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IMAGING METHODOLOGY - Workshop Summary ISMRM Workshop on Fat–Water Separation: Insights, Applications and Progress in MRI Houchun Harry Hu, 1 * Peter Bornert, 2 Diego Hernando, 3 Peter Kellman, 4 Jingfei Ma, 5 Scott Reeder, 3 and Claude Sirlin 6 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 his- torical 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 influ- ence 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 obe- sity, 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 68:378–388, 2012. V C 2012 Wiley Periodicals, Inc. Key words: water–fat imaging; fat–water separation; Dixon; chemical-shift; fat quantification Research in water–fat MRI has increased significantly in recent years with the development of robust qualitative and quantitative MRI techniques that utilize chemical- shift principles to separate, identify, and measure water and fat signals. The motivation has been catalyzed partly by the rising prevalence of obesity and type 2 diabetes (T2D) and the need to study body and organ fat deposi- tion in relation to comorbidities. This was the first ISMRM workshop on water–fat MRI and was held at the Hotel Maya in Long Beach, California, from February 19 to 22, 2012. The meeting brought to- gether the international community to exchange insights, progress, and applications steadily gained over the past years and to stimulate dialog in identifying future research directions. Participants traveled from Canada, France, Germany, Italy, the Netherlands, Norway, Swe- den, Switzerland, United Kingdom, China, Japan, South Korea, and the United States. The program involved 25 lectures that provided summaries and focused themes and described innovative advances and applications. A poster session facilitated in-depth discussions and inter- actions among attendees. More than 60 abstracts were submitted: 52.4% focused on data reconstruction and pulse sequences; 15.9% on skeletal muscle fat; 14.3% on abdominal adiposity, whole-body composition, and image segmentation; and 17.4% on fat in organs. The program broadly attracted trainees, engineers, and investigators from academia, government, and industry. On the first day, the program focused on pulse sequences and performance limits, mathematical theory, data acquisition and reconstruction algorithms, consid- erations in signal-to-noise ratio, confounders that influ- ence quantitative fat measurements as a biomarker, and validation techniques. On the second day, the theme transitioned to diagnostic applications in the heart, liver, pancreas, abdomen, spine, pelvis, and muscles. This was followed by an overview of diabetes and obe- sity, a session on MR spectroscopy (MRS), and an out- look on future research opportunities. On the third day, the discussion focused on childhood obesity, lifestyle interventions, and brown adipose tissue (BAT). This ar- ticle summarizes the scientific highlights, and the future needs and trends identified from presentations of the 25 invited speakers. HISTORICAL AND CLINICAL PERSPECTIVES It was an honor to have W. Thomas Dixon (GE Global Research) as the opening keynote speaker and set the tone for this workshop. He described how the idea of ‘‘simple spectroscopic imaging’’ came to him on a dark stormy afternoon in 1983. He entertained the audience with the peer-review process of his now seminal Radiol- ogy paper (1), noting the 94 days between initial submis- sion and the revision request, and the additional 44 days between revision submission and acceptance. There were two hurdles: the lack of nomenclature at the time distinguishing radiofrequency-recalled and gradient- recalled echoes, and the general editorial disbelief of his proposed method. Nonetheless, Dr. Dixon recognized two other groups that independently arrived at similar observations (2,3). 1 Departments of Radiology and Electrical Engineering, Children’s Hospital Los Angeles, University of Southern California, Los Angeles, California, USA. 2 Philips Research Laboratories, Hamburg, Germany. 3 Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA. 4 Laboratory of Cardiac Energetics, National Institutes of Health, National Heart, Lung and Blood Institute, Bethesda, Maryland, USA. 5 Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas, USA. 6 Liver Imaging Group, Department of Radiology, University of California, San Diego, California, USA. Grant sponsors: GE Healthcare, Philips Healthcare, Toshiba America Medical Systems. *Correspondence to: Houchun Harry Hu, Ph.D., Children’s Hospital Los Angeles, Radiology, Mail Stop #81, 4650 Sunset Boulevard, Los Angeles, CA 90027. E-mail: [email protected] or [email protected] Received 3 April 2012; revised 14 May 2012; accepted 16 May 2012. DOI 10.1002/mrm.24369 Published online 12 June 2012 in Wiley Online Library (wileyonlinelibrary. com). Magnetic Resonance in Medicine 68:378–388 (2012) V C 2012 Wiley Periodicals, Inc. 378
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Page 1: ISMRM workshop on fat-water separation: Insights, applications and progress in MRI

IMAGINGMETHODOLOGY -

Workshop Summary

ISMRM Workshop on Fat–Water Separation: Insights,Applications and Progress in MRI

Houchun Harry Hu,1* Peter B€ornert,2 Diego Hernando,3 Peter Kellman,4 Jingfei Ma,5

Scott Reeder,3 and Claude Sirlin6

Approximately 130 attendees convened on February 19–22,2012 for the first ISMRM-sponsored workshop on water–fatimaging. The motivation to host this meeting was driven bythe increasing number of research publications on this topicover the past decade. The scientific program included an his-torical perspective and a discussion of the clinical relevanceof water–fat MRI, a technical description of multiecho pulsesequences, a review of data acquisition and reconstructionalgorithms, a summary of the confounding factors that influ-ence quantitative fat measurements and the importance ofMRI-based biomarkers, a description of applications in theheart, liver, pancreas, abdomen, spine, pelvis, and muscles, anoverview of the implications of fat in diabetes and obesity, adiscussion on MR spectroscopy, a review of childhood obe-sity, the efficacy of lifestyle interventional studies, and the roleof brown adipose tissue, and an outlook on federal fundingopportunities from the National Institutes of Health. MagnReson Med 68:378–388, 2012. VC 2012 Wiley Periodicals, Inc.

Key words: water–fat imaging; fat–water separation; Dixon;chemical-shift; fat quantification

Research in water–fat MRI has increased significantly inrecent years with the development of robust qualitativeand quantitative MRI techniques that utilize chemical-shift principles to separate, identify, and measure waterand fat signals. The motivation has been catalyzed partlyby the rising prevalence of obesity and type 2 diabetes(T2D) and the need to study body and organ fat deposi-tion in relation to comorbidities.

This was the first ISMRM workshop on water–fat MRIand was held at the Hotel Maya in Long Beach, California,from February 19 to 22, 2012. The meeting brought to-gether the international community to exchange insights,progress, and applications steadily gained over the past

years and to stimulate dialog in identifying futureresearch directions. Participants traveled from Canada,France, Germany, Italy, the Netherlands, Norway, Swe-den, Switzerland, United Kingdom, China, Japan, SouthKorea, and the United States. The program involved 25lectures that provided summaries and focused themesand described innovative advances and applications. Aposter session facilitated in-depth discussions and inter-actions among attendees. More than 60 abstracts weresubmitted: 52.4% focused on data reconstruction andpulse sequences; 15.9% on skeletal muscle fat; 14.3% onabdominal adiposity, whole-body composition, and imagesegmentation; and 17.4% on fat in organs.

The program broadly attracted trainees, engineers,and investigators from academia, government, andindustry. On the first day, the program focused on pulsesequences and performance limits, mathematical theory,data acquisition and reconstruction algorithms, consid-erations in signal-to-noise ratio, confounders that influ-ence quantitative fat measurements as a biomarker, andvalidation techniques. On the second day, the themetransitioned to diagnostic applications in the heart,liver, pancreas, abdomen, spine, pelvis, and muscles.This was followed by an overview of diabetes and obe-sity, a session on MR spectroscopy (MRS), and an out-look on future research opportunities. On the third day,the discussion focused on childhood obesity, lifestyleinterventions, and brown adipose tissue (BAT). This ar-ticle summarizes the scientific highlights, and thefuture needs and trends identified from presentations ofthe 25 invited speakers.

HISTORICAL AND CLINICAL PERSPECTIVES

It was an honor to have W. Thomas Dixon (GE GlobalResearch) as the opening keynote speaker and set thetone for this workshop. He described how the idea of‘‘simple spectroscopic imaging’’ came to him on a darkstormy afternoon in 1983. He entertained the audiencewith the peer-review process of his now seminal Radiol-ogy paper (1), noting the 94 days between initial submis-sion and the revision request, and the additional 44 daysbetween revision submission and acceptance. Therewere two hurdles: the lack of nomenclature at the timedistinguishing radiofrequency-recalled and gradient-recalled echoes, and the general editorial disbelief of hisproposed method. Nonetheless, Dr. Dixon recognizedtwo other groups that independently arrived at similarobservations (2,3).

1Departments of Radiology and Electrical Engineering, Children’s HospitalLos Angeles, University of Southern California, Los Angeles, California, USA.2Philips Research Laboratories, Hamburg, Germany.3Department of Radiology, University of Wisconsin-Madison, Madison,Wisconsin, USA.4Laboratory of Cardiac Energetics, National Institutes of Health, NationalHeart, Lung and Blood Institute, Bethesda, Maryland, USA.5Department of Imaging Physics, University of Texas MD Anderson CancerCenter, Houston, Texas, USA.6Liver Imaging Group, Department of Radiology, University of California, SanDiego, California, USA.

Grant sponsors: GE Healthcare, Philips Healthcare, Toshiba AmericaMedical Systems.

*Correspondence to: Houchun Harry Hu, Ph.D., Children’s Hospital LosAngeles, Radiology, Mail Stop #81, 4650 Sunset Boulevard, Los Angeles,CA 90027. E-mail: [email protected] or [email protected]

Received 3 April 2012; revised 14 May 2012; accepted 16 May 2012.

DOI 10.1002/mrm.24369Published online 12 June 2012 in Wiley Online Library (wileyonlinelibrary.com).

Magnetic Resonance in Medicine 68:378–388 (2012)

VC 2012 Wiley Periodicals, Inc. 378

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Gary Glover (Stanford University) gave a tour on thehistorical developments in water–fat MRI. He began withT1-based Short-Tau Inversion Recovery methods and fre-quency-selective excitation/saturation techniques andprogressed to two- and three-echo symmetric and asym-metric sampling approaches to mitigate B0 inhomogeneityand address phase unwrapping with strategic echo timechoices and innovative postprocessing algorithms (4–9).He summarized early efforts to account for signal attenua-tion, spectral broadening, and the multipeak spectrum offat (10), to estimate the effective signal-to-noise ratio andnumber of signal averages (NSAs), and to reduce scantime with interleaved and multiecho acquisitions (11,12).Dr. Glover concluded with a review of N-point schemes.It was informative to see the logical progression in meth-odological advances over the past 30 years.

