Multiecho water-fat separation and simultaneous Rmath image estimation with multifrequency fat spectrum modeling



Multiecho chemical shift–based water-fat separation methods are seeing increasing clinical use due to their ability to estimate and correct for field inhomogeneities. Previous chemical shift-based water-fat separation methods used a relatively simple signal model that assumes both water and fat have a single resonant frequency. However, it is well known that fat has several spectral peaks. This inaccuracy in the signal model results in two undesired effects. First, water and fat are incompletely separated. Second, methods designed to estimate Tmath image in the presence of fat incorrectly estimate the Tmath image decay in tissues containing fat. In this work, a more accurate multifrequency model of fat is included in the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) water-fat separation and simultaneous Tmath image estimation techniques. The fat spectrum can be assumed to be constant in all subjects and measured a priori using MR spectroscopy. Alternatively, the fat spectrum can be estimated directly from the data using novel spectrum self-calibration algorithms. The improvement in water-fat separation and Tmath image estimation is demonstrated in a variety of in vivo applications, including knee, ankle, spine, breast, and abdominal scans. Magn Reson Med 60:1122–1134, 2008. © 2008 Wiley-Liss, Inc.