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DOI: 10.1148/radiol.2392050505
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(Radiology 2006;239:425-437.)
© RSNA, 2006

Gastrointestinal Imaging

Liver Fibrosis: Noninvasive Diagnosis with Double Contrast Material–enhanced MR Imaging1

Diego A. Aguirre, MD, Cynthia A. Behling, MD, PhD, Elliot Alpert, MD, Tarek I. Hassanein, MD and Claude B. Sirlin, MD

1 From the Departments of Radiology (D.A.A., C.B.S.), Pathology (C.A.B.), and Medicine (E.A., T.I.H.), University of California, San Diego Medical Center, 200 W Arbor Dr, San Diego, CA 92103-8756; and Department of Radiology, Fundacion Santa Fe de Bogota, University Hospital, Bogota, Colombia (D.A.A.). Received March 26, 2005; revision requested June 2; revision received June 4; final version accepted July 1. Address correspondence to C.B.S. (e-mail: csirlin{at}ucsd.edu).


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCE IN KNOWLEDGE
 References
 
Purpose: To retrospectively evaluate the accuracy of double contrast material–enhanced (hereafter double-enhanced) magnetic resonance (MR) imaging depiction of hepatic fibrosis, with histopathologic analysis findings as the reference standard.

Materials and Methods: The institutional review board approved this HIPAA-compliant study and waived the requirement for informed consent. One hundred one patients (58 men, 43 women; mean age ± standard deviation, 52 years ± 10) who underwent double-enhanced MR imaging with superparamagnetic iron oxide (SPIO)-enhanced and double-enhanced spoiled gradient-echo (SPGR) sequences between 2001 and 2004 and had a reliable reference standard for the diagnosis of liver fibrosis were included. Two blinded MR radiologists retrospectively scored qualitative (reticulation, nodularity, and total scores) and quantitative (contrast-to-noise ratio between hyperintense and hypointense liver regions, coefficient of variation, and noise-corrected coefficient of variation) liver texture features on MR images in consensus. The image scores for patients with advanced (METAVIR fibrosis score ≥ 3) versus those for patients with mild (METAVIR score ≤ 2) fibrosis were compared, and receiver operating characteristic curves were determined. Diagnostic performance values were calculated at the optimal operating point. Mann-Whitney U and unpaired Student t tests were performed.

Results: Qualitative and quantitative image scores were significantly higher for patients with METAVIR fibrosis scores of 3 or higher than for those with scores of 2 or lower (P < .001); on SPIO-enhanced SPGR images, differences increased with increasing echo time. Diagnostic performance for detection of grade 3 or more severe fibrosis was better with the double-enhanced sequence than with the SPIO-enhanced sequences, and qualitative scores had higher diagnostic performance than quantitative scores. The sensitivity, specificity, and accuracy of qualitative scores on double-enhanced SPGR images were higher than 90%.

Conclusion: Advanced hepatic fibrosis can be detected by using double-enhanced MR imaging. Although diagnostic performance depended on the sequence and scoring system used, sensitivity, specificity, and accuracy values higher than 90% were achievable.

© RSNA, 2006


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCE IN KNOWLEDGE
 References
 
Hepatic fibrosis is an important cause of morbidity, mortality, and increasing health care costs (1–4). The detection and grading of fibrosis currently require biopsy, which is expensive, has inherent risks (5–10), and may lead to underestimation of disease severity due to sampling error (11–16). Noninvasive imaging of liver fibrosis would reduce biopsy-related risks and costs and thus potentially eliminate sampling errors and enable global liver assessment.

Historically, imaging evaluation of hepatic fibrosis has been limited to the assessment of cirrhosis-related complications in patients with known liver disease. Although the presence of cirrhosis can be confirmed on the basis of liver contour abnormalities and portal hypertension stigmata by using ultrasonography (US), computed tomography, and magnetic resonance (MR) imaging, these findings are insensitive in the detection of early cirrhosis and milder fibrosis (17–20).

