Original Research
T1 Independent, T2* Corrected Chemical Shift Based
Fat–Water Separation With Multi-peak Fat Spectral
Modeling Is an Accurate and Precise Measure of
Hepatic Steatosis
Catherine D.G. Hines, PhD,1 Alex Frydrychowicz, MD,1,2 Gavin Hamilton, PhD,3
Dana L. Tudorascu, PhD,4 Karl K. Vigen, PhD,1 Huanzhou Yu, PhD,5
Charles A. McKenzie, PhD,6 Claude B. Sirlin, MD,3
Jean H. Brittain, PhD,7 and Scott B. Reeder, MD, PhD1,8*
Purpose: To determine the precision and accuracy of he-
patic fat-fraction measured with a chemical shift-based
MRI fat-water separation method, using single-voxel MR
spectroscopy (MRS) as a reference standard.
Materials and Methods: In 42 patients, two repeated
measurements were made using a T1-independent, T
2 -
corrected chemical shift-based fat-water separation
method with multi-peak spectral modeling of fat, and T2-
corrected single voxel MR spectroscopy. Precision was
assessed through calculation of Bland-Altman plots and
concordance correlation intervals. Accuracy was assessed
through linear regression between MRI and MRS. Sensi-
tivity and specificity of MRI fat-fractions for diagnosis of
steatosis using MRS as a reference standard were also
calculated.
Results: Statistical analysis demonstrated excellent
precision of MRI and MRS fat-fractions, indicated by
95% confidence intervals (units of absolute percent)
of [2.66%,2.64%] for single MRI ROI measurements,
[0.81%,0.80%] for averaged MRI ROI, and
[2.70%,2.87%] for single-voxel MRS. Linear regression
between MRI and MRS indicated that the MRI method is
highly accurate. Sensitivity and specificity for detection of
steatosis using averaged MRI ROI were 100% and 94%,
respectively. The relationship between hepatic fat-fraction
and body mass index was examined.
Conclusion: Fat-fraction measured with T1-independent
T
2 -corrected MRI and multi-peak spectral modeling of fat
is a highly precise and accurate method of quantifying
hepatic steatosis.
Key Words: fat quantification; MRI; hepatic steatosis;
nonalcoholic fatty liver disease; MR spectroscopy
J. Magn. Reson. Imaging 2011;33:873–881.
V
C 2011 Wiley-Liss, Inc.
NONALCOHOLIC FATTY LIVER disease (NAFLD) is the
most common cause of chronic liver disease in West-
ern societies with an increasing prevalence that paral-
lels current epidemics of obesity and diabetes (1,2).
NAFLD is considered by many to be the hepatic mani-
festation of the metabolic syndrome, a constellation of
diseases including adult-onset diabetes (type II), hy-
perlipidemia, and obesity (3,4). Individuals with NAFLD
can progress to a more aggressive form of NAFLD
known as nonalcoholic steatohepatitis (NASH), which
is characterized by inflammation, ballooning degenera-
tion and fibrosis, in addition to steatosis (5,6). Many
patients with steatohepatitis progress to end-stage fibro-
sis (cirrhosis), which predisposes patients to hepato-
cellular carcinoma (HCC) and liver failure (7,8).
Intracellular accumulation of triglycerides and fatty
acids (steatosis) is the earliest and hallmark histologi-
cal feature of NAFLD. Definitive diagnosis of NAFLD
and grading of steatosis requires biopsy, which is
1Liver Imaging Research Program, Department of Radiology, University
of Wisconsin, Madison, Wisconsin, USA.
2Department of Diagnostic Radiology and Medical Physics, University
Hospital Freiburg, Freiburg, Germany.
3Liver Imaging Group, Department of Radiology, University of
California, San Diego, California, USA.
4Waisman Laboratory for Brain Imaging and Behavior, University of
Wisconsin, Madison, Wisconsin, USA.
5Applied Science Laboratory, GE Healthcare, Menlo Park, California,
USA.
6Department of Medical Biophysics, University of Western Ontario,
London, Ontario, Canada.
7Applied Science Laboratory, GE Healthcare, Madison, Wisconsin,
USA.
8Departments of Medical Physics, Biomedical Engineering, and
Medicine, University of Wisconsin, Madison, Wisconsin, USA.
Resubmitted to Journal Magnetic Resonance Imaging as an Original
Manuscript on 10 January, 2011
Contract grant sponsor: NIH; Contract grant numbers: R01
DK083380-01, R01 DK088925-01, RC1 EB010384-01; Contract
grant sponsor: Coulter Foundation; University of Wisconsin IEDR.
*Address reprint requests to: S.B.R., Department of Radiology, E1/
374 CSC, University of Wisconsin, 600 Highland Avenue, Madison,
WI 53792-3252. E-mail: sreeder@wisc.edu
Received October 20, 2010; Accepted January 12, 2011.
DOI 10.1002/jmri.22514
View this article online at wileyonlinelibrary.com.
JOURNAL OF MAGNETIC RESONANCE IMAGING 33:873–881 (2011)
CME
V
C 2011 Wiley-Liss, Inc. 873

regarded as the clinical gold standard test and is the
current standard of care. Biopsy, however, is limited
by cost, high sampling variability (9), and other signifi-
cant risks that limit its utility for repeated evaluation
of liver disease. For these reasons, a noninvasive, cost-
effective, and quantitative alternative to biopsy is
needed for accurate quantification of hepatic steatosis.