Shahid Hussain (University of Nebraska Medical Cen-ter) demonstrated the importance of traditional inversion-recovery (Short-Tau Inversion Recovery) and frequency-selective fat suppression (FATSAT, SPECIAL, SPIR, andCHESS) techniques, focusing on liver applications inadults. He discussed the clinical utility of fat suppressionand its function in improving lesion conspicuity on T1-and T2-weighted images, expanding the tissue contrastdynamic range, reducing ghost artifacts arising from sub-cutaneous fat and respiratory motion, and minimizingchemical-shift in diffusion-weighting echo-planar imag-ing sequences (13). To emphasize the role of fat suppres-sion/detection in abdominal MRI, Dr. Hussain illustratedexamples of fat containing lesions that can be diagnosedbased on their unique appearances, including hepatocel-lular adenomas versus fat-containing hepatocellular carci-nomas, hepatic lipomas versus hemangiomas, neuroendo-crine metastases versus multifocal fat-containinghepatocellular carcinomas, clear-cell type renal cell carci-nomas versus angiomyolipoma, and normal pancreas ver-sus acute focal pancreatitis (14). These classical MRI tech-niques continue to play a central role in daily clinicalworkflow, despite their sensitivity to B0 and B1 inhomo-geneities and the continuing advances of water–fat MRI.

Jeffrey Schwimmer (University of California, SanDiego, and Rady Children’s Hospital) gave a thought-pro-voking presentation on pediatric fat imaging. He high-lighted the prevalence of childhood obesity and its expo-nential growth from approximately 2 to 12 million casesbetween 1980 and 2010. Obese adolescents have a highermortality rate by the age of 50 in comparison to thosewith normal weight, with liver and heart diseases, infec-tions, cancer, and diabetes as the predominant causes ofdeath. He focused on visceral adipose tissue (VAT) andemphasized that it is not only the amount of VAT butalso the distribution and the lipid particle size withinthe adipocytes that influence metabolic disease risk. Heparticularly noted the association between VAT andsleep apnea (15). He summarized the lack of guidelinesfor the utilization of MRI to measure fat in pediatricsand offered one putative explanation. There is a widerange of fat values in the literature, with dependencieson gender (16), age, and ethnicity. The spectrum is fur-ther widened by the use of different MR techniques,including single-slice and multislice imaging, and spec-troscopy. Consequently, it is difficult to ascertain in a

systematic manner appropriate stratification values forroutine clinical diagnosis. He discussed the prevalenceof fatty liver in children (17) and argued that while MRIis useful in determining hepatic steatosis, it does not yetprovide a myriad of other useful disease-related informa-tion that is available from biopsy. Lastly, Dr. Schwimmerdescribed the motivation to standardize quantitative MRIfat measurements. He challenged the community to de-velop a framework such that an accurate diagnosis ofdisease, an understanding of disease severity and pro-gression over time, a meaningful measure of interventionand therapeutic efficacy, and a reliable predictor of clini-cal outcomes can be determined from nominal numbers.

TECHNIQUE AND RECONSTRUCTIONCONSIDERATIONS

Qing-San Xiang (University of British Columbia) compre-hensively described one-, two-, and three-echo water–fatMRI methods, utilizing a framework of two rotating vec-tors to demonstrate each technique and how factors suchas time-dependent phase errors from B0 inhomogeneityand time-independent ones from receiver coils affectedthe signal model. With one-echo strategies, he showedthat by judiciously selecting the echo time (TE) such thatwater and fat vectors are orthogonal, one can separatewater and fat into the real- and imaginary-axis of the re-sultant signal, provided phase errors are removed by cali-bration or postprocessing (18–21). Next, he discussedtwo-echo methods with symmetric sampling that yield in-and opposed-phase data, and subsequent determinationof the major ‘‘big’’ and minor ‘‘small’’ components, effec-tively separating water and fat in each voxel. However,identification of water and fat can be ambiguous (e.g.,water–fat swaps) due to B0 inhomogeneity. He then dem-onstrated how asymmetric ‘‘partially-opposed-phase’’ (22)sampling can overcome this ambiguity to achieve consist-ent water–fat separation and identification (23,24). Heconcluded with three-echo methods, summarizing sym-metric and asymmetric strategies (25) and early efforts inT2* mapping (26), multispectral-peak ethanol imaging, andmulticomponent (water/fat/silicone) applications (27). Dr.Xiang concluded that asymmetrical sampling and properhandling of phase are critical to robust water–fat MRI.

Holger Eggers (Philips Research) discussed the benefitsof water–fat MRI using three or more echoes. He empha-sized that two-point methods are adequate for separatingwater and fat signals and are sufficient for qualitativeuse. Expanding on the classical signal model wherewater, fat, and B0 inhomogeneity are unknowns, Dr.Eggers demonstrated that using three or more echoesallows improved accuracy in water–fat separation andprovides additional clinically relevant information. Forexample, the measurement of more echoes can facilitateincreasing tolerance to eddy currents (23,28), improvingB0 inhomogeneity estimation, reducing water–fat swaps,enhancing signal-to-noise ratio, estimating T2* of waterand fat components (29), and characterizing triglycerideproperties such as degree of saturation (30–32). Samplingmore echoes does not necessarily come at the expense ofincreased scan times. Rather, it allows more flexible TEand echo spacing choices. He noted that multiecho

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water–fat imaging is a subset of chemical-shift imaging,where resonances and relative amplitudes of spectralmodels of components to be separated are assumed a pri-ori in the former but unconstrained in the latter.

Walter Block (University of Wisconsin-Madison) sum-marized flavors of water–fat MRI pulse sequences and B0

fieldmap estimation techniques. He reviewed gradientecho (33), spin echo (34), and hybrid designs (35). He high-lighted developments in magnetization transfer water–fatimaging and where the absence of magnetization transfereffects in fat is exploited (36). Dr. Block focused on bal-anced steady state free precession (SSFP) variants, demon-strating fat-suppression (37), water-excitation (38), phasesensitive approaches (39), integration with chemical-shiftwater–fat schemes (40,41), fluctuating equilibrium mag-netic resonance (42), linear combination approaches (43),and alternating pulse repetition time methods (44,45) thatshape the spectral frequency response to place the stopband over a majority of fat resonances (46). He discussedB0 fieldmap estimation, a critical component in water–fatMRI. Several methods to address a fundamental challengein avoiding incorrect global minima fieldmap solutionsthat lead to swaps have been reviewed (47). In overcomingthis ambiguity, field map smoothness assumptions havebeen exploited in region growing (48) and multiresolutionapproaches (49–52), direct algebraic formulations (53),and regularization schemes (54,55).

Peter B€ornert (Philips Research) emphasized the needto accelerate water–fat MRI, because the chemical-shiftencoding process needs extra time, requiring usually theacquisition of multiple data at different TEs. A compre-hensive overview of techniques to accelerate multiechowater–fat MRI was provided, summarizing advantagesand drawbacks spanning partial-Fourier approaches (56),integration with parallel imaging (57), interleaved fly-back and nonfly-back schemes (58,59), and advancedmethods such as k-space-based water–fat decomposition(60), compressed sensing (61,62), and compressed sens-ing with parallel imaging (63,64). Furthermore, Dr.B€ornert highlighted that non-Cartesian methods (60,65–68) are also compatible with water–fat MRI and haveinteresting inherent benefits, including robustness tophysiological and patient motion and the ability to ac-quire ultrashort and very long effective TEs (e.g., radial,spiral, and propeller sampling). Some water–fatapproaches, especially the non-Cartesian variants, arestill in the research phase, but the current combinationof parallel imaging with efficient sampling has alreadyfacilitated rapid acquisition for several interesting appli-cations in research and clinical practice. Additionalwork needs to be investigated in data reconstruction, notonly to handle large amounts of data from multicoil,multiecho acquisitions, but also for advanced and itera-tive methods that require additional processing steps tocompensate for chemical-shift effects during signal sam-pling and potential off-resonance blurring.

QUANTITATIVE WATER–FAT MRI

Claude Sirlin (University of California, San Diego) gave aprelude to quantitative water–fat MRI, emphasizing fat asan objective image-based indicator of biological, patho-

logical, or pathogenic process and a surrogate for a clini-cal endpoint—an imaging biomarker. He illustrated theconcepts of accuracy and precision (69,70). Accuracy isthe correctness of a biomarker measurement in compari-son to a reference standard and can be assessed with re-ceiver operating curves and true/false positives/negativesif the metric is dichotomous or with correlation andregression if the measure is continuous or ordinal. Preci-sion is the consistency (and variability) of the biomarker.No reference is needed in assessing precision. Precisionis affected by technical components including repeatabil-ity (within a site, within examinations, between examina-tions), reproducibility (between sites, between manufac-turers, magnetic field strength, and software platforms),and robustness (invariance to changes in pulse sequenceparameters and operator). It is also affected by biologicalcomponents, including temporal variability (within day,between days, in response to physiological changes) andspatial variability in cross-sectional and longitudinalstudies. While accuracy is critical in single-site studies,precision is important in multisite studies, and standardi-zation efforts are needed to properly integrate a bio-marker into clinical trials and patient practice.

Catherine Hines (Merck) compared measures of fatfraction from histology, chemical extraction, and MRI/S.MRI/S measures a signal fat fraction. Once J-coupling, T1

and T2 relaxation, noise, phase errors, multiple fat peaks,and other confounders are considered, the resultant met-ric is a proton-density fat fraction (PDFF), a ratio ofunconfounded fat signal to the sum of the unconfoundedfat and water signals (71). The PDFF only representsMR-visible signals. Protons originating from macromole-cules and solids are MR-invisible and not reflected. Shedescribed biopsy/histology grading of fat in the diagnosisof organ steatosis (72,73), where numerical scores reflectincreasing proportions of fat-involved cells. Next, threechemical processes that yield extraction-based fat frac-tions were illustrated, and Dr. Hines cautioned that thesetechniques destroy the sample. They can be categorizedas: measurement of total lipid mass (Folch method) (74),measurement of triglyceride mass (colorimetric assays)(75), and measurement of triglyceride composition interms of different fatty acid concentrations (gas chroma-tography) (76). When normalized to the sample mass, theendpoints are total lipid, triglyceride, and individualfatty acid mass percents, respectively. While a correla-tion between PDFF and extraction-based fat fraction isexpected, an identity association is nontrivial (77),because extraction-based fat fraction includes both MR-visible and invisible components. She concluded hertalk with recipes for constructing water–fat emulsions,emphasizing antimicrobial agent (sodium azide), emulsi-fiers and surfactants (sodium dodecyl sulfate), and agaringredients. She highlighted D2O (deuterium heavywater) to mimic MR-invisible components.