The possibility of noninvasively diagnosing cirrhosis on the basis of the hepatic texture alterations seen on contrast material–enhanced MR images has been suggested (21–23). After injection of superparamagnetic iron oxides (SPIOs) (21,22) or gadolinium chelates (23), hyperintense reticulations, which are postulated to represent septal fibrosis, can be observed in the cirrhotic liver. It is known that after SPIOs are intravenously infused, they accumulate within liver reticuloendothelial cells (24) and cause T2* shortening, which reduces liver signal intensity (21,25,26). In patients with fibrosis, SPIOs accumulate and cause T2* shortening preferentially in the spared liver parenchyma, and this leads to fibrotic bands being relatively hyperintense. Also, it is known that fibrotic tissue has a relatively large extracellular space. The delayed distribution of extracellular gadolinium chelates in fibrotic tissue is well documented, and delayed T1 shortening and delayed enhancement of hepatic septal fibrosis signal intensity are expected (23).

For these reasons, it may be possible to diagnose cirrhosis and grade liver fibrosis on SPIO- and/or gadolinium-enhanced MR images on the basis of hepatic texture alterations. Moreover, because SPIOs and gadolinium chelates have potentially synergistic mechanisms, a double contrast material–enhanced (hereafter referred to as double-enhanced) MR imaging protocol in which SPIOs and gadolinium chelates are administered sequentially may be superior to a single contrast material–enhanced MR imaging protocol for fibrosis detection. To our knowledge, no study in which both SPIOs and gadolinium chelates were used in the same patient to detect hepatic fibrosis had been performed before this investigation. Thus, the purpose of our study was to retrospectively evaluate the accuracy of double-enhanced MR imaging depiction of hepatic fibrosis, with histopathologic analysis findings as the reference standard.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 ADVANCE IN KNOWLEDGE
 References
 
Patients
This investigation was a retrospective, Health Insurance Portability and Accountability Act–compliant, cross-sectional study performed at the University of California, San Diego Liver Center, a tertiary liver center. The institutional review board of the University of California, San Diego Medical Center approved the study and waived the requirement for informed consent for our patient data review. The study sample consisted of consecutive patients who had undergone double-enhanced MR imaging between April 2001 and January 2004 and had histopathologic findings as the reference standard for the diagnosis of liver fibrosis. The data on patients who had undergone incomplete double-enhanced MR examinations and/or had no reference standard findings were excluded. At our institution, double-enhanced MR imaging is the standard clinical protocol for MR imaging of the liver.

Collection of Patient Information
An MR research fellow (D.A.A., 6 years experience) retrospectively reviewed radiology, hepatology, and pathology records to identify patients who met the study inclusion criteria. The information collected included demographic data; dates of and indications for double-enhanced MR imaging; liver disease history, cause, and risk factors; dates of liver biopsy and/or transplantation; and liver pathology, hepatitis viral serology, and serum liver function test results.

Reference Standard and Control Subjects
The reference standard was based on histopathologic findings (from percutaneous biopsy and/or liver explantation). Because the sample of patients with normal liver histopathologic findings was small, we included as control subjects a consecutive cohort of patients with clinical examination findings as the reference standard.

Histopathologic analyses.—One hepatologist (T.I.H.) with 15 years experience performed all the liver biopsies. The right lobe of the liver was sampled by using a 16-gauge needle with US guidance. A pathologist (C.A.B.) with 12 years experience judged all specimens to be diagnostically adequate. The explanted livers were cut into 10-mm slices. Representative samples were submitted for histopathologic analysis. The same pathologist graded the extent of fibrosis found in the histologic specimens during a session separate from the image interpretations—and while blinded to these results—by using the METAVIR scoring system (27): Score F0 indicated no fibrosis, F1 indicated portal fibrosis without septa, F2 indicated portal fibrosis with rare septa, F3 indicated numerous septa without cirrhosis, and F4 indicated cirrhosis.