MRI is highly sensitive to the presence of fat due to
differences in chemical shift between water and fat.
MR spectroscopy (MRS) is considered by many to be
the noninvasive reference standard for quantification
of hepatic fat content (10,11). MRS has both higher
sensitivity and specificity for hepatic fat quantification
compared with ultrasound and computed tomography
(12), indicating that an MR-based technique would be
advantageous for hepatic fat quantification. However,
like biopsy, MRS is prone to sampling error due to the
heterogeneity of steatosis because typically only a sin-
gle voxel is used to assess the entire liver. Alterna-
tively, chemical shift based water–fat separation
methods have demonstrated accurate quantification
of hepatic steatosis by several groups (11,13–17).
Several confounding factors have been identified
that corrupt the ability of MRI to accurately quantify
fat using fat–water separation techniques (18). These
factors must be addressed before the measured fat-
fraction accurately reflects the underlying concentra-
tion of triglycerides. Specific confounding factors
include T1 bias (13,19–21), noise bias (19), the com-
plex NMR spectrum of fat (13,14,22), T
2 decay
(13,23), and phase errors caused by eddy currents
(24). To perform the correction for eddy currents, a
complex image-based fat–water separation including
spectral modeling and T
2 correction is performed first.
Then, a second fit to a magnitude signal model is per-
formed, using the complex estimates of water, fat and
T
2 as the starting conditions. This provides estimates
of water and fat that are free from the effects of phase
shifts from eddy currents. After correction for all con-
founding factors, the measured fat-fraction is equiva-
lent to the proton density fat-fraction (PDFF). PDFF is
an inherent property of the tissue, and is platform
and protocol independent, making it a potentially use-
ful biomarker of liver fat content.
A recently described complex chemical shift-based
fat-water separation method, based on IDEAL (Iterative
Decomposition of water and fat with Echo Asymmetry
and Least squares estimation) has been described for
fat quantification in the liver (14,19,22,23,25). Using a
low flip angle to minimize T1 bias (19), magnitude dis-
crimination to minimize noise bias (19), T
2 correction
(22,23), multi-peak fat spectral modeling (14,22)
including six spectral peaks of fat, and eddy current
correction (24), accurate quantification has been vali-
dated in phantom experiments (26), animal experi-
ments (17) and more recently in in vivo studies (25),
over a wide range of fat-fractions (17,26). These stud-
ies collectively provide validation on the accuracy of
this method.
However, rigorous validation of a biomarker also
requires an understanding of the precision (repeat-
ability) of a method to assess longitudinal changes in
the biomarker. Therefore the primary purpose of this
work is to determine the precision of clinical MRI he-
patic fat quantification when correction for all known
confounding factors has been performed. A secondary
purpose is to reproduce accuracy measurements
reported in previous validation studies (25), using MRS
as the reference standard for hepatic fat-fraction.
PATIENTS AND METHODS
Patients
After obtaining IRB approval and informed consent,
42 patients (22 male, 20 female) referred to the
Department of Radiology for abdominal MRI were
recruited for this study, irrespective of diagnosis,
between September 16, 2009 and August 20, 2010.
Mean age for all patients was 51.0 6 13.1 years
(range, 23–80 years). Thirty-five of these patients had
height and weight recorded in the medical record;
these patients had a mean weight of 82.0 6 25.8 kg
(range, 50.3–207 kg), and a mean body mass index
(BMI) of 24.6 6 5.5 kg/m2 (range, 19.1–45.3 kg/m2).
All patients over the age of 18 were eligible for this
study, and no patients were excluded, unless they
declined to consent to the study.
Imaging Protocol
Imaging was performed on three 1.5 Tesla (T) clinical
scanners (Signa HDx, GE Healthcare, Waukesha, WI)
using an eight-channel phased array cardiac coil or
eight-channel body phased array coil.
For each patient, two repeated measurements of a
quantitative chemical shift-based water–fat separation
MRI method and a single voxel MRS were made to
assess repeatability (precision) of both techniques.
Between each measurement (‘‘Time 1’’ and ‘‘Time 2’’),
the patient was removed from the magnet, and the an-
terior coil elements only removed. The patient was
instructed to sit up and then lie down, after which the
anterior coil was repositioned and the patient placed
back into the magnet without disturbing the posterior
coil. New landmarks and new localizers were acquired,
and all prescanning was repeated, followed by re-
prescription of the MRI and MRS sequences to simu-
late a new, independent exam.
For volumetric MRI fat-fraction imaging, an investi-
gational version of the three-dimensional spoiled gra-
dient echo (SPGR) IDEAL sequence was used (27).
Using fly-back readouts, a total of six echoes were
acquired per TR, and a 2D parallel imaging accelera-
tion method (ARC) (28,29), which had an effective
net acceleration of 2.2, was used to reduce the total
imaging time to 21 s. Imaging parameters for the
MRI sequence were: first TE ¼ 1.3 ms, echo spacing ¼
2.0 ms, TR ¼ 13.7 ms, BW ¼ 6 125 kHz, FOV ¼ 35 
35 cm, slice ¼ 10 mm, 256  128 matrix, flip ¼ 5
to reduce T1 bias (19), and 24 slices in the superior/
inferior direction. Thus, complete liver coverage was
acquired in one breath-hold, with true spatial resolu-
tion of 1.4  2.7  10 mm.
Single voxel breath-held MRS data were acquired to
provide a reference fat-fraction. Spectra were acquired
874 Hines et al.