Mark Bydder (University of California, San Diego)described confounders that affect the accuracy of PDFF,including T1, T2*, and multiple fat peaks (78–80). He clas-sified these factors as operational confounders, in thesense that current MR methods for estimating PDFF mayalso measure other properties of the tissue as well. Con-founders can be addressed by either minimizing their

380 Hu et al.

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effect or postprocessing correction strategies. T1 bias canbe mitigated with low flip angles and long pulse repeti-tion times in gradient echo sequences, or corrected usingpredetermined calibration values. He cautioned that B1

inhomogeneity and variations in T1 between different fatpeaks (81) and in water- or fat-dominant tissues (82)should be considered. He reviewed algorithms with sin-gle or dual T2* terms (29) and demonstrated analytical sol-utions that modeled the degree of fat fraction over- andunder-estimation in two-echo water–fat MRI. Monte-Carlo simulations are needed to describe the effectsacross arbitrary parameters. He also noted that robustnessof the estimated PDFF to changes in T1 and T2* can betested using contrast agents (83). He compared methodsthat used predefined fat resonances and amplitudes andrecent efforts to model peak amplitudes as unknown pa-rameters, describing mathematically each fat resonanceas a function of chain length and the number of (double)C¼¼C and (methylene-interrupted double) C¼¼CAC¼¼Cbonds (30–32). Dr. Bydder acknowledged J-coupling, theinitial phases of water and fat after radiofrequency excita-tion (84), temperature, and eddy currents as additionalconfounders, and commented that some confounders arein fact physical properties of the underlying tissue thatmay themselves find utility as imaging biomarkers.

Angel Pineda (California State University, Fullerton)discussed noise, error propagation, Cram�er-Rao Bound,Fisher Information Matrix, and NSA in water–fat MRI,focusing on 3-echo acquisitions (29,85–87). He empha-sized that the reconstructed image quality of any water–fat MRI algorithm depends on the choice of TEs, echospacings, and the inherent gaussian noise in the rawdata. Dr. Pineda and his collaborators reported thatregardless of the underlying pulse sequence, the NSA isa measure of the noise efficiency of an acquisition andvaries from 0 to N, where N is the number of echoesused to estimate the water and fat. When NSA is close tozero, parameter estimates become unstable and error-prone. The NSA was originally defined for linear sys-tems where only water and fat were the unknowns buthas since been generalized to the Cram�er-Rao Bound def-inition to integrate nonlinear parameter estimates,including object phase, B0 inhomogeneity, and T2*. TheCram�er-Rao Bound analysis allows one to determinehow uncertainties in parameters propagate and to whatextent they impact the confidence in water and fat sepa-ration. In turn, 2D NSA plots reflect the most optimal,and at times nontrivial, choices in TEs that ensure robustwater and fat decomposition with minimal susceptibilityto magnet and gradient imperfections. He demonstratedhow Cram�er-Rao Bound and NSA analysis can alsoquantify improvements in noise performance when con-straints such as B0 fieldmap smoothness are incorpo-rated. Lastly, he showed a sample NSA map generatedfrom the Matlab Toolbox (see below) highlighting thespatial distribution of the variance across the image.

BODY AND CARDIAC APPLICATIONS: ORGANS,ABDOMEN, PELVIS, AND SPINE

Peter Kellman (National Institutes of Health) provided anin-depth look at water–fat MRI in the heart (88,89) and

identified two motivations. First, it facilitates improvedvisualization of anatomical structures in the heart andprovides characterization of myocardial tissue with posi-tive contrast for fat. He showed examples of intramyocar-dial fat and fibrofatty infiltration, lipid containingmasses (lipomas), and epicardial, mediastinal, and peri-cardial fat surrounding the heart. Second, water–fat MRIcan mitigate artifacts and reduce ambiguities that com-monly arise from fat. He demonstrated examples whereelimination of bright epicardial fat signals improved vis-ualization of the myocardium, detection of subepicardialgadolinium enhancement in nonischemic cardiomyopa-thies, differentiation of myocardial fibrosis from fibro-fatty infiltration, and conspicuity of the parietal pericar-dium and coronary arteries. He also showed exampleswhere fat signals can obscure detail of the thin myocar-dial wall due to voxel shifts and signal cancellationsfrom chemical-shift, and where fat infiltration in themyocardium can mimic late gadolinium enhancementand false interpretation of myocardial infarction. Dr.Kellman described electrocardiogram (ECG)-triggeredand segmented 2D multislice breath-held cine acquisi-tions, free-breathing and navigated 3D approaches, andsingle-shot 2D sequences. He also demonstrated magnet-ization preparations (dark blood double inversion recov-ery or inversion recovery for late enhancement).Improved confidence in the interpretation of compli-cated structures and the potential diagnostic value ofidentifying fat in the myocardium are top benefits of car-diac water–fat MRI.

Russell Low (Sharp and Children’s MRI Center) con-tinued with examples of water–fat MRI in the abdomen,pelvis, and spine. The key element of Dr. Low’s presen-tation was the superior diagnostic image qualityachieved with water–fat MRI, where results exhibitedhomogeneous fat suppression while clinically relevantT1 and T2 tissue contrasts were preserved (90). He com-pared water–fat MRI to conventional fat-suppressedcounterparts and noted B0 inhomogeneity as the mainculript of artifacts that can mimic or mask disease anddegrade conspicuity of benign and malignant findings. Inthe abdomen, pelvis, and spine where volume coverageis large, frequency-selective fat saturation strategies canbecome increasingly sensitive to B0 inhomogeneity,Short-Tau Inversion Recovery methods can become lessreliable in suppressing fat signals, and fat-related arti-facts can be exacerbated, especially in obese patients.For example, he illustrated a subtle peritoneal tumor inthe abdomen that is located in the periphery of the ab-dominal cavity and where inhomogeneous fat suppres-sion can obscure visualization. He showed examples ofrenal angiomyolipoma, liposarcoma, and ovarian der-moid that were better visualized with water–fat MRI.Lastly, he commented that a single Dixon acquisitioncan replace conventional protocols utilizing multiplescan to achieve similar tissue contrast with and withoutfat suppression (91). The improved efficiency is criticalin claustrophobic and pediatric patients.

Scott Reeder (University of Wisconsin-Madison) thor-oughly reviewed fat quantification in hepatic steatosis(92). He described hepatic steatosis as abnormal and exces-sive intracellular accumulation of fat in hepatocytes. Long

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considered an incidental consequence of other conditionssuch as diabetes, obesity, and cardiovascular diseases, he-patic steatosis is now recognized as having a causative rolein important hepatic and systemic disorders, includingnonalcoholic fatty liver disease, fibrosis, and cirrhosis,hepatitis C, and hepatocellular carcinoma. He emphasizedthe benefits of a MRI-based biomarker for liver fat in con-trast to percutaneous biopsy, which is invasive and highlysensitive to sampling variability (93). Accurate measure-ment of steatosis with MRI permits frequent evaluation ofthe entire organ with a greatly improved safety profile andreduced cost. It also facilitates monitoring of disease pro-gression and efficacy of treatments in reversing hepatic ste-atosis. A comparison between magnitude- and complex-based methods in multiecho water–fat MRI was made. Theimportance of addressing signal confounders was reiter-ated. These corrections are critical in standardizing PDFFacross MRI platforms as an independent biomarker of he-patic steatosis. Dr. Reeder concluded that developmentsand validations in PDFF and T2*-based iron quantificationapproaches are still needed to mature these metrics intobroadly accepted biomarkers.

DIABETES AND OBESITY

John Wood (Children’s Hospital Los Angeles) focused oniron overload, which occurs in hereditary hemochromato-sis, porphyrias, liver diseases, the metabolic syndrome,thalassemia, sickle-cell anemia, and myelodysplastic syn-drome. Iron toxicity leads to dysfunctions of the pituitary,thyroid and parathyroid glands, and organs such as theliver, pancreas, and heart. It appears to also impact athero-sclerosis, endothelial dysfunction, and osteoporosis. Hedescribed the pathophysiology of iron overload, describingits transferrin-mediated uptake into organs. He explainedthe liver as a high-capacity iron reservoir with low toxicityeffects and characterized the pancreas and heart oppo-sitely. Ferritin is responsible for shuttling iron into intra-cellular lysosomes that protect cells from oxidative effects(94). He highlighted works that correlated T2* with ironconcentration determined from liver biopsies (95,96) andpointed to fat-mediated modulations when signal intensitywas plotted against TE. The magnitude of the residualsremaining after monoexponential data fitting reflected thelevel of lipid present, which in turn correlated positivelywith glucose dysregulation measures (97,98). Dr. Wooddescribed the relationship between iron in the pancreasand the heart (99). He illustrated subjects with normal glu-cose tolerance who had higher T2* values than those withimpaired glucose tolerance and diabetes. There was a pat-tern where progressive iron in the pancreas preceded ironoverload in the heart (100). He noted that iron and fat con-tent, which can be simultaneously measured by water–fatMRI, are both critical biomarkers in diabetes.

Richard Bergman (Cedars-Sinai Medical Center), Edi-tor-in-Chief of Obesity, presented on the pathogenesis ofdiabetes and obesity. He summarized putative causes ofobesity, including high-calorie food and exercise-limitedenvironments, temperature regulation, psychotropicagents, reproductive selection, infectious agents, andsleep deprivation (101), and the negative associationbetween visceral adiposity and insulin sensitivity (102).

He described a canine model to study the complex inter-play between organ steatosis, body adiposity, insulin reg-ulation, diabetes and beta cell failure, and risk for themetabolic syndrome and highlighted the critical roleMRI has played in revealing these relationships. Hedescribed a series of events following a six-week high-fatdiet regimen, which included notable subcutaneous andVAT accumulation, an expected rise in body weight, anincrease in visceral adipocyte size, and elevated fat stor-age in the liver. The latter in turn leads to a decrease inhepatic insulin clearance and hyperinsulinemia, result-ing in insulin resistance at skeletal muscle sites and arise in nocturnal free fatty acid levels. Dr. Bergman notedthat normal functioning beta cells of the pancreatic isletscan compensate for insulin resistance and prevent hyper-glycemia. Lastly, the relationship between insulin sensi-tivity and insulin secretion (e.g., disposition index) wasdescribed (103), and the metric remains the strongest in-dependent predictor of T2D (104).

