Abstract

Background

The aim of this study was to investigate the incremental value of global longitudinal strain (GLS), postsystolic strain index (PSI) and prestretch (PSE) by automated function imaging with respect to wall motion (WM) and coronary flow reserve (CFR) for the diagnosis of significant coronary artery disease (CAD) during dipyridamole stress echocardiography.

Methods

We retrospectibely enrolled 227 patients with known or suspected CAD, approaching our echo lab to perform a DSE; all patient underwent coronary angiography within 1 month for clinical reasons. Obstructive CAD was defined as the evidence of >70% stenosis during coronary angiogram. Obstructive CAD was detected in 143 (63%) patients, while 84 (37%) had no significant CAD.

Global longitudinal strain, PSI and PSE were measured at rest and peak of the stress (after 6 minutes of 0,84mg/kg of dipyridamole infusion).

Results

Patient with CAD showed a significantly lower GLS at rest (−16.9±4.2 vs −18.6±3.4; p<0.01) and peak (14.9±3.8 vs −21.50±3.3; p<0.01) Figure A; the behavior of GLS was opposite, in patient with CAD showed an increase while in patient without CAD a significant decrease after dipyridamole infusion. There was also a significant difference between groups for Delta PSI (PSIpeak − PSIrest) and Delta PSE (PSEpeak − PSErest), respectively 126±145 vs −40±97, (p<0.01) and 108±163 vs −41±106 (p<0.01) Figure C. ROC analyses produced a statistically valid model: Average GLS at peak (p 0.001; AUC=0.906, cut-off value −18%, sensitivity 83% and specificity 82%); on the basis of these results, we compared WM and myocardial deformation analysis and GLS was superior to CFR LAD, Delta EF, Delta ESV and Delta WMI (Figure B).

Conclusions

GLS, PSE and PSI show an opposite response to dipyridamole, in patients with CAD in patient without CAD and show much higher sensitivity and specificity compared to the conventional parameters like WMI, EF and CFR in detecting CAD

STE and conventional DSE parameters

ParametersAUCCut-offSensibilitySpecificity
EF at peak0.694<60%71%69%
Delta WMI (WMIpeak − WMIrest)0.741>070%73%
Delta ESV (ESVpeak − ESVrest)0.706>0ml45%86%
CFR LAD0.804<279%66%
Delta Average PSI (PSIpeak − PSIrest)0.862>0 msec85%82%
Peak Average GLS0.906<−18%83%82%
Delta Average PSE (PSEpeak − PSErest)0.904>0.5 msec88%87%
ParametersAUCCut-offSensibilitySpecificity
EF at peak0.694<60%71%69%
Delta WMI (WMIpeak − WMIrest)0.741>070%73%
Delta ESV (ESVpeak − ESVrest)0.706>0ml45%86%
CFR LAD0.804<279%66%
Delta Average PSI (PSIpeak − PSIrest)0.862>0 msec85%82%
Peak Average GLS0.906<−18%83%82%
Delta Average PSE (PSEpeak − PSErest)0.904>0.5 msec88%87%
Funding Acknowledgement

Type of funding source: None

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