Automated Pericardial Fat Quantification from Coronary Magnetic Resonance Angiography

Pericardial fat volume (PFV) is emerging as an important parameter for cardiovascular risk stratification. We propose a hybrid multi-atlas and graph-based segmentation approach for automated PFV quantification from water/fat-resolved whole-heart “needlefree” non-contrast coronary magnetic resonance angiography (MRA). We validated the quantification results on 6 subjects and compared them with manual quantifications by an expert reader. The PFV quantified by our algorithm was 62.78± 27.85 cm3 compared to 58.66± 27.05 cm3 by the expert, which were not significantly different (p = 0.47, mean percent difference 9.6 ± 9.5%) and showed excellent correlation (R = 0.89, p < 0.01). The mean Dice coefficient of pericardial fat voxels was 0.82±0.06 (median 0.85). Using our approach, physicians can accurately quantify patients’ pericardial fat volume from MRI without tedious manual tracing. To our knowledge, this is the first report of an automated algorithm for PFV from whole-heart, non-contrast coronary MRA images. c © 2015. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms. 2 MRA PERICARDIAL FAT QUANTIFICATION: MANUSCRIPT Figure 1: Example transverse slices of MRA data.