Michael Goran (University of Southern California), Edi-tor of Pediatric Obesity, presented on differences in sub-cutaneous adipose tissue/VAT and hepatic and pancreaticfat between Hispanics and African Americans. He citeddisparities between the two groups and cautioned that theunderlying mechanisms remain elusive. While VAT islinked to obesity and metabolic dysfunction, this hypoth-esis leads to a paradox (105), because African Americanshave lower VAT and higher subcutaneous adipose tissuecompared to Hispanics (106). Hispanics also have higherhepatic and pancreatic fat (107). However, Hispanics andAfrican Americans are equally at risk for obesity and met-abolic diseases. Part of this disparity can be attributed tothe PNPLA3 allele, a polymorphism that is more prevalentin Hispanics (108,109). Dr. Goran showed that pancreaticfat is correlated with VAT and hepatic fat but is notrelated to insulin resistance and beta-cell function (110).Pancreatic fat is higher in prediabetic African Americansthan those with normal glucose tolerance but not in His-panics. He alluded to adipocyte cell size and macrophageinflammation as plausible explanations. When cell sizeincreases, it indicates the inability of pre-existing adipo-cytes to expand further in number to accommodate addi-tional triglycerides. Larger adipocytes are associated withVAT and hepatic fat, and macrophage accumulation isassociated with higher fasting insulin levels and reducedbeta-cell function (111). He urged the development of MRImethods to facilitate inflammation and cell size measure-ments. He emphasized the desire to image adipokine andcytokine release and to dynamically track fat depositionduring and after meal intake with MRI.

Jurgen Machann (University of Tubingen) discussedcross-sectional and interventional studies in obesity. Hedescribed the utilization of T1-weighted protocols toassess whole-body adiposity (112), single-voxel protonMRS for evaluating hepatic lipids (113,114) and intra-myocellular lipid/extramyocellular lipid (IMCL/EMCL)in the soleus and tibialis anterior muscles, spectral-spa-tial fat-selective techniques (115,116), and automatedand standardized image segmentations (117) to study theconjunction between adipose tissue/ectopic lipids andinsulin resistance. Dr. Machann motivated his talk byhighlighting that insulin resistance is reversible and that

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worsening toward overt T2D can be circumvented bydiet and exercise. He described cross-sectional resultsfrom two studies comprising 550 subjects at increasedrisk for T2D as identified by high body-mass-index (BMI> 27 kg/m2), family history of T2D, impaired glucose tol-erance, and/or gestational diabetes. Results showed thatsubjects with comparable BMI can exhibit very differentsubcutaneous adipose tissue and VAT distributions.Females have �15% more body fat than males in all fatdepots except in VAT, where males have greateramounts (118). He highlighted that in females, less VATand lower hepatic lipid and IMCL were associated withbetter insulin sensitivity and appeared to be a benignform of adiposity (119). He also described a longitudinalstudy involving 400 subjects enrolled in a 2-year pro-gram that included 30% reduced calorie intake from fat,increased fiber uptake, and 3 h of moderate weekly exer-cise. The study demonstrated that improved insulin sen-sitivity goes along with a reduction in VAT and hepaticlipid and that lower baseline values in VAT and hepaticlipid are predictors of a success in lifestyle interventionin respect of metabolic parameters (120).

Rosa Tamara Branca (University of North Carolina atChapel Hill) described MRI of BAT, an organ involved inenergy expenditure and thermogenesis (121–123).Although BAT physiology has been thoroughly studiedin rodents, the role of human BAT remains in question,especially during childhood growth. Positron emissionand computed tomography (PET/CT) is the currentstandard for BAT imaging. The approach, however, ishindered by radiation exposure, the ability to detect onlymetabolically active tissue, and sensitivity to environ-mental temperature. She described the use of chemical-shift water–fat MRI to distinguish BAT and white adi-pose tissue using fat fraction (124,125). She then stressedthat human BAT imaging is challenging, because inadult humans BAT is present only with scattered distri-bution and often mixed with white adipose tissue andmuscle, and that partial volume effects can lead to mis-leading results. She explained that intermolecular zero-quantum coherence spectroscopy, with its sensitivity tothe intravoxel distribution of water and fat spins, mayovercome the partial volume effect and allow users toclearly differentiate white adipose tissue from BAT(126). Dr. Branca concluded by presenting T2-based tech-niques to assess BAT activity with blood oxygen leveldependent MRI in mice, effectively exploiting the greatervascularity and rich mitochondria content of BAT (127).

MR SPECTROSCOPY OF ORGANS, MUSCLES, ANDBONE MARROW

Gavin Hamilton (University of California, San Diego)summarized single-voxel MRS and focused on threethemes: the proton spectrum of triglycerides is complexwith six or more peaks (81); the fat spectrum is shapedby both J-coupling (128) and contributions from distincttriglyceride proton moieties; the relative area of each fatpeak is not fixed but changes depending on the type oftriglyceride (129). He described Point Resolved Spectros-copy (PRESS) (130) and Stimulated Echo AcquisitionMode (STEAM) (131) techniques and noted that both are

equally popular in the literature. While PRESS benefitsfrom increased signal-to-noise ratio, STEAM is capableof shorter minimum TEs (132). Dr. Hamilton demystifiedthe concept of J-coupling. He showed how J-couplingcan lead to nonexponential T2 decay and incorrect fatpeak quantification (133), that all fat peaks experience J-coupling, and that J-coupling effects vary betweenSTEAM and PRESS, even at identical TE (134). Heexplained the MRUI software for MRS analysis (135),and cautioned that the modeling of complex spectrashapes may require multiple Gaussians or Lorentzian fitsper fat peak. He discussed the impact of saturation bandsin MRS fat quantification and reiterated that like itsimaging counterparts, accurate peak-area estimatesrequires T1 and T2 relaxation. Lastly, he showed thatMRS can likewise determine triglyceride carbon chainlength, number of double bonds, and number of methyl-ene-interrupted bonds (81) and can detect differences inthese three parameters in vivo (136).

Lidia Szczepaniak (Cedars-Sinai Medical Center) nextdescribed the application of proton MRS for measurementof triglycerides within the pancreas and the heart (137–142). She motivated her talk by introducing a hypothesison organ steatosis and lipotoxicity, which states that tri-glycerides overflow to ectopic sites due to inefficient fatstorage by adipose tissue depots. Furthermore, chronicdeposits of triglycerides within the cytosol of parenchy-mal cells lead to steatosis and organ dysfunction. Shedescribed strategies for the accurate prescription of MRSvoxels in each organ. She emphasized the importance ofrespiratory and cardiac motion compensation and correc-tion, discussed the lower dynamic range of fat fraction inthe pancreas and the heart, and summarized normal andabnormal ranges of triglyceride levels. She also reviewedstudies demonstrating the development of fatty pancreasand heart in stages that worsen with obesity and glucosetolerance impairment, and noted that steatosis in theseorgans establishes prior to the onset of diabetes and doesnot change significantly further with disease progression.Dr. Szczepaniak discussed how fatty organs are dysfunc-tional. For the pancreas, fat content tracks positively withthe duration of obesity, compensatory insulin secretion,and disposition index, but not with insulin sensitivity.For the heart, she showed positive associations betweenorgan failure and myocardial steatosis in the septum andreduced myocardial contractility in fatty hearts.

Chris Boesch (University of Bern) described fat quanti-fication in skeletal muscles, focusing on the ability ofMRS to differentiate IMCL and EMCL (143,144). WhereasIMCL consists of spherical fat droplets and provideenergy to muscles metabolism, EMCL lipids are arrangedin parallel plates and exhibit characteristics similar toadipose tissue. Magnetic susceptibility causes the fre-quency difference in the ACH2A resonances betweenIMCL and EMCL (144,145), and maximal differenceoccurs when the muscle fibers and the magnetic field areparallel. He emphasized that IMCL levels can fluctuatewith insulin sensitivity, physical activity, diet, pharma-cological effects, and others influences. In particular,obese, sedentary, and diabetic patients are characterizedby higher IMCL levels (146) and lower insulin sensitivity(147,148). However, in athletes, a paradox exists where

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both high IMCL and insulin sensitivity are observed(149–151). Dr. Boesch stressed the need for standardizedIMCL measurements, because preceding diet and physi-cal activity can strongly influence baseline levels (152).He touched on diffusion-weighted characterization ofIMCL (153). As IMCL experiences hindered diffusion,one challenge has been the design of sequences that uti-lize strong diffusion gradients and are robust to phaseerrors from physiological motion. He outlined the poten-tial of using other metabolites in the proton spectrum,such as acetylcarnitine (154,155) to study generalizedaspects of lipid metabolism. He emphasized that 13Cand 31P MRS can provide additional information on sub-strate selection in muscle that may complement theknowledge on skeletal muscle lipid metabolism.

Fritz Schick (University of Tubingen) described periph-eral yellow and vertebral red marrow. He demonstratedhematological diseases where the water and fat content inred marrow changes and how MRI/S can monitor the effi-cacy of therapeutic interventions (113,156,157). In con-trast to yellow marrow, which contains predominantlyfat, red marrow is characterized by similar proportions ofwater from hemopoietic cells, extracellular fluid (plasma),connective tissue, and fat (adipocytes). Red marrow con-sequently exhibits marked microscopic field inhomogene-ities due to the bony trabecular structure and increasediron deposition (hemosiderin), leading to broader MRSresonances. Dr. Schick illustrated examples from acutemyeloid leukemia patients, where red marrow is initiallycharacterized by high cellularity and very little fat signal,because adipocytes are replaced by tumor cells. He thenshowed follow-up examples where effective chemother-apy led to a reduction of cellularity—a decrease in watersignal and progressive increase in fat signal—due toreconstitution of adipocytes in the red marrow. He alsoshowed the efficacy of stem cell transplantation in casesof myeloma, leukemia, lymphoma, neuroblastoma, andEwing’s sarcoma. In this procedure, red marrow is firstablated by high-dose chemotherapy and/or total body irra-diation, destroying all hemopoietic cells in the process.Consequently, cellularity is extremely low. The red mar-row is then repopulated with transfusion of autologous orallogenic stem cells, and the resultant increase in cellular-ity and reconstitution of normal marrow composition canbe visualized with water–fat MRI, magnetization transfer(158), and diffusion pulse sequences. Magnetizationtransfer and diffusion contrast mechanisms exhibit highersensitivity to changes in cellularity immediately follow-ing transplantation.

