Infarct tissue heterogeneity by magnetic resonance imaging identifies enhanced cardiac arrhythmia susceptibility in patients with left ventricular dysfunction

Abstract

Background: The extent of the peri-infarct zone by magnetic resonance imaging (MRI) has been related to all-cause mortality in patients with coronary artery disease. This relationship may result from arrhythmogenesis in the infarct border. However, the relationship between tissue heterogeneity in the infarct periphery and arrhythmic substrate has not been investigated. In the present study, we quantify myocardial infarct heterogeneity by contrast-enhanced MRI and relate it to an electrophysiological marker of arrhythmic substrate in patients with left ventricular (LV) systolic dysfunction undergoing prophylactic implantable cardioverter defibrillator placement.

Methods and results: Before implantable cardioverter defibrillator implantation for primary prevention of sudden cardiac death, 47 patients underwent cine and contrast-enhanced MRI to measure LV function, volumes, mass, and infarct size. A method for quantifying the heterogeneous infarct periphery and the denser infarct core is described. MRI indices were related to inducibility of sustained monomorphic ventricular tachycardia during electrophysiological or device testing. For the noninducible versus inducible patients, LV ejection fraction (30+/-10% versus 29+/-7%, P=0.79), LV end-diastolic volume (220+/-70 versus 228+/-57 mL, P=0.68), and infarct size by standard contrast-enhanced MRI definitions (P=NS) were similar. Quantification of tissue heterogeneity at the infarct periphery was strongly associated with inducibility for monomorphic ventricular tachycardia (noninducible versus inducible: 13+/-9 versus 19+/-8 g, P=0.015) and was the single significant factor in a stepwise logistic regression.

Conclusions: Tissue heterogeneity is present and quantifiable within human infarcts. More extensive tissue heterogeneity correlates with increased ventricular irritability by programmed electrical stimulation. These findings support the hypothesis that anatomic tissue heterogeneity increases susceptibility to ventricular arrhythmias in patients with prior myocardial infarction and LV dysfunction.

Conflict of interest statement

Disclosures

Drs Foo and Gupta are employed by GE Healthcare Technologies. The remaining authors report no conflicts.

Figures

Figure 1

Algorithm for determining the gray zone. Basal short-axis delayed enhanced magnetic resonance image (A) shows the inferolateral infarct as high SI and the normal myocardium as dark SI. To define the gray zone, the following algorithm was used: the endocardial and epicardial borders were drawn by a trained observer. The observer then planimetered an ROI in the remote, noninfarcted myocardium, and the upper limit of normal SI was defined as peak remote SI (peak remote SI=10 in the example shown). The myocardial segment containing the hyperenhanced region was loosely outlined. Using peak remote SI as the lower SI cutoff for abnormal myocardium, the actual region of abnormal late gadolinium enhancement (LGE) was determined by automatic thresholding (ie, any region with SI > peak remote SI is hyperenhanced). The SI profile (B) for this hyperenhanced region is displayed with SI value on the x-axis and number of pixels on the y-axis. The peak infarct (LGE) SI is displayed (peak LGE SI=56 in the example shown). The upper SI cutoff for the gray zone was calculated as 50% of peak LGE SI (0.5×56=28 in the example). The gray zone extent was automatically determined as the region (C, shown in yellow) with SI between peak remote SI and 50% of peak LGE SI (between 10 and 28 in the example). The core region (C, shown in red) is the area with SI >50% of peak SI.

Figure 2

Gray zone measurement. A, Late gadolinium-enhanced short-axis magnetic resonance image of a patient with an anterior infarct. The peak SI within the remote, noninfarcted region was 9 in this example. Abnormal enhancement was defined as SI >9. The histogram of SI within the hyperenhanced region is displayed in B. Peak SI within the high SI region is 90 in this example. The upper threshold for gray zone extent is 50% of the peak SI (or 90×0.50=45 in this example). The gray zone (C, yellow area) is the region with SI between 9 and 45. The core region (C, red area) is the region with SI >45.

Figure 3

Time course of gray zone (GZ) extent. A, Representative short-axis late gadolinium-enhanced magnetic resonance image of an anterior infarct, imaged at 2 time points, 10 minutes apart. The SI cutoffs for determining the gray zone and the resultant gray zone extent are similar (9 and 47 for time point 1 and 11 and 47 for time point 2). B, Bland-Altman plot for gray zone quantification at 2 time points from contrast bolus (see text).

Figure 4

Interobserver variability of gray zone extent. Bland-Altman plot for interobserver variability of gray zone quantification.

Figure 5

SI curves over time in myocardial regions of interest. Absolute SI (y-axis) in the remote, gray, and infarct core regions over time after contrast bolus from 8 patients. A significant difference exists among the 3 regions (ANOVA P<0.001). However, the difference is between the remote and core (P<0.001) and gray zone and core (P<0.001); the wash-in pattern for the remote and gray zone was not significantly different over this time frame (P=NS).