Charles A. McKenzie

Multiecho water-fat separation and simultaneous R2* 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 T  2* in the presence of fat incorrectly estimate the T  2* 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 T  2* 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 T  2* 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.

Fat quantification with IDEAL gradient echo imaging: correction of bias from T(1) and noise.

Quantification of hepatic steatosis is a significant unmet need for the diagnosis and treatment of patients with nonalcoholic fatty liver disease (NAFLD). MRI is capable of separating water and fat signals in order to quantify fatty infiltration of the liver (hepatic steatosis). Unfortunately, fat signal has confounding T1 effects and the nonzero mean noise in low signal‐to‐noise ratio (SNR) magnitude images can lead to incorrect estimation of the true lipid percentage. In this study, the effects of bias from T1 effects and image noise were investigated. An oil/water phantom with volume fat‐fractions ranging linearly from 0% to 100% was designed and validated using a spoiled gradient echo (SPGR) sequence in combination with a chemical‐shift based fat‐water separation method known as iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL). We demonstrated two approaches to reduce the effects of T1: small flip angle (flip angle) and dual flip angle methods. Both methods were shown to effectively minimize deviation of the measured fat‐fraction from its true value. We also demonstrated two methods to reduce noise bias: magnitude discrimination and phase‐constrained reconstruction. Both methods were shown to reduce this noise bias effectively from 15% to less than 1%. Magn Reson Med 58:354–364, 2007.

Multiecho reconstruction for simultaneous water‐fat decomposition and T2* estimation

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.

Water–fat separation with IDEAL gradient‐echo imaging

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 water–fat separation. Robust fat suppression is necessary for many GRE imaging applications; unfortunately, uniform fat suppression is challenging in the presence of B0 inhomogeneities. These challenges are addressed with the IDEAL technique.

Quantification of Hepatic Steatosis with T1-independent, T2*-corrected MR Imaging with Spectral Modeling of Fat: Blinded Comparison with MR Spectroscopy

PURPOSE To prospectively compare an investigational version of a complex-based chemical shift-based fat fraction magnetic resonance (MR) imaging method with MR spectroscopy for the quantification of hepatic steatosis. MATERIALS AND METHODS This study was approved by the institutional review board and was HIPAA compliant. Written informed consent was obtained before all studies. Fifty-five patients (31 women, 24 men; age range, 24-71 years) were prospectively imaged at 1.5 T with quantitative MR imaging and single-voxel MR spectroscopy, each within a single breath hold. The effects of T2 correction, spectral modeling of fat, and magnitude fitting for eddy current correction on fat quantification with MR imaging were investigated by reconstructing fat fraction images from the same source data with different combinations of error correction. Single-voxel T2-corrected MR spectroscopy was used to measure fat fraction and served as the reference standard. All MR spectroscopy data were postprocessed at a separate institution by an MR physicist who was blinded to MR imaging results. Fat fractions measured with MR imaging and MR spectroscopy were compared statistically to determine the correlation (r(2)), and the slope and intercept as measures of agreement between MR imaging and MR spectroscopy fat fraction measurements, to determine whether MR imaging can help quantify fat, and examine the importance of T2 correction, spectral modeling of fat, and eddy current correction. Two-sided t tests (significance level, P = .05) were used to determine whether estimated slopes and intercepts were significantly different from 1.0 and 0.0, respectively. Sensitivity and specificity for the classification of clinically significant steatosis were evaluated. RESULTS Overall, there was excellent correlation between MR imaging and MR spectroscopy for all reconstruction combinations. However, agreement was only achieved when T2 correction, spectral modeling of fat, and magnitude fitting for eddy current correction were used (r(2) = 0.99; slope ± standard deviation = 1.00 ± 0.01, P = .77; intercept ± standard deviation = 0.2% ± 0.1, P = .19). CONCLUSION T1-independent chemical shift-based water-fat separation MR imaging methods can accurately quantify fat over the entire liver, by using MR spectroscopy as the reference standard, when T2 correction, spectral modeling of fat, and eddy current correction methods are used.