OUTLOOK

Maren Laughlin (National Institutes of Health) provideda roadmap in fat research. She emphasized the need formore in-depth mechanistic studies of childhood obesity,the maternal effects of obesity to offspring, and the rela-tions between obesity and its comorbidities, particularlyin minorities. She identified funding opportunities topromote interdisciplinary collaborations (PAR-11-221), todevelop interventions and treatments of overweight/obe-sity (PAR-09-124), to create educational opportunities indisease-oriented biomedical research (PAR-10-092), and

to stimulate ongoing work in nonalcoholic steatohepati-tis, bariatric surgery, chronic renal insufficiency, diabe-tes, and adipocyte biology (PAR-09-247). She underlinedBAT, citing that its incidence and metabolic activity,and its response to pharmacological agents, temperature,environment, diet, and exercise, remain largelyunknown. She stressed the need to investigate fat as acomplex organ. Fat depots differ in physiology (e.g., en-docrine functions, metabolism, regulation, and cell line-age), and the interplay between depots in diseases hasnot been thoroughly studied. She highlighted the need toassess the fat redistribution due to lifestyle interventionssuch as bariatric surgery or weight/loss gain due to diet/exercise, along with implications in metabolism and glu-cose regulation, and disease risks. Questions remainwhether certain depots and fat patterns pose more healthrisks than others and whether certain characteristics (tri-glyceride vs. fatty free acids and saturated vs. unsatu-rated) are associated with healthy phenotypes. Lastly,Dr. Laughlin challenged the need to develop MRI meth-ods for monitoring the progression of adipocyte macro-phage inflammation and cell size, and whether theseproperties vary with chemical profiles of the stored fat,alterations in body composition, and metabolic diseases.

POSTER AWARDS AND MATLAB TOOLBOX

Three top-scoring posters were recognized: ‘‘Prospec-tively Accelerated Water–Fat Separation Using ParallelImaging and Compressed Sensing’’ by Samir Sharma(University of Southern California), ‘‘Fat–Water Separa-tion and T2* Estimation Based on Discrete Whole-ImageOptimization in 3D’’ by Johan Berglund (Uppsala Univer-sity), and ‘‘Fast Field Map Estimation with Multi-Label-ing Continuous Max-Flow’’ by Abraam Soliman (Univer-sity of Western Ontario).

Diego Hernando (University of Wisconsin-Madison)spearheaded an initiative to develop a Matlab Toolboxfor water–fat data reconstruction. The goals were to estab-lish a resource for investigators to implement previouslypublished algorithms without having to ‘‘reinvent thewheel,’’ and to provide an interface that utilized a com-mon input/output structure. The toolbox consisted of:

• Reconstruction algorithms for 2D/3D Cartesian andnon-Cartesian (e.g., spiral, concentric rings) data, andundersampled compressed sensing trajectories wereprovided. Users can toggle and select single or multi-ple peak fat spectral modeling, the saturation degreeof triglycerides, magnitude or complex data fitting,initial phase constraints, T2* fitting, and various B0

fieldmap estimation approaches. Postprocessing suchas image deblurring and the computation of fat frac-tion and NSA maps were also included. Instructionsand descriptions of parameters were provided.

• Multiple data sets including 2D/3D, single/multicoil,and 2–15 echoes, from cardiac, abdomen, thigh,knee, ankle, and phantoms, acquired at 1.5 and 3.0T, were provided. Code to generate synthetic datawas also included.

The toolbox was distributed to workshop attendees andcan be downloaded from the ISMRM website. Attendees

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were encouraged to ‘‘plug-n-play’’ the existing code,tweak and improve the algorithms, integrate the codebuilding blocks to tailor to their specific applications,and provide feedback. Along with Diego Hernando, con-tributions came from Johan Berglund, Emily Bice, MarkBydder, Mariya Doneva, Holger Eggers, Houchun Hu,Yun Jiang, Peter Kellman, Wenmiao Lu, Angel Pineda,Samir Sharma, Jeffrey Tsao, and Holden Wu. Investiga-tors interested in gaining toolbox access and contributingto future versions, which are planned to be made avail-able to the general ISMRM community, should contactDiego Hernando ([email protected]) or Houchun Hu([email protected]).

CONCLUSIONS

Water–fat MRI methods are a critical toolset, and theirutility is gaining momentum. Nearly 30 years after Dix-on’s seminal manuscript on ‘‘simple proton spectro-scopic imaging,’’ new findings, novel methodologies, andinnovative applications continue to progress. The water–fat community is strong and active. The workshop wassuccessful in fostering collaborations and dialog, identi-fying challenges and opportunities, and promoting con-sensus in standardizing qualitative and quantitativewater–fat techniques. As a result of the collective effortsof many talented scientists who have advanced thisfield, our knowledge of water–fat MRI has significantlyexpanded, the topic has greatly matured, and applica-tions that can benefit from water–fat MRI have broad-ened. Accompanying this summary is a MRM VirtualIssue on the journal’s website that lists water–fat MRIcontributions in 2010 and 2011.

ACKNOWLEDGMENTS

The organizers are grateful to the ISMRM staff for theirassistance. The authors thank ISMRM’s corporate mem-bers, and specifically Joanna Jobson (GE Healthcare),Gordon Herron (Philips Healthcare), and Stuart Clarkson(Toshiba America Medical Systems), for their sponsor-ship. They thank the speakers for their contributions andthe attendees for their participation.

REFERENCES

1. Dixon WT. Simple proton spectroscopic imaging. Radiology 1984;

153:189–194.

2. Sepponen RE, Sipponen JT, Tanttu JI. A method for chemical

shift imaging: demonstration of bone marrow involvement with

proton chemical shift imaging. J Comput Assist Tomogr 1984;8:

585–587.

3. Blatter DD, Morris AH, Ailion DC, Cutillo AG, Case TA. Asymmet-

ric spin echo sequences. A simple new method for obtaining NMR

1H spectral images. Invest Radiol 1985;20:845–853.

4. Borrello JA, Chenevert TL, Meyer CR, Aisen AM, Glazer GM. Chem-

ical shift-based true water and fat images: regional phase correction

of modified spin-echo MR images. Radiology 1987;164:531–537.

5. Kim YS, Mun CW, Cho ZH. Chemical-shift imaging with large mag-

netic field inhomogeneity. Magn Reson Med 1987;4:452–460.

6. Lodes CC, Felmlee JP, Ehman RL, Sehgal CM, Greenleaf JF, Glover

GH, Gray JE. Proton MR chemical shift imaging using double and

triple phase contrast acquisition methods. J Comput Assist Tomogr

1989;13:855–861.

7. Glover GH, Schneider E. Three-point Dixon technique for true

water/fat decomposition with B0 inhomogeneity correction. Magn

Reson Med 1991;18:371–383.

8. Skinner TE, Glover GH. An extended two-point Dixon algorithm for

calculating separate water, fat, and B0 images. Magn Reson Med

1997;37:628–630.

9. Wang Y, Li D, Haacke EM, Brown JJ. A three-point Dixon method

for water and fat separation using 2D and 3D gradient-echo techni-

ques. J Magn Reson Imaging 1998;8:703–710.

10. Brix G, Heiland S, Bellemann ME, Koch T, Lorenz WJ. MR imaging

of fat-containing tissues: valuation of two quantitative imaging tech-

niques in comparison with localized proton spectroscopy. Magn

Reson Imaging 1993;11:977–991.

11. Zhang W, Goldhaber DM, Kramer DM. Separation of water and fat

MR images in a single scan at .35 T using ‘‘sandwich’’ echoes. J

Magn Reson Imaging 1996;6:909–917.

12. Ma J, Singh SK, Kumar AJ, Leeds NE, Broemeling LD. Method for

efficient fast spin echo Dixon imaging. Magn Reson Med 2002;48:

1021–1027.

13. Delfaut EM, Beltran J, Johnson G, Rousseau J, Marchandise X, Cot-

ten A. Fat suppression in MR imaging: techniques and pitfalls.

Radiographics 1999;19:373–382.

14. Hussain SM. Liver MRI: correlation with other imaging modalities

and histopathology. Secaucus, NJ: Springer-Verlag; 2007. 250 p.

15. Canapari CA, Hoppin AG, Kinane B, Thomas BJ, Torriani M. Rela-

tionship between Sleep Apnea, Fat Distribution, and Insulin Resist-

ance in Obese Children. Clin Sleep Med 2011;7:268–273.

16. Gilsanz V, Chung SA, Kaplowitz N. Differential effect of gender on

hepatic fat. Pediatr Radiol 2011;41:1146–1153.

17. Schwimmer JB, Deutsch R, Kahen T, Lavine JE, Stanley C, Behling

C. Prevalence of fatty liver in children and adolescents. Pediatrics

2006;118:1388–1393.

18. Ahn CB, Lee SY, Nalcioglu O, Cho ZH. Spectroscopic imaging by

quadrature modulated echo time shifting, Magn Reson Imaging

1986;4:110–111.

19. Xiang QS. Improved single point water–fat imaging with virtual

shimming. Proc Intl Soc Magn Reson Med 2001;9:789.

20. Son J, Ji J, Ma J. Three-dimensional T1-weighted MR imaging using

a one-point Dixon technique with arbitrary echo times. Proc Intl

Soc Magn Reson Med 2005;13:893.

21. Ma J. A single-point Dixon technique for fat-suppressed fast 3D gra-

dient-echo imaging with a flexible echo time. J Magn Reson Imaging

2008;27:881–890.

22. Xiang QS. Two-point water–fat imaging with partially-opposed-

phase (POP) acquisition: an asymmetric Dixon method. Magn Reson

Med 2006;56:572–584.

23. Eggers H, Brendel B, Duijndam A, Herigault G. Dual-echo Dixon

imaging with flexible choice of echo times. Magn Reson Med 2011;

65:96–107.

24. Berglund J, Ahlstr€om H, Johansson L, Kullberg J. Two-point Dixon

method with flexible echo times. Magn Reson Med. 2011;65:

994–1004.

25. Xiang QS, An L. Water–fat imaging with direct phase encoding. J

Magn Reson Imaging 1997;7:1002–1015.

26. Xiang QS. Simultaneous water–fat and T2* mapping with 3-point

acquisitions. Proc Intl Soc Magn Reson Med 2008;16:1383.

27. An L, Xiang QS. Chemical shift imaging with spectrum modeling.

Magn Reson Med 2001;46:126–130.

28. Yu H, Shimakawa A, McKenzie CA, Lu W, Reeder SB, Hinks RS,

Brittain JH. Phase and amplitude correction for multi-echo water–

fat separation with bipolar acquisitions. J Magn Reson Imaging

2011;31:1264–1271.

