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Title: Non-invasive, model-based measures of ventricular electrical dyssynchrony for predicting CRT outcomes. Author: Villongco CT, Krummen DE, Omens JH, McCulloch AD. Journal: Europace; 2016 Dec; 18(suppl 4):iv104-iv112. PubMed ID: 28011837. Abstract: AIMS: Left ventricular activation delay due to left bundle branch block (LBBB) is an important determinant of the severity of dyssynchronous heart failure (DHF). We investigated whether patient-specific computational models constructed from non-invasive measurements can provide measures of baseline dyssynchrony and its reduction after CRT that may explain the degree of long-term reverse ventricular remodelling. METHODS AND RESULTS: LV end-systolic volume reduction (ΔESVLV) measured by 2D trans-thoracic echocardiography in eight patients following 6 months of CRT was significantly (P < 0.05) greater in responders (26 ± 20%, n = 4) than non-responders (11 ± 16%, n = 4). LV reverse remodelling did not correlate with baseline QRS duration or its change after biventricular pacing, but did correlate with baseline LV endocardial activation measured by electroanatomic mapping (R2 =0.71, P < 0.01). Patient-specific models of LBBB ventricular activation with parameters obtained by matching model-computed vectorcardiograms (VCG) to those derived from standard patient ECGs yielded LV endocardial activation times that correlated well with those measured from endocardial maps (R2 =0.90). Model-computed 3D LV activation times correlated strongly with the reduction in LVESV (R2 =0.93, P < 0.001). Computed decreases due to simulated CRT in the time delay between LV septal and lateral activation correlated strongly with ΔESVLV (R2 =0.92, P < 0.001). Models also suggested that optimizing VV delays may improve resynchronization by this measure of activation delay. CONCLUSIONS: Patient-specific computational models constructed from non-invasive measurements can compute estimates of LV dyssynchrony and their changes after CRT that may be as good as or better than electroanatomic mapping for predicting long-term reverse remodelling.[Abstract] [Full Text] [Related] [New Search]