A feasible and automatic free tool for T1 and ECV mapping. (January 2017)

• Record Type: Journal Article
• Authors: Altabella, Luisa; Borrazzo, Cristian; Carnì, Marco; Galea, Nicola; Francone, Marco; Fiorelli, Andrea; Di Castro, Elisabetta; Catalano, Carlo; Carbone, Iacopo
• Is Part Of: Physica medica. Volume 33(2017)
• Page Start: 47
• Page End: 55
• Publication Date: 2017-01
• Subjects: Cardiac magnetic resonance -- T1 mapping -- ECV mapping -- Myocardial fibrosis; Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2016.12.002
• Languages: English
• ISSNs: 1120-1797

Abstract

Highlights: A tool for T1 fitting and extracellular volume fraction (ECV) mapping is presented. T1 fitting algorithm allows a reliable and accurate pre/post contrast T1 estimation. ECV mapping procedures are completely automatic and reliable. Abstract: Purpose: Cardiac magnetic resonance (CMR) is a useful non-invasive tool for characterizing tissues and detecting myocardial fibrosis and edema. Estimation of extracellular volume fraction (ECV) using T1 sequences is emerging as an accurate biomarker in cardiac diseases associated with diffuse fibrosis. In this study, automatic software for T1 and ECV map generation consisting of an executable file was developed and validated using phantom and human data. Methods: T1 mapping was performed in phantoms and 30 subjects (22 patients and 8 healthy subjects) on a 1.5T MR scanner using the modified Look-Locker inversion-recovery (MOLLI) sequence prototype before and 15 min after contrast agent administration. T1 maps were generated using a Fast Nonlinear Least Squares algorithm. Myocardial ECV maps were generated using both pre- and post-contrast T1 image registration and automatic extraction of blood relaxation rates. Results: Using our software, pre- and post-contrast T1 maps were obtained in phantoms and healthy subjects resulting in a robust and reliable quantification as compared to reference software. Coregistration of pre- and post-contrast images improved the quality of ECV maps. Mean ECV value in healthy subjects was 24.5% ± 2.5%. Conclusions: This study demonstrated that it is possible to obtain accurate T1 maps and informative ECV maps using our software. Pixel-wise ECV maps obtained with this automatic software made it possible to visualize and evaluate the extent and severity of ECV alterations.