Septal Deformation Patterns Delineate Mechanical Dyssynchrony and Regional Differences in Contractility: Analysis of Patient Data Using a Computer Model Leenders et al: Septal Deformation in Dyssynchronous Heart Failure

Background Response to cardiac resynchronization therapy (CRT) 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 CRT response. Methods and Results In 132 CRT-candidates with left bundle branch block (LBBB)like ECG morphology (left ventricular (LV) ejection fraction 19±6%; QRS-width 170±23ms), longitudinal septal strain was assessed by speckle tracking echocardiography. To investigate the effects of dyssynchronous activation and differences in septal and LV free wall (LVFW) contractility on septal deformation pattern, we utilized the CircAdapt computer model of the human heart and circulation. In the patients, three 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 to LBBB-1 and LBBB-2 (both 0 [0-1], p<0.05). In the model, imposing a time difference of activation between septum and LVFW resulted in pattern LBBB-1. This transformed into pattern LBBB-2 by additionally simulating septal hypocontractility and into pattern LBBB-3 by imposing additional LVFW or global LV hypocontractility. Improvement of LV ejection fraction and reduction of LV volumes after CRT 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 CRT response.