29. Reeder SB, Bice EK, Yu H, Hernando D, Pineda AR. On the per-

formance of T2* correction methods for quantification of hepatic fat

content. Magn Reson Med 2011;67:389–404.

30. Peterson P, Mansson S. Simultaneous quantification of fat fraction

and fatty acid composition using MRI. Proc Intl Soc Magn Reson

Med 2011;19:2712.

31. Bydder M, Girard O, Hamilton G. Mapping the double bonds in tri-

glycerides. Magn Reson Imaging 2011;29:1041–1046.

32. Berglund J, Ahlstrom H, Kullberg J. Model-based mapping of fat

unsaturation and chain length by chemical shift imaging-phantom

validation and in vivo feasibility. Magn Reson Med, 2012; doi:

10.1002/mrm.24196.

33. Reeder SB, McKenzie CA, Pineda AR, Yu H, Shimakawa A, Brau

AC, Hargreaves BA, Gold GE, Brittain JH. Water–fat separation with

IDEAL gradient-echo imaging. J Magn Reson Imaging 2007;25:

644–652.

2012 ISMRM Workshop on Fat–Water Separation 385

Page 9: ISMRM workshop on fat-water separation: Insights, applications and progress in MRI

34. Hardy PA, Hinks RS, Tkach JA. Separation of fat and water in fast

spin-echo MR imaging with the three-point Dixon technique. J

Magn Reson Imaging 1995;5:181–185.

35. Li Z, Gmitro AF, Bilgin A, Altbach MI. Fast decomposition of water

and lipid using a GRASE technique with the IDEAL algorithm.

Magn Reson Med 2007;57:1047–1057.

36. Chen JH, Le HC, Koutcher JA, Singer S. Fat-free MRI based on mag-

netization exchange. Magn Reson Med 2010;63:713–718.

37. Scheffler K, Heid O, Hennig J. Magnetization preparation during the

steady state: fat-saturated 3D TrueFISP. Magn Reson Med 2001;45:

1075–1080.

38. Kornaat PR, Doornbos J, van der Molen AJ, Kloppenburg M, Nelis-

sen RG, Hogendoorn PC, Bloem JL. Magnetic resonance imaging of

knee cartilage using a water selective balanced steady-state free pre-

cession sequence. J Magn Reson Imaging 2004;20:850–856.

39. Hargreaves BA, Vasanawala SS, Nayak KS, Hu BS, Nishimura DG.

Fat-suppressed steady-state free precession imaging using phase

detection. Magn Reson Med 2003;50:210–213.

40. Worters PW, Saranathan M, Xu A, Vasanawala SS. Inversion-recov-

ery-prepared Dixon bSSFP: initial clinical experience with a novel

pulse sequence for renal MRA within a breathhold. J Magn Reson

Imaging 2012;35:875–881.

41. Quist B, Hargreaves BA, Cukur T, Morrell GR, Gold GE, Bangerter

NK. Simultaneous fat suppression and band reduction with large-

angle multiple-acquisition balanced steady-state free precession.

Magn Reson Med 2012;67:1004–1012.

42. Vasanawala S, Pauly J, Nishimura D, Gold G. MR imaging of knee

cartilage with FEMR. Skeletal Radiol 2002;31:574–580.

43. Vasanawala SS, Pauly JM, Nishimura DG. Linear combination

steady-state free precession MRI. Magn Reson Med 2000;43:82–90.

44. Leupold J, Hennig J, Scheffler K. Alternating repetition time bal-

anced steady state free precession. Magn Reson Med 2006;55:

557–565.

45. Nayak KS, Lee HL, Hargreaves BA, Hu BS. Wideband SSFP: alter-

nating repetition time balanced steady state free precession with

increased band spacing. Magn Reson Med 2007;58:931–938.

46. Cukur T, Nishimura DG. Multiple repetition time balanced steady-

state free precession imaging. Magn Reson Med 2009;62:193–204.

47. Ma J. Dixon techniques for water and fat imaging. J Magn Reson

Imaging 2008;28:543–558.

48. Yu H, Reeder SB, Shimakawa A, Brittain JH, Pelc NJ. Field map

estimation with a region growing scheme for iterative 3-point

water–fat decomposition. Magn Reson Med 2005;54:1032–1039.

49. Berglund J, Johansson L, Ahlstrom H, Kullberg J. Three-point Dixon

method enables whole-body water and fat imaging of obese sub-

jects. Magn Reson Med 2010;63:1659–1668.

50. Lu W, Hargreaves BA. Multiresolution field map estimation using

golden section search for water–fat separation. Magn Reson Med

2008;60:236–244.

51. Tsao J, Jiang Y. Hierarchical IDEAL: robust water–fat separation at

high field by multiresolution field map estimation. Proc Intl Soc

Magn Reson Med 2008;16:653.

52. Narayan S, Huang F, Johnson D, Gargesha M, Flask CA, Zhang GQ,

Wilson DL. Fast lipid and water levels by extraction with spatial

smoothing (FLAWLESS): three-dimensional volume fat/water sepa-

ration at 7 Tesla. J Magn Reson Imaging 2011;33:1464–1473.

53. Jacob M, Sutton BP. Algebraic decomposition of fat and water in

MRI. IEEE Trans Med Imaging 2009;28:173–184.

54. Hernando D, Kellman P, Haldar JP, Liang ZP. Robust water/fat sepa-

ration in the presence of large field inhomogeneities using a graph

cut algorithm. Magn Reson Med 2009;63:79–90.

55. Berglund J, Kullberg J. Three-dimensional water/fat separation and

T2* estimation based on whole-image optimization—application in

breathhold liver imaging at 1.5 T. Magn Reson Med 2012;67:

1684–1693.

56. Reeder SB, Hargreaves BA, Yu H, Brittain JH. Homodyne recon-

struction and IDEAL water–fat decomposition. Magn Reson Med

2005;54:586–593.

57. Ma J, Son JB, Bankson JA, Stafford RJ, Choi H, Ragan D. A fast spin

echo two-point Dixon technique and its combination with sensitiv-

ity encoding for efficient T2-weighted imaging. Magn Reson Imaging

2005;23:977–982.

58. Reeder S, Vu A, Hargreaves B, Shimakawa A, Wieben O, McKenzie

C, Polzin J, Brittain J. Rapid 3D-SPGR Imaging of the Liver with

Multi-Echo IDEAL. Proc Intl Soc Magn Reson Med 2006;14:2444.

59. Koken P, Eggers H, B€ornert P. Fast single breath-hold 3D abdominal

imaging with water–fat separation. Proc Intl Soc Magn Reson Med

2007;15:1623.

60. Brodsky EK, Holmes JH, Yu H, Reeder SB. Generalized k-space

decomposition with chemical shift correction for non-Cartesian

water–fat imaging. Magn Reson Med 2008;59:1151–1164.

61. Doneva M, Bornert P, Eggers H, Mertins A, Pauly J, Lustig M. Com-

pressed sensing for chemical shift-based water–fat separation. Magn

Reson Med 2010;64:1749–1759.

62. Sharma SD, Hu HH, Nayak KS. Accelerated water–fat imaging using

restricted subspace field map estimation and compressed sensing.

Magn Reson Med 2012;67:650–659.

63. Wiens CN, McCurdy C, McKenzie CA. A combined approach to

compressed sensing and parallel imaging for fat–water separation

with R2* estimation. Proc Intl Soc Magn Reson Med 2012;20:7.

64. Sharma SD, Hu HH, Nayak KS. Accelerated water–fat separation

using parallel imaging, compressed sensing, and multiscale cubic

B-splines. Proc Intl Soc Magn Reson Med 2012;20:4170.

65. Moriguchi H, Lewin JS, Duerk JL. Dixon techniques in spiral trajec-

tories with off-resonance correction: a new approach for fat signal

suppression without spatial-spectral RF pulses. Magn Reson Med

2003;50:915–924.

66. Bornert P, Koken P, Eggers H. Spiral water–fat imaging with inte-

grated off-resonance correction on a clinical scanner. J Magn Reson

Imaging 2010;32:1262–1267.

67. Huo D, Li Z, Aboussouan E, Karis JP, Pipe JG. Turboprop IDEAL: a

motion-resistant fat–water separation technique. Magn Reson Med

2009;61:188–195.

68. Wu HH, Lee JH, Nishimura DG. Fat/water separation using a con-

centric rings trajectory. Magn Reson Med 2009;61:639–649.

69. Goodsaid F, Frueh F. Biomarker qualification pilot process at the

US food and drug administration. AAPS J 2007;9:E105–E108.

70. FDA Guidance for Industry. Validation of analytical procedures:

defintion and terminology. U.S. Department of Health and Human

Services. Food and Drug Administration Center for Veterinary Med-

icine; July 1999.

71. Reeder SB, Sirlin CB. Quantification of liver fat with magnetic reso-

nance imaging. Magn Reson Imaging Clin N Am 2010;18:337–357,

ix.

72. Brunt EM, Janney CG, Di Bisceglie AM, Neuschwander-Tetri BA,

Bacon BR. Nonalcoholic steatohepatitis: a proposal for grading and

staging the histological lesions. Am J Gastroenterol 1999;94:

2467–2474.

73. Kleiner DE, Brunt EM, Van Natta M, Behling C, Contos MJ, Cum-

mings OW, Ferrell LD, Liu YC, Torbenson MS, Unalp-Arida A, Yeh

M, McCullough AJ, Sanyal AJ. Design and validation of a histologi-

cal scoring system for nonalcoholic fatty liver disease. Hepatology

2005;41:1313–1321.

74. Folch J, Lees M, Sloane Stanley GH. A simple method for the isola-

tion and purification of total lipids from animal tissues. J Biol

Chem 1957;226:497–509.

75. Hines CD, Agni R, Roen C, Rowland I, Hernando D, Bultman E,

Horng D, Yu H, Shimakawa A, Brittain JH, Reeder SB. Validation of

MRI biomarkers of hepatic steatosis in the presence of iron overload

in the ob/ob mouse. J Magn Reson Imaging 2011;35:844–851.

76. Vuppalanchi R, Cummings OW, Saxena R, Ulbright TM, Martis N,

Jones DR, Bansal N, Chalasani N. Relationship among histologic,

radiologic, and biochemical assessments of hepatic steatosis: a

study of human liver samples. J Clin Gastroenterol 2007;41:

206–210.

