Constrained Reconstruction of Dynamic Contrast Enhanced Tumor MR Data with Respiratory Self-Gating

Ganesh Adluru¹, Wei Lin¹, Mark Rosen¹, Hee Kwon Song¹

Compressed sensing/constrained reconstruction methods have recently been proposed and applied to accelerate MR acquisitions. Here we apply the spatio-temporal constrained reconstruction method in conjunction with the recently proposed respiratory self-gated DCE-MRI strategy to improve the reconstructions of radially undersampled DCE tumor data. Respiratory gating effectively reduces the temporal signal variations due to breathing and leads to enhanced sparsity in the temporal gradient. Improved image quality is clearly demonstrated in undersampled lung and liver tumor DCE-MRI datasets. The approach offers a promising framework to accelerate DCE-MRI of lesions located in regions severely affected by respiratory motion.