Optimization of Tag Thickness for Measuring Position with Magnetic Resonance Imaging

Using magnetic resonance (MR) tagging, it is possible to track tissue motion by accurate detection of tag line positions. In this study, we show that with a least squares estimation algorithm, it is possible to define the position of the tag lines with a precision on the order of a tenth of a pixel. Here, we calculate the Cramer-Rao bound for the tag position estimation error as a function of the tag thickness, the shape of the tag profile and line spread function of the MR imaging system. The tag thickness that minimizes tag position estimation error is between 0.8 to 1.5 pixels depending on the shape of the tag and the line spread function. In addition, tag position estimation error is inversely proportional to contrast-to-noise ratio (CNR) between the tag and the background tissue. The theoretical results obtained in this study were verified by experiments performed on a whole-body 1.5T MR imager and Monte-Carlo simulation studies.