Rapid water and lipid imaging with T2 mapping using a radial IDEAL‐GRASE technique

Reliable and fast separation of tissue water and lipid components is desired in many clinical applications to improve the diagnosis of disease. Conventional chemical-shift saturation techniques for suppressing the water or lipid component are problematic due to the presence of static field inhomogeneities (1-4). Chemical shift imaging based on phase sensitive methods has been widely investigated to overcome the problems in lipid-water imaging caused by field inhomogeneities. There have been many approaches, including the two-point method acquiring “in-phase” and “opposed-phase” images originally proposed by Dixon (5) and a refinement with possible phase correction due to field inhomogeneities (6,7). The two-point Dixon method was followed by the three-point Dixon approach with symmetric sampling (e.g., the acquisition of images with phase shifts between lipid and water of −π,0,π; 0,π,2π; or the more general scheme −α,0,α). The three points were used to resolve lipid and water and a field map (8-11). These methods relied on a phase unwrapping algorithm to estimate the field map which in many cases complicated the separation of lipid and water. As an alternative, Xiang et al introduced the use of asymmetric sampling with direct phase encoding to directly separate lipid and water without the need for an initial estimation of the field map (12,13). Another advantage of asymmetric sampling is that the redundancy of symmetrically sampled data is removed yielding a more efficient utilization of the data (13). Recently an iterative algorithm for the decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL) was developed (14,15). IDEAL is also based on the asymmetric acquisition and requires at least three images to resolve the lipid and water images and the field map. In IDEAL the field map is calculated in an iterative fashion and does not require a specific algorithm to unwrap the phase. IDEAL has been implemented with FSE, gradient-echo (GRE), and steady-state free precession (SSFP) sequences (14-16) and is reported to yield robust lipid-water imaging for various clinical applications. In these applications the collection of the three phase-shifted echoes is done in separate TR periods. In FSE applications this results in long scan times, which is not adequate for imaging anatomic locations where fast imaging is required. In order to reduce scan time for lipid-water imaging in FSE acquisitions we developed the IDEAL Gradient and Spin Echo method (IDEAL-GRASE) (17) where multiple gradient echoes are collected within each spin-echo period so that the data with different phase-shifts for lipid-water imaging are obtained within the same TR period. The IDEAL-GRASE method was developed for conventional Cartesian data acquisition. The Cartesian IDEAL-GRASE technique was shown to produce comparable separation of lipid and water to IDEAL-FSE in 1/3 of the imaging time. Another method based on the collection of multiple echoes within a spin-echo (SE) period was also recently developed for fast lipid-water imaging by Ma et al (18). The acquisition of data using a radial k-space trajectory offers robustness to motion and flow (19-22). We have shown that radial MRI is a good alternative to Cartesian MRI for T2-weighted imaging where the image quality of the conventional Cartesian-based methods is deteriorated by motion and flow artifacts (22). Moreover, due to the oversampling in the center of k-space a single radial FSE or GRASE k-space data set can be processed to generate high resolution T2 maps (23-26). The T2 information obtained from radial FSE data successfully discriminated benign from malignant liver lesions (22,26). In this work, we describe a radial GRASE technique combined with the IDEAL algorithm (radial IDEAL-GRASE) to achieve time-efficient lipid-water decomposition as well as T2 mapping. The radial IDEAL-GRASE technique is demonstrated in phantoms and in vivo for applications including pelvic, cardiac, and abdominal imaging.