Luisa Altabella1, Cristian Borrazzo2, Marco Carnì3, Nicola Galea4, Marco Francone4, Andrea Fiorelli4, Elisabetta Di Castro2, Carlo Catalano4, Iacopo Carbone4. 1. Medical Physics Unit, Policlinico Umberto I, Rome, Italy. Electronic address: luisa.altabella@gmail.com. 2. Medical Physics Unit, Policlinico Umberto I, Rome, Italy; Department of Molecular Medicine, University of Rome La Sapienza, Viale Regina Elena 291, 00161 Rome, Italy. 3. Medical Physics Unit, Policlinico Umberto I, Rome, Italy. 4. Department of Radiological, Oncological and Pathological Sciences, University of Rome La Sapienza, Rome, Italy.
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.
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.
Authors: Francesco Sardanelli; Simone Schiaffino; Moreno Zanardo; Francesco Secchi; Paola Maria Cannaò; Federico Ambrogi; Giovanni Di Leo Journal: Eur Radiol Date: 2019-05-02 Impact factor: 5.315
Authors: Henrik Engblom; Mikael Kanski; Sascha Kopic; David Nordlund; Christos G Xanthis; Robert Jablonowski; Einar Heiberg; Anthony H Aletras; Marcus Carlsson; Håkan Arheden Journal: J Cardiovasc Magn Reson Date: 2018-06-28 Impact factor: 5.364