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Proceedings Paper

A new linear least squares method for T1 estimation from SPGR signals with multiple TRs
Author(s): Lin-Ching Chang; Cheng Guan Koay; Peter J. Basser; Carlo Pierpaoli
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Paper Abstract

The longitudinal relaxation time, T1, can be estimated from two or more spoiled gradient recalled echo x (SPGR) images with two or more flip angles and one or more repetition times (TRs). The function relating signal intensity and the parameters are nonlinear; T1 maps can be computed from SPGR signals using nonlinear least squares regression. A widely-used linear method transforms the nonlinear model by assuming a fixed TR in SPGR images. This constraint is not desirable since multiple TRs are a clinically practical way to reduce the total acquisition time, to satisfy the required resolution, and/or to combine SPGR data acquired at different times. A new linear least squares method is proposed using the first order Taylor expansion. Monte Carlo simulations of SPGR experiments are used to evaluate the accuracy and precision of the estimated T1 from the proposed linear and the nonlinear methods. We show that the new linear least squares method provides T1 estimates comparable in both precision and accuracy to those from the nonlinear method, allowing multiple TRs and reducing computation time significantly.

Paper Details

Date Published: 13 March 2009
PDF: 8 pages
Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging, 72584O (13 March 2009); doi: 10.1117/12.811618
Show Author Affiliations
Lin-Ching Chang, The Catholic Univ. of America (United States)
National Institutes of Health (United States)
Cheng Guan Koay, National Institutes of Health (United States)
Peter J. Basser, National Institutes of Health (United States)
Carlo Pierpaoli, National Institutes of Health (United States)


Published in SPIE Proceedings Vol. 7258:
Medical Imaging 2009: Physics of Medical Imaging
Ehsan Samei; Jiang Hsieh, Editor(s)

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