Diego Hernando

Robust water/fat separation in the presence of large field inhomogeneities using a graph cut algorithm

Water/fat separation is a classical problem for in vivo proton MRI. Although many methods have been proposed to address this problem, robust water/fat separation remains a challenge, especially in the presence of large amplitude of static field inhomogeneities. This problem is challenging because of the nonuniqueness of the solution for an isolated voxel. This paper tackles the problem using a statistically motivated formulation that jointly estimates the complete field map and the entire water/fat images. This formulation results in a difficult optimization problem that is solved effectively using a novel graph cut algorithm, based on an iterative process where all voxels are updated simultaneously. The proposed method has good theoretical properties, as well as an efficient implementation. Simulations and in vivo results are shown to highlight the properties of the proposed method and compare it to previous approaches. Twenty‐five cardiac datasets acquired on a short, wide‐bore scanner with different slice orientations were used to test the proposed method, which produced robust water/fat separation for these challenging datasets. This paper also shows example applications of the proposed method, such as the characterization of intramyocardial fat. Magn Reson Med, 2010.

Joint Estimation of Water/Fat Images and Field Inhomogeneity Map

Water/fat separation in the presence of B0 field inhomogeneity is a problem of considerable practical importance in MRI. This article describes two complementary methods for estimating the water/fat images and the field inhomogeneity map from Dixon‐type acquisitions. One is based on variable projection (VARPRO) and the other on linear prediction (LP). The VARPRO method is very robust and can be used in low signal‐to‐noise ratio conditions because of its ability to achieve the maximum‐likelihood solution. The LP method is computationally more efficient, and is shown to perform well under moderate levels of noise and field inhomogeneity. These methods have been extended to handle multicoil acquisitions by jointly solving the estimation problem for all the coils. Both methods are analyzed and compared and results from several experiments are included to demonstrate their performance. Magn Reson Med 59:571–580, 2008.

Compressed-Sensing MRI With Random Encoding

Compressed sensing (CS) has the potential to reduce magnetic resonance (MR) data acquisition time. In order for CS-based imaging schemes to be effective, the signal of interest should be sparse or compressible in a known representation, and the measurement scheme should have good mathematical properties with respect to this representation. While MR images are often compressible, the second requirement is often only weakly satisfied with respect to commonly used Fourier encoding schemes. This paper investigates the use of random encoding for CS-MRI, in an effort to emulate the “universal” encoding schemes suggested by the theoretical CS literature. This random encoding is achieved experimentally with tailored spatially-selective radio-frequency (RF) pulses. Both simulation and experimental studies were conducted to investigate the imaging properties of this new scheme with respect to Fourier schemes. Results indicate that random encoding has the potential to outperform conventional encoding in certain scenarios. However, our study also indicates that random encoding fails to satisfy theoretical sufficient conditions for stable and accurate CS reconstruction in many scenarios of interest. Therefore, there is still no general theoretical performance guarantee for CS-MRI, with or without random encoding, and CS-based methods should be developed and validated carefully in the context of specific applications.

Rank-Constrained Solutions to Linear Matrix Equations Using PowerFactorization

Algorithms to construct/recover low-rank matrices satisfying a set of linear equality constraints have important applications in many signal processing contexts. Recently, theoretical guarantees for minimum-rank matrix recovery have been proven for nuclear norm minimization (NNM), which can be solved using standard convex optimization approaches. While nuclear norm minimization is effective, it can be computationally demanding. In this work, we explore the use of the powerfactorization (PF) algorithm as a tool for rank-constrained matrix recovery. Empirical results indicate that incremented-rank PF is significantly more successful than NNM at recovering low-rank matrices, in addition to being faster.

Chemical shift–based water/fat separation: A comparison of signal models

Quantitative water/fat separation in MRI requires careful modeling of the acquired signal. Multiple signal models have been proposed in recent years, but their relative performance has not yet been established. This article presents a comparative study of 12 signal models for quantitative water/fat separation. These models were selected according to three main criteria: magnitude or complex fitting, use of single‐peak or multipeak fat spectrum, and modeling of T  2* decay. The models were compared based on an analysis of the bias and standard deviation of their resulting estimates. Results from theoretical analysis, simulation, phantom experiments, and in vivo data were in good agreement. These results show that (a) complex fitting is uniformly superior to magnitude fitting, (b) multipeak fat modeling is able to remove the bias present in single‐peak fat modeling, and (c) a single‐T  2* model performs best over a range of clinically relevant signal‐to‐noise ratios (SNRs) and water/fat ratios. Magn Reson Med, 2010.

