Analysis of dynamic magnetic resonance images.

Abstract

Dynamic magnetic resonance (MR) imaging with contrast agents is a very promising technique for studying tissue perfusion in vivo. A temporal series of magnetic resonance images of the same slice are acquired following the injection of a contrast agent into the blood stream. The image intensity depends on the local concentration of the contrast agent, so that tissue perfusion can be studied by the image series. A new method of analyzing such series is described here. Nonparametric linear regression is used for modeling the image intensity along the series on a pixel by pixel basis. After modeling, some relevant quantities describing the time series are obtained and displayed as images. Due to its flexibility, this approach is preferred to parametric modeling when pathology is present since this can induce a wide spread of patterns for the pixel image intensity along time. Results of the application of the method to series of dynamic magnetic resonance images from ischaemic rat brains after the injection of the susceptibility agent Sprodiamide Inj. (Dy-DTPA-BMA) are shown and compared to results from a related known method.