Spatially regularized T1 estimation from variable flip angles MRI

Hesheng Wang

doi:10.1118/1.4722747

2012-06-13

Hesheng Wang *

Yue Cao (Yue Cao)

DOI：10.1118/1.4722747

原文链接

查看原文

摘要

En 中文

Purpose: To develop efficient algorithms for fast voxel-by-voxel quantification of tissue longitudinal relaxation time (T-1) from variable flip angles magnetic resonance images (MRI) to reduce voxel-level noise without blurring tissue edges. Methods: T-1 estimations regularized by total variation (TV) and quadratic penalty are developed to measure T-1 from fast variable flip angles MRI and to reduce voxel-level noise without decreasing the accuracy of the estimates. First, a quadratic surrogate for a log likelihood cost function of T-1 estimation is derived based upon the majorization principle, and then the TV-regularized surrogate function is optimized by the fast iterative shrinkage thresholding algorithm. A fast optimization algorithm for the quadratically regularized T-1 estimation is also presented. The proposed methods are evaluated by the simulated and experimental MR data. Results: The means of the T-1 values in the simulated brain data estimated by the conventional, TV-regularized, and quadratically regularized methods have less than 3% error from the true T-1 in both GM and WM tissues with image noise up to 9%. The relative standard deviations (SDs) of the T-1 values estimated by the conventional method are more than 12% and 15% when the images have 7% and 9% noise, respectively. In comparison, the TV-regularized and quadratically regularized methods are able to suppress the relative SDs of the estimated T-1 to be less than 2% and 3%, respectively, regardless of the image noise level. However, the quadratically regularized method tends to overblur the edges compared to the TV-regularized method. Conclusions: The spatially regularized methods improve quality of T-1 estimation from multiflip angles MRI. Quantification of dynamic contrast-enhanced MRI can benefit from the high quality measurement of native T-1. (C) 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4722747]

Keyword:

magnetic resonance imaging

variable flip angles

T-1 estimation

total variation

spatial regularization

dual approach

quadratic penalty