Quantitative evaluation of simultaneous spatial and temporal regularization in dynamic contrast-enhanced MRI of the liver using Gd-EOB-DTPA

Abstract

The purpose of this study was to quantitatively evaluate the usefulness of simultaneous spatial and temporal regularization using total variation (TV), total generalized variation (TGV), a combination of low-rank decomposition (LRD) and TV (LRD+TV), a combination of LRD and TGV (LRD+TGV), and nuclear norm (NN) when applied to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in rats with concanavalin A (ConA)-induced acute hepatic injury.The rats were divided into three groups: normal control (NC) (n = 10), ConA10 (n = 8), and ConA20 (n = 7). Rats in the ConA10 and ConA20 groups were intravenously injected with 10 and 20 mg/kg of ConA, respectively; those in the NC group were intravenously injected with the same volume of saline. DCE-MRI studies were performed using gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA; 0.025 mmol Gd/kg) as a contrast agent (CA), 24 h after the ConA or saline injection. After the DCE-MRI study, we generated zero-filled and undersampled k-space data from the original images using a pseudoradial sampling scheme with 4 to 64 spokes. We subsequently reconstructed images from these data using the above regularizers and calculated the signal-to-error ratio (SERimg) and structural similarity index measure (SSIM) using the original and reconstructed images. We also calculated the area under the curve (AUC), rate of CA washout (λw), maximum relative enhancement (REmax), and time to REmax (Tmax) from time-intensity curves using an empirical mathematical model (EMM) and the signal-to-error ratio for curve fitting (SERfit) from the original and fit curves. We also compared the parameters obtained using the pseudoradial and Cartesian sampling schemes in the NC group.When using LRD+TV and LRD+TGV, both SERimg and SSIM were greater than those for the other regularizers at all spoke numbers studied; the SERfit for TGV was the greatest. When using TGV and LRD+TGV, in the majority of cases the AUCs did not significantly differ from those obtained from the original images, whereas those for LRD+TV and NN were significantly less at several spoke numbers. The λw for NN was significantly greater at numerous spoke numbers in the NC group; the REmax values for LRD+TV and NN were significantly less at several spoke numbers in all groups. The Tmax values for TV, TGV, and LRD+TGV were significantly greater at numerous spoke numbers in the NC group. Although there were significant differences in SERimg and SSIM between the pseudoradial and Cartesian sampling schemes, the kinetic parameters obtained by the EMM did not significantly differ between the two sampling schemes, with certain exceptions.In conclusion, our results suggest that simultaneous spatial and temporal regularization using TGV or LRD+TGV is useful for accelerating DCE-MRI without significant reduction in the accuracy of the kinetic parameter estimation, even at extremely low sampling factors.