Rapid and Direct Quantification of Longitudinal Relaxation Time (T_1) in Look-Locker Sequences Using an Adaptive Neural Network

摘要

Fast and accurate measurement of the longitudinal relaxation time, T_1, has become increasingly important in quantitative estimates of such tissue physiological parameters as perfusion, capillary permeability, and tissue interstitial space using dynamic contrast-enhanced MRI (DCE-MRI). The Look-Locker (LL) sequence provides accurate T_1 estimates, with the advantages of reduced acquisition time, and a wide range of sampling times post-inversion. In this study, an Adaptive Neural Network (ANN) was trained and employed as an unbiased estimator of T_1 The ANN estimator was trained by simulating the LL signal at different levels of SNR. The results of its application to the simulated data were compared with T_1 maps estimated by conventional methods (Simplex method with non-negative least-squares fitting). Experimental results of the ANN method for 19 animals were also compared to the conventional method, and with values of T_1 reported in literature. The ANN and conventional methods produce estimates that are highly correlated in normal (r=0.957, p＜0.0001＝ and tumorous (r=0.965, p＜0.0001＝ tissues. It is concluded that the ANN method has very good potential to be used to produce a fast and accurate T_1 map in tissue, and thus to estimate from LL data in DCE studies the temporal change in tissue R_1 that occurs after administration of contrast agent, a measure that plays an important role in quantification of physiological parameters using MRI.