A generalized approach to parallel magnetic resonance imaging

Parallel magnetic resonance (MR) imaging uses spatial encoding from multiple radiofrequency detector coils to supplement the encoding supplied by magnetic field gradients, and thereby to accelerate MR image acquisitions beyond previous limits. A generalized formulation for parallel MR imaging is derived, demonstrating the relationship between existing techniques such as SMASH and SENSE, and suggesting new algorithms with improved performance. Hybrid approaches combining features of both SMASH-like and SENSE-like image reconstructions are constructed, and numerical conditioning techniques are described which can improve the practical robustness of parallel image reconstructions. Incorporation of numerical conditioning directly into parallel reconstructions using the generalized approach also removes a cumbersome and potentially error-prone sensitivity calibration step involving division of two distinct in vivo reference images. Hybrid approaches in combination with numerical conditioning are shown to extend the range of accelerations over which high-quality parallel images may be obtained.

Comprehensive quantification of signal‐to‐noise ratio and g‐factor for image‐based and k‐space‐based parallel imaging reconstructions

Parallel imaging reconstructions result in spatially varying noise amplification characterized by the g‐factor, precluding conventional measurements of noise from the final image. A simple Monte Carlo based method is proposed for all linear image reconstruction algorithms, which allows measurement of signal‐to‐noise ratio and g‐factor and is demonstrated for SENSE and GRAPPA reconstructions for accelerated acquisitions that have not previously been amenable to such assessment. Only a simple “prescan” measurement of noise amplitude and correlation in the phased‐array receiver, and a single accelerated image acquisition are required, allowing robust assessment of signal‐to‐noise ratio and g‐factor. The “pseudo multiple replica” method has been rigorously validated in phantoms and in vivo, showing excellent agreement with true multiple replica and analytical methods. This method is universally applicable to the parallel imaging reconstruction techniques used in clinical applications and will allow pixel‐by‐pixel image noise measurements for all parallel imaging strategies, allowing quantitative comparison between arbitrary k‐space trajectories, image reconstruction, or noise conditioning techniques. Magn Reson Med 60:895–907, 2008.

Quantification of hepatic steatosis with MRI: the effects of accurate fat spectral modeling.

To develop a chemical‐shift–based imaging method for fat quantification that accounts for the complex spectrum of fat, and to compare this method with MR spectroscopy (MRS). Quantitative noninvasive biomarkers of hepatic steatosis are urgently needed for the diagnosis and management of nonalcoholic fatty liver disease (NAFLD).

Self-calibrating parallel imaging with automatic coil sensitivity extraction.

Calibration of the spatial sensitivity functions of coil arrays is a crucial element in parallel magnetic resonance imaging (PMRI). The most common approach has been to measure coil sensitivities directly using one or more low‐resolution images acquired before or after accelerated data acquisition. However, since it is difficult to ensure that the patient and coil array will be in exactly the same positions during both calibration scans and accelerated imaging, this approach can introduce sensitivity miscalibration errors into PMRI reconstructions. This work shows that it is possible to extract sensitivity calibration images directly from a fully sampled central region of a variable‐density k‐space acquisition. These images have all the features of traditional PMRI sensitivity calibrations and therefore may be used for any PMRI reconstruction technique without modification. Because these calibration data are acquired simultaneously with the data to be reconstructed, errors due to sensitivity miscalibration are eliminated. In vivo implementations of self‐calibrating parallel imaging using a flexible coil array are demonstrated in abdominal imaging and in real‐time cardiac imaging studies. Magn Reson Med 47:529–538, 2002.

T1 independent, T2* corrected chemical shift based fat–water separation with multi‐peak fat spectral modeling is an accurate and precise measure of hepatic steatosis

To determine the precision and accuracy of hepatic fat‐fraction measured with a chemical shift‐based MRI fat‐water separation method, using single‐voxel MR spectroscopy (MRS) as a reference standard.