishing cardiac amyloidosis (CA) from other causes of myocardial thickening with, however, scarce data on their head-to-head comparison. This study aimed at comparing the diagnostic accuracy of various deformation and conventional echo parameters in differentiating CA from other hypertrophic substrates, especially in the gray zone of mild hypertrophy (maximum wall thickness ≤16 mm) or normal ejection fraction (EF). Methods and Results— We included 100 subjects, of which 40 were patients with newly diagnosed, biopsy-proven CA (65.5±10.8 years, 65% male, 62.5% amyloidosis light chain [AL] type), 40 patients with hypertrophic cardiomyopathy matched for demographics and maximum wall thickness (60.1±14.8 years, 85% male), and 20 hypertensives with prominent myocardial remodeling. Quantifiable conventional morphological and functional parameters along with multidimensional strain and strain-derived ratios indices, previously suggested to diagnose CA, were analyzed. EF global longitudinal strain ratio showed the best performance to discriminate CA (area under the curve, 0.95; 95% confidence intervals, 0.89–0.98; P <0.00005). Traditional echo indices showed overall low sensitivities and high specificities (among them myocardial contraction fraction ratio had the highest area under the curve, 0.80; 95% confidence intervals, 0.7–0.87; P <0.0001). In the challenging subgroups (maximum wall thickness ≤16 mm and EF>55%), EF global longitudinal strain ratio remained the best predicting parameter of CA diagnosis (multiple logistic regression models P <0.00005 and P =0.0002, respectively) independent of the CA type. Conclusions— Our study demonstrated that in patients with thickened hearts, EF global longitudinal strain ratio has the best accuracy in detecting CA, even among the most “challenging” patient subgroups as those with mild hypertrophy and normal EF.

Real-time 3D Echocardiography (RT3DE) has been proven to be an accurate tool for left ventricular (LV) volume assessment. However, identification of the LV endocardium remains a challenging task, mainly because of the low tissue/blood contrast of the images combined with typical artifacts. Several semi and fully automatic algorithms have been proposed for segmenting the endocardium in RT3DE data in order to extract relevant clinical indices, but a systematic and fair comparison between such methods has so far been impossible due to the lack of a publicly available common database. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms developed to segment the LV border in RT3DE. A database consisting of 45 multivendor cardiac ultrasound recordings acquired at different centers with corresponding reference measurements from three experts are made available. The algorithms from nine research groups were quantitatively evaluated and compared using the proposed online platform. The results showed that the best methods produce promising results with respect to the experts' measurements for the extraction of clinical indices, and that they offer good segmentation precision in terms of mean distance error in the context of the experts' variability range. The platform remains open for new submissions.

The accuracy of identifying regional abnormality differs significantly among vendors.

In contrast to GLS, LV segmental longitudinal strain measurements have a higher variability on top of the known intervendor bias. The fidelity of different software to follow segmental function varies considerably. We conclude that single segmental strain values should be used with caution in the clinic. Segmental strain pattern analysis might be a more robust alternative.

Overall, reproducibility of GLPSS is excellent and superior to that of 2D EF, whereas segmental LPSS reproducibility is good and similar to that of LV volumes. Both are suitable for diagnosis and follow-up of LV global and regional systolic function.