Yoon-Chul Kim1, Khu Rai Kim2, Hyelee Lee3, Yeon Hyeon Choe4. 1. Clinical Research Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea. 2. Department of Electronic Engineering, Sogang University, Seoul, South Korea. 3. Department of Mathematics, Sogang University, Seoul, South Korea. 4. Department of Radiology and HVSI Imaging Center, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Ilwon-ro, Gangnam-gu, Seoul, 06351, South Korea. ychoe11@gmail.com.
Abstract
BACKGROUND: The purpose of this study was to develop a software tool and evaluate different T1 map calculation methods in terms of computation time in cardiac magnetic resonance imaging. METHODS: The modified Look-Locker inversion recovery (MOLLI) sequence was used to acquire multiple inversion time (TI) images for pre- and post-contrast T1 mapping. The T1 map calculation involved pixel-wise curve fitting based on the T1 relaxation model. A variety of methods were evaluated using data from 30 subjects for computational efficiency: MRmap, python Levenberg-Marquardt (LM), python reduced-dimension (RD) non-linear least square, C++ single- and multi-core LM, and C++ single- and multi-core RD. RESULTS: Median (interquartile range) computation time was 126 s (98-141) for the publicly available software MRmap, 261 s (249-282) for python LM, 77 s (74-80) for python RD, 3.4 s (3.1-3.6) for C++ multi-core LM, and 1.9 s (1.9-2.0) for C++ multi-core RD. The fastest C++ multi-core RD and the publicly available MRmap showed good agreement of myocardial T1 values, resulting in 95% Bland-Altman limits of agreement of (- 0.83 to 0.58 ms) and (- 6.57 to 7.36 ms) with mean differences of - 0.13 ms and 0.39 ms, for the pre- and post-contrast, respectively. CONCLUSION: The C++ multi-core RD was the fastest method on a regular eight-core personal computer for pre- or post-contrast T1 map calculation. The presented software tool (fT1fit) facilitated rapid T1 map and extracellular volume fraction map calculations.
BACKGROUND: The purpose of this study was to develop a software tool and evaluate different T1 map calculation methods in terms of computation time in cardiac magnetic resonance imaging. METHODS: The modified Look-Locker inversion recovery (MOLLI) sequence was used to acquire multiple inversion time (TI) images for pre- and post-contrast T1 mapping. The T1 map calculation involved pixel-wise curve fitting based on the T1 relaxation model. A variety of methods were evaluated using data from 30 subjects for computational efficiency: MRmap, python Levenberg-Marquardt (LM), python reduced-dimension (RD) non-linear least square, C++ single- and multi-core LM, and C++ single- and multi-core RD. RESULTS: Median (interquartile range) computation time was 126 s (98-141) for the publicly available software MRmap, 261 s (249-282) for python LM, 77 s (74-80) for python RD, 3.4 s (3.1-3.6) for C++ multi-core LM, and 1.9 s (1.9-2.0) for C++ multi-core RD. The fastest C++ multi-core RD and the publicly available MRmap showed good agreement of myocardial T1 values, resulting in 95% Bland-Altman limits of agreement of (- 0.83 to 0.58 ms) and (- 6.57 to 7.36 ms) with mean differences of - 0.13 ms and 0.39 ms, for the pre- and post-contrast, respectively. CONCLUSION: The C++ multi-core RD was the fastest method on a regular eight-core personal computer for pre- or post-contrast T1 map calculation. The presented software tool (fT1fit) facilitated rapid T1 map and extracellular volume fraction map calculations.
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