The prediction of ventricular arrhythmias and/or sudden cardiac death has been the “Holy Grail” of electrophysiology for many decades. Despite testing of multiple invasive and non-invasive strategies, most of the time the left ventricular ejection fraction (EF) ends up being the (imperfect) winner of these comparisons.

Magnetic resonance imaging has introduced a variety of imaging parameters that might prove useful and possibly superior to the simple EF. Over the last few years, the “grey zone” has evolved as such a possible parameter. On delayed enhanced MRI scar it will retain gadolinium and appear white, while normal myocardium after contrast washout appears black. Areas of partially surviving myocardium and interspersed scar will have a signal intensity between white and black, hence labeled the “grey zone.” It is a plausible biological hypothesis that such a heterogeneous area might be proarrhythmic.

Yan and colleagues(1) found that the grey zone (defined as >2 and <3 standard deviations above the signal of a healthy segment) made up about one-fourth of the 17% LV scar found on average in 144 patients with CAD. The grey zone was an independent predictor of all-cause and CV mortality after 2.4 years of follow up. Schmidt et al(2) found that using a different algorithm that defined the grey zone as <50% of the brightest scar point between 38-48% of scar consisted of grey zone in 47 patients with ischemic cardiomyopathy. A large grey zone was associated with inducibility of monomorpthic VT during an EP study. Finally, Roess et al(3) used a modified “Schmidt-method” and found in 91 patients with ischemic cardiomyopathy that the grey zone accounted for about 42.5% of the 38% scar found in the LV. Grey zone was the strongest predictor of ventricular arrhythmias leading to ICD therapy after 8.5 months follow-up.

The evidence is growing that more than just a binary scar yes/no assessment can be derived from MRI. Still, further validation is needed and some critics think that much of the grey zone is just an artifact of blurring and partial volume effect. To their credit, the author at least attempted to look for an association with heart rate (which should result in more blurring) and did not find a statistical correlation.

At the very least it will be another step on the quest for better prediction of ventricular arrhythmia and SCD. Maybe, rather think “Coke can” than “Holy Grail”…

References
1. Yan AT, Shayne AJ, Brown KA, et al. Characterization of the peri-infarct zone by contrast-enhanced cardiac magnetic resonance imaging is a powerful predictor of post-myocardial infarction mortality. Circulation 2006;114:32-39.
2. Schmidt A, Azevedo CF, Cheng A, et al. Infarct tissue heterogeneity by magnetic resonance imaging identifies enhanced cardiac arrhythmia susceptibility in patients with left ventricular dysfunction. Circulation 2007;115:2006-2014.
3. Roes SD, Borleffs CJ, van der Geest RJ, et al. Infarct tissue heterogeneity assessed with contrast-enhanced MRI predicts spontaneous ventricular arrhythmia in patients with ischemic cardiomyopathy and implantable cardioverter-defibrillator. Circ Cardiovasc Imaging 2009;2:183-190.

Timm Dickfeld, MD, PhD is the Chief of Electrophysiology at the VA Baltimore, Associate Professor of Medicine at the University of Maryland, and Founder of the Maryland Arrhythmia and Cardiology Imaging Group (MACIG).