77. Marsman HA, van Werven JR, Nederveen AJ, Ten Kate FJ, Heger M,

Stoker J, van Gulik TM. Noninvasive quantification of hepatic stea-

tosis in rats using 3.0T 1H-magnetic resonance spectroscopy. J

Magn Reson Imaging 2010;32:148–154.

78. Liu CY, McKenzie CA, Yu H, Brittain JH, Reeder SB. Fat quantifica-

tion with IDEAL gradient echo imaging: correction of bias from T1

and noise. Magn Reson Med 2007;58:354–364.

79. Yu H, Shimakawa A, McKenzie CA, Brodsky E, Brittain JH, Reeder

SB. Multiecho water–fat separation and simultaneous R2* estima-

tion with multifrequency fat spectrum modeling. Magn Reson Med

2008;60:1122–1134.

80. Bydder M, Yokoo T, Hamilton G, Middleton MS, Chavez AD,

Schwimmer JB, Lavine JE, Sirlin CB. Relaxation effects in the quan-

tification of fat using gradient echo imaging. Magn Reson Imaging

2008;26:347–359.

386 Hu et al.

Page 10: ISMRM workshop on fat-water separation: Insights, applications and progress in MRI

81. Hamilton G, Yokoo T, Bydder M, Cruite I, Schroeder ME, Sirlin CB,

Middleton MS. In vivo characterization of the liver fat (1)H MR

spectrum. NMR Biomed 2010;24:784–790.

82. Hu HH, Nayak KS. Change in the proton T1 of fat and water in mix-

ture. Magn Reson Med 2010;63:494–501.

83. Yokoo T, Collins JM, Hanna RF, Bydder M, Middleton MS, Sirlin

CB. Effects of intravenous gadolinium administration and flip

angle on the assessment of liver fat signal fraction with opposed-

phase and in-phase imaging. J Magn Reson Imaging 2008;28:

246–251.

84. Bydder M, Yokoo T, Yu H, Carl M, Reeder SB, Sirlin CB. Constrain-

ing the initial phase in water–fat separation. Magn Reson Imaging

2011;29:216–221.

85. Pineda AR, Reeder SB, Wen Z, Pelc NJ. Cramer-Rao bounds for

three-point decomposition of water and fat. Magn Reson Med 2005;

54:625–635.

86. Chebrolu VV, Yu H, Pineda AR, McKenzie CA, Brittain JH, Reeder

SB. Noise analysis for 3-point chemical shift-based water–fat sepa-

rationwith spectral modeling of fat. J Magn Reson Imaging 2010;32:

493–500.

87. Hernando D, Liang ZP, Kellman P. Chemical shift-based water/fat

separation: a comparison of signal models. Magn Reson Med 2010;

64:811–822.

88. Kellman P, Hernando D, Arai AE. Myocardial fat imaging. Curr Car-

diovasc Imaging Rep 2010;3:83–91.

89. Kellman P, Hernando D, Shah S, Zuehlsdorff S, Jerecic R, Mancini

C, Liang ZP, Arai AE. Multiecho Dixon fat and water separation

method for detecting fibrofatty infiltration in the myocardium.

Magn Reson Med 2009;61:215–221.

90. Low RN, Panchal N, Vu AT, Knowles A, Estkowski L, Slavens Z,

Ma J. Three-dimensional fast spoiled gradient-echo dual echo (3D-

FSPGR-DE) with water reconstruction: preliminary experience with

a novel pulse sequence for gadolinium-enhanced abdominal MR

imaging. J Magn Reson Imaging 2008;28:946–956.

91. Low RN, Austin MJ, Ma J. Fast spin-echo triple echo Dixon: initial

clinical experience with a novel pulse sequence for simultaneous

fat-suppressed and nonfat-suppressed T2-weighted spine magnetic

resonance imaging. J Magn Reson Imaging 2011;33:390–400.

92. Reeder SB, Cruite I, Hamilton G, Sirlin CB. Quantitative assessment

of liver fat with magnetic resonance imaging and spectroscopy. J

Magn Reson Imaging 2011;34:729–749.

93. Ratziu V, Charlotte F, Heurtier A, Gombert S, Giral P, Bruckert E,

Grimaldi A, Capron F, Poynard T. Sampling variability of liver bi-

opsy in nonalcoholic fatty liver disease. Gastroenterology 2005;128:

1898–1906.

94. Noetzli LJ, Carson SM, Nord AS, Coates TD, Wood JC. Longitudinal

analysis of heart and liver iron in thalassemia major. Blood 2008;

112:2973–2978.

95. St Pierre TG, Clark PR, Chua-Anusorn W, Fleming AJ, Jeffrey GP,

Olynyk JK, Pootrakul P, Robins E, Lindeman R. Noninvasive mea-

surement and imaging of liver iron concentrations using proton

magnetic resonance. Blood 2005;105:855–861.

96. Wood JC, Enriquez C, Ghugre N, Tyzka JM, Carson S, Nelson MD,

Coates TD. MRI R2 and R2* mapping accurately estimates hepatic

iron concentration in transfusion-dependent thalassemia and sickle

cell disease patients. Blood 2005;106:1460–1465.

97. Ghugre NR, Coates TD, Nelson MD, Wood JC. Mechanisms of tis-

sue-iron relaxivity: nuclear magnetic resonance studies of human

liver biopsy specimens. Magn Reson Med 2005;54:1185–1193.

98. Ghugre NR, Gonzalez-Gomez I, Butensky E, Noetzli L, Fischer R,

Williams R, Harmatz P, Coates TD, Wood JC. Patterns of hepatic

iron distribution in patients with chronically transfused thalassemia

and sickle cell disease. Am J Hematol 2009;84:480–483.

99. Ghugre NR, Enriquez CM, Gonzalez I, Nelson MD Jr, Coates TD,

Wood JC. MRI detects myocardial iron in the human heart. Magn

Reson Med 2006;56:681–686.

100. Noetzli LJ, Papudesi J, Coates TD, Wood JC. Pancreatic iron loading

predicts cardiac iron loading in thalassemia major. Blood 2009;114:

4021–4026.

101. McAllister EJ, Dhurandhar NV, Keith SW, Aronne LJ, Barger J, Bas-

kin M, Benca RM, Biggio J, Boggiano MM, Eisenmann JC, Elobeid

M, Fontaine KR, Gluckman P, Hanlon EC, Katzmarzyk P, Pietrobelli

A, Redden DT, Ruden DM, Wang C, Waterland RA, Wright SM,

Allison DB. Ten putative contributors to the obesity epidemic. Crit

Rev Food Sci Nutr 2009;49:868–913.

102. Kabir M, Stefanovski D, Hsu IR, Iyer M, Woolcott OO, Zheng D, Cat-

alano KJ, Chiu JD, Kim SP, Harrison LN, Ionut V, Lottati M, Berg-

man RN, Richey JM. Large size cells in the visceral adipose depot

predict insulin resistance in the canine model. Obesity (Silver

Spring) 2011;19:2121–2129.

103. Bergman RN, Phillips LS, Cobelli C. Physiologic evaluation of fac-

tors controlling glucose tolerance in man: measurement of insulin

sensitivity and beta-cell glucose sensitivity from the response to in-

travenous glucose. J Clin Invest 1981;68:1456–1467.

104. Lyssenko V, Almgren P, Anevski D, Perfekt R, Lahti K, Nissen M,

Isomaa B, Forsen B, Homstrom N, Saloranta C, Taskinen MR, Groop

L, Tuomi T. Predictors of and longitudinal changes in insulin sensi-

tivity and secretion preceding onset of type 2 diabetes. Diabetes

2005;54:166–174.

105. Goran MI. Ethnic-specific pathways to obesity-related disease: the

Hispanic vs. African-American paradox. Obesity (Silver Spring)

2008;16:2561–2565.

106. Goran MI, Nagy TR, Treuth MS, Trowbridge C, Dezenberg C,

McGloin A, Gower BA. Visceral fat in white and African American

prepubertal children. Am J Clin Nutr 1997;65:1703–1708.

107. Browning JD, Szczepaniak LS, Dobbins R, Nuremberg P, Horton JD,

Cohen JC, Grundy SM, Hobbs HH. Prevalence of hepatic steatosis in

an urban population in the United States: impact of ethnicity. He-

patology 2004;40:1387–1395.

108. Goran MI, Walker R, Le KA, Mahurkar S, Vikman S, Davis JN,

Spruijt-Metz D, Weigensberg MJ, Allayee H. Effects of PNPLA3 on

liver fat and metabolic profile in Hispanic children and adolescents.

Diabetes 2010;59:3127–3130.

109. Davis JN, Le KA, Walker RW, Vikman S, Spruijt-Metz D, Weigens-

berg MJ, Allayee H, Goran MI. Increased hepatic fat in overweight

Hispanic youth influenced by interaction between genetic variation

in PNPLA3 and high dietary carbohydrate and sugar consumption.

Am J Clin Nutr 2010;92:1522–1527.

110. Le KA, Ventura EE, Fisher JQ, Davis JN, Weigensberg MJ, Punyani-

tya M, Hu HH, Nayak KS, Goran MI. Ethnic differences in pancre-

atic fat accumulation and its relationship with other fat depots and

inflammatory markers. Diabetes Care 2011;34:485–490.

111. Le KA, Mahurkar S, Alderete TL, Hasson RE, Adam TC, Kim JS,

Beale E, Xie C, Greenberg AS, Allayee H, Goran MI. Subcutaneous

adipose tissue macrophage infiltration is associated with hepatic

and visceral fat deposition, hyperinsulinemia, and stimulation of

NF-kappaB stress pathway. Diabetes 2011;60:2802–2809.

112. Machann J, Thamer C, Schnoedt B, Haap M, Haring HU, Claussen

CD, Stumvoll M, Fritsche A, Schick F. Standardized assessment of

whole body adipose tissue topography by MRI. J Magn Reson Imag-

ing 2005;21:455–462.

113. Machann J, Stefan N, Schick F. 1H MR spectroscopy of skeletal

muscle, liver and bone marrow. Eur J Radiol 2008;67:275–284.

114. Machann J, Thamer C, Schnoedt B, Stefan N, Haring HU, Claussen

CD, Fritsche A, Schick F. Hepatic lipid accumulation in healthy

subjects: a comparative study using spectral fat-selective MRI and

volume-localized 1H-MR spectroscopy. Magn Reson Med 2006;55:

913–917.

115. Schick F, Machann J, Brechtel K, Strempfer A, Klumpp B, Stein DT,

Jacob S. MRI of muscular fat. Magn Reson Med 2002;47:720–727.

