ABC | Volume 114, Nº3, March 2020

Original Article Sousa et al. Software: analysis of strain curves Arq Bras Cardiol. 2020; 114(3):496-506 Table 1 – Global Longitudinal Strain (%) obtained by EchoPAC and D-Station Subject GLS_Echopac GLS-D-Station Subject GLS_Echopac GLS-D-Station Subject GLS_Echopac GLS-D-Station 1 –17.90 –17.88 17 –19.00 –19.03 33 –24.40 –24.62 2 –7.90 –9.50 18 –16.90 –16.82 34 –19.10 –19.57 3 –10.50 –11.10 19 –19.500 –16.68 35 –7.40 –6.46 4 –8.50 –8.19 20 –19.80 –19.83 36 –2.70 –3.37 5 –13.30 –13.55 21 –16.70 –17.04 37 –5.70 –5.22 6 –18.40 –18.26 22 –20.50 –20.93 38 –4.50 –4.32 7 –4.60 –4.21 23 –14.90 –14.71 39 –10.50 –9.83 8 –21.60 –21.48 24 –20.20 –19.76 40 –9.40 –10.95 9 –16.20 –16.36 25 –17.80 –18.19 41 –10.60 –10.47 10 –11.90 –11.41 26 –20.10 –20.47 42 –11.10 –11.15 11 –8.80 –7.33 27 –17.30 –17.60 43 –3.20 –3.69 12 –17.30 –17.23 28 –17.50 –16.96 44 –8.20 –8.64 13 –20.40 –20.32 29 –21.20 –20.28 45 –6.60 –6.01 14 –19.80 –19.40 30 – 23.00 –23.06 46 –6.90 –6.85 15 –16.40 –15.27 31 – 20.70 –19.91 47 –10.60 –10.11 16 –19.20 –19.38 32 –21.10 –21.22 48 –8.80 –9.28 including combinations of different displays can be easily added to the program, with consequent extraction of other parameters for the study on cardiac strain in different chambers simultaneously and by cardiac cycle. As example, exhibits the curves of left and right ventricles, which facilitates the analysis of the interactions between them. CircAdapt Interface: generation of virtual cardiac models The D-Station “Test” option has been designed to define the strain curve parameters without separation into phases. Consequently, the ECG curve is no longer necessary, and the program becomes compatible with the mathematical model CircAdapt. This model, combined with the MultiPatch Module, proposed by Walmsley et al., 11 can retrieve the strain curves corresponding to simulations and the times of mechanical events, without ECG signals, as shown in Figure 6. Thus, the D-Station software can work with virtual cardiac models developed according to Walmsley et al. 11-14 Applicability of machine learning techniques Machine learning consists of a subset of artificial intelligence, capable of processing complex problems of interaction between variables and making accurate predictions. It has been widely used in different areas of cardiology. The storage format of entries and data obtained by the program allows the implementation of machine learning algorithms and thereby the automatic extraction of parameters, classification of a large number of signals and reading of space-time characteristics of the entire strain curve, as proposed by Tabassian et al. 15 Validation analysis results a) Normality testing of measures Figure 7 shows the Q-Q plot of EchoPAC (Figure 7a), D-Station (Figure 7b) and EchoPAC - D-Station (Figure 7c). As can be seen in Figures 7a and 7b, several points are out of the red reference line, indicating that EchoPAC and D-Station data are not normally distributed. On the other hand, in Figura 7c, most of the points lie on or are very close to the red reference line (except for two points in the right upper corner), indicating that the difference between the measurements tend to be normally distributed. Since the difference between measurements will be used in the hypothesis test, we sought to confirm the hypothesis of normality in the distribution of these differences obtained by the graphical method by using the Shapiro‑Wilk test, which confirmed the hypothesis of normality (p > 0.05) (Figure 8). b) Graphs of EchoPAC and D-Station measurements in relation to equality line and coefficient of correlation Figure 9 shows the distribution of EchoPAC and D-Station (paired data) in relation to the equality line, evidencing a distribution of points close to and in both sides of the line, suggesting a low bias from the qualitative viewpoint and scattering. Since these measures did not have a normal distribution, we used the Spearman correlation test, which indicated a strong correlation (r = 0.99) between results obtained by the two methods. 500