Improving temporal resolution of pulmonary perfusion imaging in rats using the partially separable functions model

Abstract

Dynamic contrast-enhanced MRI (or DCE-MRI) is a useful tool for measuring blood flow and perfusion, and it has found use in the study of pulmonary perfusion in animal models. However, DCE-MRI experiments are difficult in small animals such as rats. A recently developed method known as Interleaved Radial Imaging and Sliding window-keyhole (IRIS) addresses this problem by using a data acquisition scheme that covers (k,t)-space with data acquired from multiple bolus injections of a contrast agent. However, the temporal resolution of IRIS is limited by the effects of temporal averaging inherent in the sliding window and keyhole operations. This article describes a new method to cover (k,t)-space based on the theory of partially separable functions (PSF). Specifically, a sparse sampling of (k,t)-space is performed to acquire two data sets, one with high-temporal resolution and the other with extended k-space coverage. The high-temporal resolution training data are used to determine the temporal basis functions of the PSF model, whereas the other data set is used to determine the spatial variations of the model. The proposed method was validated by simulations and demonstrated by an experimental study. In this particular study, the proposed method achieved a temporal resolution of 32 msec.