Correlation between automatic and manual methods of right ventricle and left atrium strain quantification

Abstract Introduction Myocardial strain quantification by speckle-tracking of the right ventricle (RV) and left atrium (LA) can be performed by manual or automatic methods. Purpose The objective of our study is to evaluate the degree of correlation between manual measurement method and automatic software used in our imaging laboratory, in a population of healthy individuals and patients with cardiac transthyretin amyloidosis (ATTR). Methods Fifty-seven individuals were included, 30 patients with ATTR and 27 healthy volunteers, who underwent a transthoracic echocardiogram (TTE) from January to December 2019. Classic echocardiographic parameters and myocardial deformation were obtained according to the ASE/ EACVI guidelines. Global and free wall longitudinal strain of the RV (RVGLS, RVFWLS) and LA global strain (LAGS) analysis were obtained using speckle-tracking with two different software: QLAB Philips 10.7 and AutoSTRAIN Tomtec. Measurements analysis was performed by two experienced echocardiographers. Correlation and reproducibility analysis was performed using Pearson correlation coefficient (PCC) and intraclass correlation coefficient (ICC), respectively. Results Seventy-two percent were male and average age was 63±20 years. Linear correlation of RVGLS, RVFWLS and LAGS measurements with both methods reached statistical significance (table). This correlation was stronger and more reliable in the case of the LAGS. The attached figure shows the correlation between the different software in both groups. Conclusions AutoSTRAIN Tomtec automatic measurement method had higher reliability and correlation comparing to manual measurements performed by QLAB 10.7, especially in LA measurements. The obtained results, the application speed and the less operator's dependence of this automatic software support its routine use for RV and LA strain quantification. Funding Acknowledgement Type of funding sources: None. Correlation and reproducibility resultsLinear regression lines