Abstract
BackgroundThe 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.MethodsThe 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.ResultsMedian (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.ConclusionThe 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.
Highlights
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
Recent related studies of software development in parameter mapping focused on magnetization transfer imaging [11] and neuroimage processing [12], and they lack the comparison of computational efficiency among different calculation methods
We focus on evaluating the performance of different T1 map calculation methods with an emphasis on the comparison between the LM method and the reduced dimension non-linear least squares (RD-NLS) method implemented in C++ as well as an emphasis on the comparison between the RD-NLS method and the publicly available MRmap for T1 estimation accuracy in the myocardium
Summary
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. Cardiac T1 mapping in magnetic resonance imaging (MRI) is a non-invasive and quantitative method for the characterization of the myocardial tissue [1,2,3,4] and is useful for the evaluation of diffuse myocardial fibrosis [5]. It typically involves two separate image acquisitions: native T1 mapping (a.k.a. pre-contrast T1 mapping) and post-contrast T1 mapping. Recent related studies of software development in parameter mapping focused on magnetization transfer imaging [11] and neuroimage processing [12], and they lack the comparison of computational efficiency among different calculation methods
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