116. Machann J, Bachmann OP, Brechtel K, Dahl DB, Wietek B, Klumpp

B, Haring HU, Claussen CD, Jacob S, Schick F. Lipid content in the

musculature of the lower leg assessed by fat selective MRI: intra-

and interindividual differences and correlation with anthropometric

and metabolic data. J Magn Reson Imaging 2003;17:350–357.

117. Wurslin C, Machann J, Rempp H, Claussen C, Yang B, Schick F. To-

pography mapping of whole body adipose tissue using A fully auto-

mated and standardized procedure. J Magn Reson Imaging 2010;31:

430–439.

118. Machann J, Thamer C, Schnoedt B, Stefan N, Stumvoll M, Haring

HU, Claussen CD, Fritsche A, Schick F. Age and gender related

effects on adipose tissue compartments of subjects with increased

risk for type 2 diabetes: a whole body MRI/MRS study. Magma

2005;18:128–137.

119. Stefan N, Kantartzis K, Machann J, Schick F, Thamer C, Rittig K,

Balletshofer B, Machicao F, Fritsche A, H€aring HU. Identification

and characterization of metabolically benign obesity in humans.

Arch Intern Med 2008;168:1609–1616.

120. Machann J, Thamer C, Stefan N, Schwenzer NF, Kantartzis K, Har-

ing HU, Claussen CD, Fritsche A, Schick F. Follow-up whole-body

2012 ISMRM Workshop on Fat–Water Separation 387

Page 11: ISMRM workshop on fat-water separation: Insights, applications and progress in MRI

assessment of adipose tissue compartments during a lifestyle inter-

vention in a large cohort at increased risk for type 2 diabetes. Radi-

ology 2010;257:353–363.

121. Nedergaard J, Bengtsson T, Cannon B. Unexpected evidence for

active brown adipose tissue in adult humans. Am J Physiol Endo-

crinol Metab 2007;293:E444–E452.

122. Nedergaard J, Cannon B. The changed metabolic world with human

brown adipose tissue: therapeutic visions. Cell Metab 2010;11:

268–272.

123. Cannon B, Nedergaard J. Brown adipose tissue: function and physi-

ological significance. Physiol Rev 2004;84:277–359.

124. Hu HH, Smith DL Jr, Nayak KS, Goran MI, Nagy TR. Identification

of brown adipose tissue in mice with fat–water IDEAL-MRI. J Magn

Reson Imaging 2010;31:1195–1202.

125. Hu HH, Tovar J, Pavlova Z, Smith ML, Gilsanz V. Unequivocal

identification of brown adipose tissue in a human infant. J Magn

Reson Imaging 2012;35:938–942.

126. Branca RT, Warren WS. In vivo brown adipose tissue detection and

characterization using water–lipid intermolecular zero-quantum

coherences. Magn Reson Med 2011;65:313–319.

127. Khanna A, Branca RT. Detecting brown adipose tissue activity with

BOLD MRI in mice. Magn Reson Med, 2012; doi:10.1002/

mrm.24118.

128. Schick F, Nagele T, Klose U, Lutz O. Lactate quantification by

means of press spectroscopy—influence of refocusing pulses and

timing scheme. Magn Reson Imaging 1995;13:309–319.

129. Ren J, Dimitrov I, Sherry AD, Malloy CR. Composition of adipose

tissue and marrow fat in humans by 1H NMR at 7 Tesla. J Lipid

Res 2008;49:2055–2062.

130. Bottomley PA. Spatial localization in NMR spectroscopy in vivo.

Ann NY Acad Sci 1987;508:333–348.

131. Frahm J, Bruhn H, Gyngell ML, Merboldt KD, Hanicke W, Sauter R.

Localized high-resolution proton NMR spectroscopy using stimu-

lated echoes: initial applications to human brain in vivo. Magn

Reson Med 1989;9:79–93.

132. Thompson RB, Allen PS. Response of metabolites with coupled

spins to the STEAM sequence. Magn Reson Med 2001;45:955–965.

133. Ernst T, Hennig J. Coupling effects in volume selective 1H spectros-

copy of major brain metabolites. Magn Reson Med 1991;21:82–96.

134. Hamilton G, Middleton MS, Bydder M, Yokoo T, Schwimmer JB,

Kono Y, Patton HM, Lavine JE, Sirlin CB. Effect of PRESS and

STEAM sequences on magnetic resonance spectroscopic liver fat

quantification. J Magn Reson Imaging 2009;30:145–152.

135. Naressi A, Couturier C, Castang I, de Beer R, Graveron-Demilly D.

Java-based graphical user interface for MRUI, a software package for

quantitation of in vivo/medical magnetic resonance spectroscopy

signals. Comput Biol Med 2001;31:269–286.

136. Hamilton G, Middleton MS, Yokoo T, Sirlin CB. Regional variability

in triglyceride composition of adipose tissue measured by 1H MRS.

Proc Intl Soc Magn Reson Med 2011;19:3006.

137. Szczepaniak LS, Babcock EE, Schick F, Dobbins RL, Garg A, Burns

DK, McGarry JD, Stein DT. Measurement of intracellular triglyceride

stores by 1H spectroscopy: validation in vivo. Am J Physiol 1999;

276(pt 1):E977–E989.

138. Szczepaniak LS, Dobbins RL, Metzger GJ, Sartoni-D’Ambrosia G,

Arbique D, Vongpatanasin W, Unger R, Victor RG. Myocardial tri-

glycerides and systolic function in humans: in vivo evaluation by

localized proton spectroscopy and cardiac imaging. Magn Reson

Med 2003;49:417–423.

139. Szczepaniak LS, Victor RG, Orci L, Unger RH. Forgotten but not

gone: the rediscovery of fatty heart, the most common unrecognized

disease in America. Circ Res 2007;101:759–767.

140. McGavock JM, Lingvay I, Zib I, Tillery T, Salas N, Unger R, Levine

BD, Raskin P, Victor RG, Szczepaniak LS. Cardiac steatosis in dia-

betes mellitus: a 1H-magnetic resonance spectroscopy study. Circu-

lation 2007;116:1170–1175.

141. Lingvay I, Raskin P, Szczepaniak LS. The fatty hearts of patients

with diabetes. Nat Rev Cardiol 2009;6:268–269.

142. Lingvay I, Esser V, Legendre JL, Price AL, Wertz KM, Adams-Huet

B, Zhang S, Unger RH, Szczepaniak LS. Noninvasive quantification

of pancreatic fat in humans. J Clin Endocrinol Metab 2009;94:

4070–4076.

143. Schick F, Eismann B, Jung WI, Bongers H, Bunse M, Lutz O. Com-

parison of localized proton NMR signals of skeletal muscle and fat

tissue in vivo: two lipid compartments in muscle tissue. Magn

Reson Med 1993;29:158–167

144. Boesch C, Slotboom J, Hoppeler H, Kreis R. In vivo determination

of intra-myocellular lipids in human muscle by means of localized

1H-MR-spectroscopy. Magn Reson Med 1997;37:484–493.

145. Szczepaniak LS, Dobbins RL, Stein DT, McGarry JD. Bulk magnetic

susceptibility effects on the assessment of intra- and extramyocellu-

lar lipids in vivo. Magn Reson Med 2002;47:607–610.

146. Stein DT, Szczepaniak LS, Dobbins R, Malloy CR, McGarry JD. Skel-

etal muscle triglyceride stores are increased in insulin resistance.

Diabetes 1997;46(Suppl 1):23A.

147. Krssak M, Petersen KF, Dresner A, DiPietro L, Vogel SM, Rothman

DL, Shulman GI, Roden M. Intramyocellular lipid concentrations

are correlated with insulin sensitivity in humans: a 1H NMR spec-

troscopy study. Diabetologia 1999;42:113–116.

148. Jacob S, Machann J, Rett K, Brechtel K, Volk A, Renn W, Maerker

E, Matthaei S, Schick F, Claussen CD, Haring HU. Association of

increased intramyocellular lipid content with insulin resistance in

lean nonadiabetic offspring of type 2 diabetic subjects. Diabetes

1999;48:1113–1119.

149. Decombaz J, Schmitt B, Ith M, Decarli B, Diem P, Kreis R, Hoppeler

H, Boesch C. Postexercise fat intake repletes intramyocellular lipids

but no faster in trained than in sedentary subjects. Am J Physiol

Regul Integr Comp Physiol 2001;281:R760–R769.

150. Goodpaster BH, He J, Watkins S, Kelley DE. Skeletal muscle lipid

content and insulin resistance: evidence for a paradox in endur-

ance-trained athletes. J Clin Endocrinol Metab 2001;86:5755–5761.

151. Thamer C, Machann J, Bachmann O, Haap M, Dahl D, Wietek B,

Tschritter O, Niess A, Brechtel K, Fritsche A, Claussen C, Jacob S,

Schick F, Haring HU, Stumvoll M. Intramyocellular lipids: anthro-

pometric determinants and relationships with maximal aerobic

capacity and insulin sensitivity. J Clin Endocrinol Metab 2003;88:

1785–1791.

152. Ith M, Huber PM, Egger A, Schmid JP, Kreis R, Christ E, Boesch C.

Standardized protocol for a depletion of intramyocellular lipids

(IMCL). NMR Biomed 2010;23:532–538.

153. Brandejsky V, Kreis R, Boesch C. In vivo proton MR spectroscopy

shows restricted or severely hindered diffusion of intramyocellular

lipids in human skeletal muscle. Magn Reson Med 2012;67:

310–316.

154. Kreis R, Jung B, Rotman S, Slotboom J, Boesch C. Non-invasive ob-

servation of acetyl-group buffering by 1H-MR spectroscopy in exer-

cising human muscle. NMR Biomed 1999;12:471–476.

155. Boesch C. Musculoskeletal spectroscopy. J Magn Reson Imaging

2007;25:321–338.

156. Schick F, Weiss B, Einsele H. Magnetic resonance imaging reveals a

markedly inhomogeneous distribution of marrow cellularity in a

patient with myelodysplasia. Ann Hematol 1995;71:143–146.

157. Schick F, Einsele H, Lutz O, Claussen CD. Lipid selective MR imag-

ing and localized 1H spectroscopy of bone marrow during therapy

of leukemia. Anticancer Res 1996;16:1545–1551.

158. Schick F, Forster J, Einsele H, Weiss B, Lutz O, Claussen CD. Mag-

netization transfer in hemopoietic bone marrow examined by local-

ized proton spectroscopy. Magn Reson Med 1995;34:792–802.

388 Hu et al.