Purpose:To describe and demonstrate the feasibility of a novel multiecho reconstruction technique that achieves simultaneous water-fat decomposition and T2* estimation. The method removes interference of water-fat separation with iron-induced T2* effects and therefore has potential for the simultaneous characterization of hepatic steatosis (fatty infiltration) and iron overload. Materials and Methods:The algorithm called "T2*-IDEAL" is based on the IDEAL water-fat decomposition method. A novel "complex field map" construct is used to estimate both R2* (1/T2*) and local B 0 field inhomogeneities using an iterative least-squares estimation method. Water and fat are then decomposed from source images that are corrected for both T2* and B 0 field inhomogeneity. Results:It was found that a six-echo multiecho acquisition using the shortest possible echo times achieves an excellent balance of short scan and reliable R2* measurement. Phantom experiments demonstrate the feasibility with high accuracy in R2* measurement. Promising preliminary in vivo results are also shown. Conclusion:The T2*-IDEAL technique has potential applications in imaging of diffuse liver disease for evaluation of both hepatic steatosis and iron overload in a single breath-hold.

Purpose: To combine gradient-echo (GRE) imaging with a multipoint water-fat separation method known as "iterative decomposition of water and fat with echo asymmetry and least squares estimation" (IDEAL) for uniform waterfat separation. Robust fat suppression is necessary for many GRE imaging applications; unfortunately, uniform fat suppression is challenging in the presence of B 0 inhomogeneities. These challenges are addressed with the IDEAL technique. Materials and Methods:Echo shifts for three-point IDEAL were chosen to optimize noise performance of the water-fat estimation, which is dependent on the relative proportion of water and fat within a voxel. Phantom experiments were performed to validate theoretical SNR predictions. Theoretical echo combinations that maximize noise performance are discussed, and examples of clinical applications at 1.5T and 3.0T are shown. Results:The measured SNR performance validated theoretical predictions and demonstrated improved image quality compared to unoptimized echo combinations. Clinical examples of the liver, breast, heart, knee, and ankle are shown, including the combination of IDEAL with parallel imaging. Excellent water-fat separation was achieved in all cases. The utility of recombining water and fat images into "in-phase," "out-of-phase," and "fat signal fraction" images is also discussed. Conclusion:IDEAL-SPGR provides robust water-fat separation with optimized SNR performance at both 1.5T and 3.0T with multicoil acquisitions and parallel imaging in multiple regions of the body. GRADIENT-ECHO (GRE) imaging is a rapid MRI method that is used for a variety of applications throughout the body. T 1 -weighted (T 1 W) spoiled gradient-echo (SPGR) sequences are of particular importance for postcontrast imaging in many areas of the body, including the abdomen (1) and breast (2). Noncontrast-enhanced T 1 W SPGR imaging is also highly valuable for assessing cartilage morphology (3).Many T 1 W GRE imaging applications require suppression of fat signal. Fat is bright in these sequences and can potentially obscure underlying pathologies, such as tumor or inflammation. Unfortunately, reliable and uniform fat suppression can be challenging in areas of main field (B 0 ) and RF (B 1 ) inhomogeneities. Examples of challenging applications include imaging of the extremities and areas with unfavorable geometry (e.g., the brachial plexus), off-isocenter imaging, and large field of view (FOV) imaging. Other fat-suppression methods, such as short TI inversion recovery (STIR) (4), are incompatible with rapid GRE imaging because of the need for a long inversion time (approximately 200 msec). Spectral-spatial or water-selective pulses can be combined with GRE imaging, but they are lengthy. Although the fat-water discrimination achieved by these pulses is insensitive to B 1 inhomogeneities, they are still sensitive to B 0 inhomogeneities (5).In 1984 Dixon (6) first described "in-and out-ofphase" imaging, a method that acquires two images at different echo times (TEs), thereby exploiting th...

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The recently developed multi-acquisition with variable resonance image combination (MAVRIC) and slice-encoding metal artifact correction (SEMAC) techniques can significantly reduce image artifacts commonly encountered near embedded metal hardware. These artifact reductions are enabled by applying alternative spectral and spatial-encoding schemes to conventional spin-echo imaging techniques. Here, the MAVRIC and SEMAC concepts are connected and discussed. The development of a hybrid technique that utilizes strengths of both methods is then introduced. The presented technique is shown capable of producing minimal artifact, high-resolution images near total joint replacements in a clinical setting. Magn Reson Med 65:71-82, 2011.

The class of autocalibrating "data-driven" parallel imaging (PI) methods has gained attention in recent years due to its ability to achieve high quality reconstructions even under challenging imaging conditions. The aim of this work was to perform a formal comparative study of various data-driven reconstruction techniques to evaluate their relative merits for certain imaging applications. A total of five different reconstruction methods are presented within a consistent theoretical framework and experimentally compared in terms of the specific measures of reconstruction accuracy and efficiency using one-dimensional (1D)-accelerated Cartesian datasets. It is shown that by treating the reconstruction process as two discrete phases, a calibration phase and a synthesis phase, the reconstruction pathway can be tailored to exploit the computational advantages available in certain data domains. A new "split-domain" reconstruction method is presented that performs the calibration phase in k-space (k x , k y ) and the synthesis phase in a hybrid (x, k y ) space, enabling highly accurate 2D neighborhood reconstructions to be performed more efficiently than previously possible with conventional techniques. This analysis may help guide the selection of PI methods for a given imaging task to achieve high reconstruction accuracy at minimal computational expense. Magn Reson Med 59:382-395, 2008.