Automatic assessment of myocardial fibrosis by delayed enhanced magnetic resonance imaging

Cardiovascular magnetic resonance is able to detect myocardial fibrosis by delayed enhancement of a contrast media. However, detection and quantification of fibrosis is difficult due to the complex pattern of the fibrotic tissue signal. In this study a software model of the signal distribution in normal and fibrotic myocardium was inferred from MR images of healthy subjects and patients with hypertrophic cardiomyopathy. The developed model allowed to define a methodology for the discrimination of fibrotic areas. The method was based on the fitting of the signal histogram with a modified gamma function. The scale parameter characterizing the gamma function was used as discriminating factor in MR image analysis, reaching a sensitivity of 85% and a specificity of 86%. The proposed approach outperformed the standard approach used in the clinical practice.