Theodorus A.M. Kaandorp

BACKGROUND: Currently, one third of patients treated with cardiac resynchronization therapy (CRT) do not respond. Nonresponse to CRT may be explained by the presence of scar tissue in the posterolateral left ventricular (LV) segments, which may result in ineffective LV pacing and inadequate LV resynchronization. In the present study, the relationship between transmural posterolateral scar tissue and response to CRT was evaluated. METHODS AND RESULTS: Forty consecutive patients with end-stage heart failure (NYHA class III/IV), LV ejection fraction < or =35%, QRS duration >120 ms, left bundle-branch block, and chronic coronary artery disease were included. The localization and transmurality of scar tissue were evaluated with contrast-enhanced MRI. Next, LV dyssynchrony was assessed at baseline and immediately after implantation with tissue Doppler imaging. Clinical parameters, LV volumes, and LV ejection fraction were assessed at baseline and at a 6-month follow-up. Fourteen patients (35%) had a transmural (>50% of LV wall thickness) posterolateral scar. In contrast to patients without posterolateral scar tissue, these patients showed a low response rate (14% versus 81%; P<0.05) and did not show improvement in clinical or echocardiographic parameters. In addition, LV dyssynchrony remained unchanged after CRT implantation (84+/-46 versus 78+/-41 ms; P=NS). Patients without posterolateral scar tissue and severe baseline dyssynchrony (> or =65 ms) showed an excellent response rate of 95% compared with patients with a posterolateral scar and/or absent LV dyssynchrony (11%). CONCLUSIONS: CRT does not reduce LV dyssynchrony in patients with transmural scar tissue in the posterolateral LV segments, resulting in clinical and echocardiographic nonresponse to CRT.

BACKGROUND: The relation between infarct tissue heterogeneity on contrast-enhanced MRI and the occurrence of spontaneous ventricular arrhythmia (or sudden cardiac death) is unknown. Therefore, the study purpose was to evaluate the predictive value of infarct tissue heterogeneity assessed with contrast-enhanced MRI on the occurrence of spontaneous ventricular arrhythmia with subsequent implantable cardioverter-defibrillator (ICD) therapy (as surrogate of sudden cardiac death) in patients with previous myocardial infarction. METHODS AND RESULTS: Ninety-one patients (age, 65+/-11 years) with previous myocardial infarction scheduled for ICD implantation underwent cine MRI to evaluate left ventricular function and volumes and contrast-enhanced MRI for characterization of scar tissue (infarct gray zone as measure of infarct tissue heterogeneity, infarct core, and total infarct size). Appropriate ICD therapy was documented in 18 patients (20%) during a median follow-up of 8.5 months (interquartile range, 2.1 to 20.3). Multivariable Cox proportional hazards analysis revealed that infarct gray zone was the strongest predictor of the occurrence of spontaneous ventricular arrhythmia with subsequent ICD therapy (hazard ratio, 1.49/10 g; CI, 1.01 to 2.20; chi(2)=4.0; P=0.04). CONCLUSIONS: Infarct tissue heterogeneity on contrast-enhanced MRI is the strongest predictor of spontaneous ventricular arrhythmia with subsequent ICD therapy (as surrogate of sudden cardiac death) among other clinical and MRI variables, that is, total infarct size and left ventricular function and volumes, in patients with previous myocardial infarction.

In this paper, a statistical shape analysis method for myocardial contraction is presented that was built to detect and locate regional wall motion abnormalities (RWMA). For each slice level (base, middle, and apex), 44 short-axis magnetic resonance images were selected from healthy volunteers to train a statistical model of normal myocardial contraction using independent component analysis (ICA). A classification algorithm was constructed from the ICA components to automatically detect and localize abnormally contracting regions of the myocardium. The algorithm was validated on 45 patients suffering from ischemic heart disease. Two validations were performed; one with visual wall motion scores (VWMS) and the other with wall thickening (WT) used as references. Accuracy of the ICA-based method on each slice level was 69.93% (base), 89.63% (middle), and 72.78% (apex) when WT was used as reference, and 63.70% (base), 67.41% (middle), and 66.67% (apex) when VWMS was used as reference. From this we conclude that the proposed method is a promising diagnostic support tool to assist clinicians in reducing the subjectivity in VWMS.