Quantitative analysis of late gadolinium enhancement in hypertrophic cardiomyopathy

Background. Cardiovascular Magnetic resonance (CMR) with the late gadolinium enhancement (LGE) technique allows the detection of myocardial fibrosis in Hypertrophic cardiomyopathy (HCM). The aim of this study was to compare different methods of automatic quantification of LGE in HCM patients. Methods: Forty HCM patients (mean age 48 y, 30 males) and 20 normal subjects (mean age 38 y, 16 males) underwent CMR, and we compared 3 methods of quantification of LGE: 1) in the SD2 method a region of interest (ROI) was placed within the normal myocardium and enhanced myocardium was considered as having signal intensity >2 SD above the mean of ROI; 2) in the SD6 method enhanced myocardium was defined with a cut-off of 6 SD above mean of ROI; 3) in the RC method a ROI was placed in the background of image, a Rayleigh curve was created using the SD of that ROI and used as ideal curve of distribution of signal intensity of a perfectly nulled myocardium. The maximal signal intensity found in the Rayleigh curve was used as cut-off for enhanced myocardium. Parametric images depicting non enhanced and enhanced myocardium was created using each method. Three investigators assigned a score to each method by the comparison of the original LGE image to the respective parametric map generated. Results. Patients with HCM had lower concordance between the measured curve of distribution of signal intensity and the Rayleigh curve than controls (63.7 12.3% vs 92.2 2.3%, p < 0.0001). A cut off of concordance < 82.9% had a 97.1% sensitivity and 92.3% specificity to distinguish HCM from controls. The RC method had higher score than the other methods. The average extent of enhanced myocardium measured by SD6 and Rayleigh curve method was not significant different but SD6 method showed underestimation of enhancement in 12% and overestimation in 5% of patients with HCM. Conclusions. Quantification of fibrosis in LGE images with a cut-off derived from the Rayleigh curve is more accurate than using a fixed cut-off. © 2010 Aquaro et al; licensee BioMed Central Ltd.