Multiecho dixon fat and water separation method for detecting fibrofatty infiltration in the myocardium

Conventional approaches for fat and water discrimination based on chemical‐shift fat suppression have reduced ability to characterize fatty infiltration due to poor contrast of microscopic fat. The multiecho Dixon approach to water and fat separation has advantages over chemical‐shift fat suppression: 1) water and fat images can be acquired in a single breathhold, avoiding misregistration; 2) fat has positive contrast; 3) the method is compatible with precontrast and late‐enhancement imaging, 4) less susceptible to partial‐volume effects, and 5) robust in the presence of background field variation; and 6) for the bandwidth implemented, chemical‐shift artifact is decreased. The proposed technique was applied successfully in all 28 patients studied. This included 10 studies with indication of coronary artery disease (CAD), of which four cases with chronic myocardial infarction (MI) exhibited fatty infiltration; 13 studies to rule out arrhythmogenic right ventricular cardiomyopathy (ARVC), of which there were three cases with fibrofatty infiltration and two confirmed with ARVC; and five cases of cardiac masses (two lipomas). The precontrast contrast‐to‐noise ratio (CNR) of intramyocardial fat was greatly improved, by 240% relative to conventional fat suppression. For the parameters implemented, the signal‐to‐noise ratio (SNR) was decreased by 30% relative to conventional late enhancement. The multiecho Dixon method for fat and water separation provides a sensitive means of detecting intramyocardial fat with positive signal contrast. Magn Reson Med 61:215–221, 2009.

Anatomically constrained reconstruction from noisy data

Noise is a major concern in many important imaging applications. To improve data signal‐to‐noise ratio (SNR), experiments often focus on collecting low‐frequency k‐space data. This article proposes a new scheme to enable extended k‐space sampling in these contexts. It is shown that the degradation in SNR associated with extended sampling can be effectively mitigated by using statistical modeling in concert with anatomical prior information. The method represents a significant departure from most existing anatomically constrained imaging methods, which rely on anatomical information to achieve super‐resolution. The method has the advantage that less accurate anatomical information is required relative to super‐resolution approaches. Theoretical and experimental results are provided to characterize the performance of the proposed scheme. Magn Reson Med 59:810–818, 2008.

Addressing Phase Errors in Fat-Water Imaging Using a Mixed Magnitude/Complex Fitting Method

Accurate, noninvasive measurements of liver fat content are needed for the early diagnosis and quantitative staging of nonalcoholic fatty liver disease. Chemical shift‐based fat quantification methods acquire images at multiple echo times using a multiecho spoiled gradient echo sequence, and provide fat fraction measurements through postprocessing. However, phase errors, such as those caused by eddy currents, can adversely affect fat quantification. These phase errors are typically most significant at the first echo of the echo train, and introduce bias in complex‐based fat quantification techniques. These errors can be overcome using a magnitude‐based technique (where the phase of all echoes is discarded), but at the cost of significantly degraded signal‐to‐noise ratio, particularly for certain choices of echo time combinations. In this work, we develop a reconstruction method that overcomes these phase errors without the signal‐to‐noise ratio penalty incurred by magnitude fitting. This method discards the phase of the first echo (which is often corrupted) while maintaining the phase of the remaining echoes (where phase is unaltered). We test the proposed method on 104 patient liver datasets (from 52 patients, each scanned twice), where the fat fraction measurements are compared to coregistered spectroscopy measurements. We demonstrate that mixed fitting is able to provide accurate fat fraction measurements with high signal‐to‐noise ratio and low bias over a wide choice of echo combinations. Magn Reson Med, 2012.

ISMRM workshop on fat–water separation: Insights, applications and progress in MRI

Approximately 130 attendees convened on February 19–22, 2012 for the first ISMRM‐sponsored workshop on water–fat imaging. The motivation to host this meeting was driven by the increasing number of research publications on this topic over the past decade. The scientific program included an historical perspective and a discussion of the clinical relevance of water–fat MRI, a technical description of multiecho pulse sequences, a review of data acquisition and reconstruction algorithms, a summary of the confounding factors that influence quantitative fat measurements and the importance of MRI‐based biomarkers, a description of applications in the heart, liver, pancreas, abdomen, spine, pelvis, and muscles, an overview of the implications of fat in diabetes and obesity, a discussion on MR spectroscopy, a review of childhood obesity, the efficacy of lifestyle interventional studies, and the role of brown adipose tissue, and an outlook on federal funding opportunities from the National Institutes of Health. Magn Reson Med, 2012.

Quantification of liver iron with MRI: state of the art and remaining challenges.

Liver iron overload is the histological hallmark of hereditary hemochromatosis and transfusional hemosiderosis, and can also occur in chronic hepatopathies. Iron overload can result in liver damage, with the eventual development of cirrhosis, liver failure, and hepatocellular carcinoma. Assessment of liver iron levels is necessary for detection and quantitative staging of iron overload and monitoring of iron‐reducing treatments. This article discusses the need for noninvasive assessment of liver iron and reviews qualitative and quantitative methods with a particular emphasis on magnetic resonance imaging (MRI). Specific MRI methods for liver iron quantification include signal intensity ratio as well as R2 and R2* relaxometry techniques. Methods that are in clinical use, as well as their limitations, are described. Remaining challenges, unsolved problems, and emerging techniques to provide improved characterization of liver iron deposition are discussed. J. Magn. Reson. Imaging 2014;40:1003–1021.