title: Comparison of spoiled gradient echo and steady-state free-precession imaging for native myocardial T1 mapping using the slice-interleaved T1 mapping (STONE) sequence.
abstract: Cardiac T1 mapping allows non-invasive imaging of interstitial diffuse fibrosis. Myocardial T1 is commonly calculated by voxel-wise fitting of the images acquired using balanced steady-state free precession (SSFP) after an inversion pulse. However, SSFP imaging is sensitive to B1 and B0 imperfection, which may result in additional artifacts. A gradient echo (GRE) imaging sequence has been used for myocardial T1 mapping; however, its use has been limited to higher magnetic field to compensate for the lower signal-to-noise ratio (SNR) of GRE versus SSFP imaging. A slice-interleaved T1 mapping (STONE) sequence with SSFP readout (STONE-SSFP) has been recently proposed for native myocardial T1 mapping, which allows longer recovery of magnetization (>8 R-R) after each inversion pulse. In this study, we hypothesize that a longer recovery allows higher SNR and enables native myocardial T1 mapping using STONE with GRE imaging readout (STONE-GRE) at 1.5T. Numerical simulations and phantom and in vivo imaging were performed to compare the performance of STONE-GRE and STONE-SSFP for native myocardial T1 mapping at 1.5T. In numerical simulations, STONE-SSFP shows sensitivity to both T2 and off resonance. Despite the insensitivity of GRE imaging to T2 , STONE-GRE remains sensitive to T2 due to the dependence of the inversion pulse performance on T2 . In the phantom study, STONE-GRE had inferior accuracy and precision and similar repeatability as compared with STONE-SSFP. In in vivo studies, STONE-GRE and STONE-SSFP had similar myocardial native T1 times, precisions, repeatabilities and subjective T1 map qualities. Despite the lower SNR of the GRE imaging readout compared with SSFP, STONE-GRE provides similar native myocardial T1 measurements, precision, repeatability, and subjective image quality when compared with STONE-SSFP at 1.5T.
authors.affiliation: Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.|Department of Computer Science, Technical University of Munich, Munich, Germany.
authors.forename: Jihye
authors.initials: J
authors.lastname: Jang
authors.affiliation: Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.
authors.forename: Steven
authors.initials: S
authors.lastname: Bellm
authors.affiliation: Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.
authors.forename: Sébastien
authors.initials: S
authors.lastname: Roujol
authors.affiliation: Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.|Biomedical Engineering Department, Cairo University, Giza, Egypt.
authors.forename: Tamer A
authors.identifier: 0000-0003-4431-8646
authors.initials: TA
authors.lastname: Basha
authors.affiliation: Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.|Division of Imaging Sciences & Biomedical Engineering, King's College London, London, UK.
authors.forename: Maryam
authors.initials: M
authors.lastname: Nezafat
authors.affiliation: Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.
authors.forename: Shingo
authors.initials: S
authors.lastname: Kato
authors.affiliation: Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.|Computer Assisted Clinical Medicine, University Medical Center Mannheim, Heidelberg University, Mannheim, Germany.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Weingärtner
authors.affiliation: Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA. rnezafat@bidmc.harvard.edu.
authors.forename: Reza
authors.initials: R
authors.lastname: Nezafat
mesh_terms: D000328:Adult; D000465:Algorithms; D057791:Cardiac Imaging Techniques / Q000379:methods*; D005260:Female; D006321:Heart / Q000000981:diagnostic imaging*; D006331:Heart Diseases / Q000000981:diagnostic imaging*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted
keywords: balanced steady-state free precession; cardiovascular MR (CMR) methods; myocardial T1 mapping; relaxometry; slice-interleaved T1 mapping; spoiled gradient echo