It is well known that hepatitis C virus (HCV),
can lead to steatotic change in hepatocytes.
In fact,
the proportion of chronic hepatitis C patients with steatosis is considerable,
suggesting a direct role of HCV in the intrahepatic accumulation of triglycerides [1,
2].
In addition,
steatosis has been recognized as one of the factors capable of influencing both liver fibrosis progression and the rate of response to interferon–alpha–based therapy [3].
Currently,
percutaneous liver biopsy remains the reference standard for the diagnosis and grading of hepatic steatosis,
but its clinical application for purposes of screening,
frequent monitoring,
and epidemiologic studies is limited by the significant risk of bleeding,
infection and sampling error [4].
Different non–invasive imaging techniques have been proposed to assess the presence and severity of hepatic steatosis,
including ultrasonography (US),
computed tomography (CT) and magnetic resonance imaging (MRI) [5].
Due to its power of tissue characterization,
MRI has a pivotal role for the detection and quantification of liver fat content.
To this regard,
the main MRI–based tools include fat–suppressed and chemical–shift water–fat separation techniques,
and magnetic resonance spectroscopy (MRS) [6–10].
Currently,
MRS is regarded as the most accurate non–invasive imaging method for assessing fatty liver,
and MRS–derived fat fraction (FF) represents an objective biomarker of this condition,
characterized by a strong correlation with intracellular triglyceride content [11–16].
However,
MRS is not widely available,
is time consuming to perform and analyze,
and samples only a small portion of the liver (i.e.
a volume of about 4 cm3) [10,
12,
15].
Due to the limitations of spectroscopy,
rapid chemical–shift methods are more commonly used in the clinical practice for estimating the liver FF [8,
11,
13,
17–19].
Otherwise,
the application of these ready–available MRI techniques is hindered by the presence of different confounding factors (i.e.
T1 relaxation effects,
T2* decay,
spectral complexity of fat,
noise bias,
B0 inhomogeneity and eddy currents),
that require proper correction [10,
12,
18–20].
More recently,
in order to eliminate all major biases seen with conventional chemical shift–based methods,
newer multiecho [8,
11,
13,
21] and multi–interference [10,
12,
20,
22–24] methods incorporating spectral modeling of fat have been described for the quantification of proton density fat fraction (PDFF).
In addition,
in chronic liver disease,
hepatic steatosis may coexist with various other histological abnormalities,
including fibrosis,
necroinflammatory activity,
and hemosiderin deposition,
which may act as confounding factors on fat quantification by MRI [8].
From a clinical viewpoint,
the issue regarding MRI quantification of hepatic steatosis in patients affected by chronic viral C hepatitis has been addressed in few previous works [25–27].
The purpose of our study was to assess the diagnostic performance of an original T1–independent,
T2*–corrected multiecho MRI technique for the estimation and quantification of liver steatosis in a cohort of patients with chronic viral C hepatitis,
using histology as standard of reference,
and assessing the influence of the other histological abnormalities on MRI PDFF measurements.