BACKGROUND: The power of echocardiographic dyssynchrony indices to predict response to cardiac resynchronization therapy (CRT) appears to vary between indices and between studies. We investigated whether the variability of predictive power between the dyssynchrony indices can be explained by differences in their operational definitions. METHODS AND RESULTS: In 132 CRT-candidates (left ventricular [LV] ejection fraction, 19 ± 6%; QRS width, 170 ± 22 ms), 4 mechanical dyssynchrony indices (septal systolic rebound stretch [SRSsept], interventricular mechanical dyssynchrony [IVMD], septal-to-lateral peak shortening delay [Strain-SL], and septal-to-posterior wall motion delay [SPWMD]) were quantified at baseline. CRT response was quantified as 6-month percent change of LV end-systolic volume. Multiscale computer simulations of cardiac mechanics and hemodynamics were used to assess the relationships between dyssynchrony indices and CRT response within wide ranges of dyssynchrony of LV activation and reduced contractility. In patients, SRSsept showed best correlation with CRT response followed by IVMD, Strain-SL, and SPWMD (R=-0.56, -0.50, -0.48, and -0.39, respectively; all P<0.01). In patients and simulations, SRSsept and IVMD showed a continuous linear relationship with CRT response, whereas Strain-SL and SPWMD showed discontinuous relationships characterized by data clusters. Model simulations revealed that this data clustering originated from the complex multipeak pattern of septal strain and motion. In patients and simulations with (simulated) LV scar, SRSsept and IVMD retained their linear relationship with CRT response, whereas Strain-SL and SPWMD did not. CONCLUSIONS: The power to predict CRT response differs between indices of mechanical dyssynchrony. SRSsept and IVMD better represent LV dyssynchrony amenable to CRT and better predict CRT response than the indices assessing time-to-peak deformation or motion.
BACKGROUND: The power of echocardiographic dyssynchrony indices to predict response to cardiac resynchronization therapy (CRT) appears to vary between indices and between studies. We investigated whether the variability of predictive power between the dyssynchrony indices can be explained by differences in their operational definitions. METHODS AND RESULTS: In 132 CRT-candidates (left ventricular [LV] ejection fraction, 19 ± 6%; QRS width, 170 ± 22 ms), 4 mechanical dyssynchrony indices (septal systolic rebound stretch [SRSsept], interventricular mechanical dyssynchrony [IVMD], septal-to-lateral peak shortening delay [Strain-SL], and septal-to-posterior wall motion delay [SPWMD]) were quantified at baseline. CRT response was quantified as 6-month percent change of LV end-systolic volume. Multiscale computer simulations of cardiac mechanics and hemodynamics were used to assess the relationships between dyssynchrony indices and CRT response within wide ranges of dyssynchrony of LV activation and reduced contractility. In patients, SRSsept showed best correlation with CRT response followed by IVMD, Strain-SL, and SPWMD (R=-0.56, -0.50, -0.48, and -0.39, respectively; all P<0.01). In patients and simulations, SRSsept and IVMD showed a continuous linear relationship with CRT response, whereas Strain-SL and SPWMD showed discontinuous relationships characterized by data clusters. Model simulations revealed that this data clustering originated from the complex multipeak pattern of septal strain and motion. In patients and simulations with (simulated) LV scar, SRSsept and IVMD retained their linear relationship with CRT response, whereas Strain-SL and SPWMD did not. CONCLUSIONS: The power to predict CRT response differs between indices of mechanical dyssynchrony. SRSsept and IVMD better represent LV dyssynchrony amenable to CRT and better predict CRT response than the indices assessing time-to-peak deformation or motion.
Authors: Joost Lumens; Sylvain Ploux; Marc Strik; John Gorcsan; Hubert Cochet; Nicolas Derval; Maria Strom; Charu Ramanathan; Philippe Ritter; Michel Haïssaguerre; Pierre Jaïs; Theo Arts; Tammo Delhaas; Frits W Prinzen; Pierre Bordachar Journal: J Am Coll Cardiol Date: 2013-09-04 Impact factor: 24.094
Authors: Christopher Piorkowski; Arash Arya; Craig D Markovitz; Hedi Razavi; Chunlan Jiang; Stuart Rosenberg; Ole-A Breithardt; Sascha Rolf; Silke John; Jedrzej Kosiuk; Yan Huo; Michael Döring; Sergio Richter; Kyungmoo Ryu; Thomas Gaspar; Frits W Prinzen; Gerhard Hindricks; Philipp Sommer Journal: J Interv Card Electrophysiol Date: 2018-01-31 Impact factor: 1.900
Authors: Jetske van 't Sant; Aernoud T L Fiolet; Iris A H ter Horst; Maarten J Cramer; Mirjam H Mastenbroek; Wouter M van Everdingen; Thomas P Mast; Pieter A Doevendans; Henneke Versteeg; Mathias Meine Journal: PLoS One Date: 2015-05-01 Impact factor: 3.240