BACKGROUND: Response to cardiac resynchronization therapy depends both on dyssynchrony and (regional) contractility. We hypothesized that septal deformation can be used to infer integrated information on dyssynchrony and regional contractility, and thereby predict cardiac resynchronization therapy response. METHODS AND RESULTS: In 132 cardiac resynchronization therapy candidates with left bundle branch block (LBBB)-like electrocardiogram morphology (left ventricular ejection fraction 19±6%; QRS width 170±23 ms), longitudinal septal strain was assessed by speckle tracking echocardiography. To investigate the effects of dyssynchronous activation and differences in septal and left ventricular free wall contractility on septal deformation pattern, we used the CircAdapt computer model of the human heart and circulation. In the patients, 3 characteristic septal deformation patterns were identified: LBBB-1=double-peaked systolic shortening (n=28); LBBB-2=early systolic shortening followed by prominent systolic stretching (n=34); and LBBB-3=pseudonormal shortening with less pronounced late systolic stretch (n=70). LBBB-3 revealed more scar (2 [2-5] segments) compared with LBBB-1 and LBBB-2 (both 0 [0-1], P<0.05). In the model, imposing a time difference of activation between septum and left ventricular free wall resulted in pattern LBBB-1. This transformed into pattern LBBB-2 by additionally simulating septal hypocontractility, and into pattern LBBB-3 by imposing additional left ventricular free wall or global left ventricular hypocontractility. Improvement of left ventricular ejection fraction and reduction of left ventricular volumes after cardiac resynchronization therapy were most pronounced in LBBB-1 and worst in LBBB-3 patients. CONCLUSIONS: A double-peaked systolic septal deformation pattern is characteristic for LBBB and results from intraventricular dyssynchrony. Abnormal contractility modifies this pattern. A computer model can be helpful in understanding septal deformation and predicting cardiac resynchronization therapy response.
BACKGROUND: Response to cardiac resynchronization therapy depends both on dyssynchrony and (regional) contractility. We hypothesized that septal deformation can be used to infer integrated information on dyssynchrony and regional contractility, and thereby predict cardiac resynchronization therapy response. METHODS AND RESULTS: In 132 cardiac resynchronization therapy candidates with left bundle branch block (LBBB)-like electrocardiogram morphology (left ventricular ejection fraction 19±6%; QRS width 170±23 ms), longitudinal septal strain was assessed by speckle tracking echocardiography. To investigate the effects of dyssynchronous activation and differences in septal and left ventricular free wall contractility on septal deformation pattern, we used the CircAdapt computer model of the human heart and circulation. In the patients, 3 characteristic septal deformation patterns were identified: LBBB-1=double-peaked systolic shortening (n=28); LBBB-2=early systolic shortening followed by prominent systolic stretching (n=34); and LBBB-3=pseudonormal shortening with less pronounced late systolic stretch (n=70). LBBB-3 revealed more scar (2 [2-5] segments) compared with LBBB-1 and LBBB-2 (both 0 [0-1], P<0.05). In the model, imposing a time difference of activation between septum and left ventricular free wall resulted in pattern LBBB-1. This transformed into pattern LBBB-2 by additionally simulating septal hypocontractility, and into pattern LBBB-3 by imposing additional left ventricular free wall or global left ventricular hypocontractility. Improvement of left ventricular ejection fraction and reduction of left ventricular volumes after cardiac resynchronization therapy were most pronounced in LBBB-1 and worst in LBBB-3 patients. CONCLUSIONS: A double-peaked systolic septal deformation pattern is characteristic for LBBB and results from intraventricular dyssynchrony. Abnormal contractility modifies this pattern. A computer model can be helpful in understanding septal deformation and predicting cardiac resynchronization therapy response.
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: Giselle Revah; Vincent Wu; Peter R Huntjens; Eve Piekarski; Janice Y Chyou; Leon Axel Journal: Int J Cardiovasc Imaging Date: 2016-06-15 Impact factor: 2.357
Authors: Michael Huntgeburth; Ingo Germund; Lianne M Geerdink; Narayanswami Sreeram; Floris E A Udink Ten Cate Journal: Cardiovasc Diagn Ther Date: 2019-10