To be considered a reliable reference standard, the histopathologic analysis had to be performed within 3 months before or after the index double-enhanced MR examination for patients with F3 or less severe disease and any time before or within 3 months after the index double-enhanced MR examination for patients with F4 disease. Histopathologic data obtained outside of these time frames were considered unreliable (frequency of such data not recorded).

Clinical reference standard and control subjects.—Consecutive patients who met the following criteria were included as control subjects (ie, with clinical F0): Double-enhanced MR imaging was performed during the study period for indications other than hepatocellular carcinoma surveillance or diffuse liver disease assessment; there was no documentation of active or past liver disease; there were no risk factors for liver disease (ie, consumption of two or more alcoholic drinks daily, viral hepatitis, and/or drug abuse); liver function test results obtained within 3 months of the index double-enhanced MR examination were normal; and viral serology test results (if available) were negative.

MR Technique
The MR imaging protocols used, including contrast agent formulations and doses, are summarized in Figure 1. Patients were positioned supine, with anterior and posterior phased-array coils centered over the liver, and imaged at 1.5 T (Magnetom Symphony; Siemens Medical Systems, Erlangen, Germany) 30 minutes after completion of the SPIO administration. Transverse breath-hold MR images were obtained.


Figure 1
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  		Figure 1: Outline of MR imaging protocols used to perform double-enhanced (DE) MR imaging of the liver. SPIO (ferumoxides, Feridex; Berlex, Wayne, NJ) particles were diluted and infused intravenously in the preparation room outside of the MR magnet. Thirty minutes later, SPIO-enhanced images (sequences 1–4) were acquired at 1.5 T. A rectangular field of view (range 20–32 x 34–42 cm) was optimized for each patient's body habitus and held constant for all sequences. Three-dimensional (3D) T1-weighted (T1w) spoiled gradient-echo (SPGR [SGE]) images were acquired before and dynamically after bolus injection of gadolinium-based contrast material (gadodiamide, Optimark; Mallinckrodt, St Louis, Mo) but were not analyzed. Delayed double-enhanced images (sequence 5) were acquired 180 seconds after the gadodiamide injection. BW = bandwidth; DE-4.76 2D SGE = double-enhanced two-dimensional SPGR with 4.76-msec echo time (TE); ETL = echo train length; FA = flip angle; SPIO-T2 ETSE = SPIO-enhanced T2-weighted echo train spin echo; SPIO-2.65, SPIO-4.76, and SPIO-6.6 = SPIO-enhanced two-dimensional SPGR with TE of 2.65, 4.76, or 6.60 msec, respectively; TR = repetition time.

 
The double-enhanced MR examination was considered complete if all five sequences (labeled 1–5) described in Figure 1 were obtained. The two-dimensional SPIO-enhanced SPGR sequences (sequences 2–4) were designed to enable qualitative assessment of hepatic fat and T2* decay. In 2003, we added SPGR sequences with TEs longer than 6.60 msec to accentuate the T2* effects; these sequences were not performed in all patients and were not analyzed. The examinations took approximately 30 minutes from the time the patient was entered into the magnet to the time he or she was removed from the magnet (exact times not recorded). Minor reactions occurred occasionally (frequency not recorded). Anecdotally, by far the most common reaction was musculoskeletal pain during SPIO infusion, which on every occasion resolved with the temporary discontinuation of the infusion. No patient had a severe reaction or a reaction that required termination of the SPIO infusion.

Review of MR Images
Two MR radiologists (C.B.S., a body MR attending physician with 9 years experience, and D.A.A., the MR research fellow) retrospectively reviewed, in consensus and in random order, all MR images on two side-by-side 2048 x 2560-pixel-resolution gray-scale picture archiving and communicating system monitors (Agfa Healthcare IMPAX; Agfa, Ridgefield Park, NJ). The radiologists were blinded to the demographic, clinical, laboratory, and pathology data at the time of image review, which was performed a minimum of 4 weeks after patient data collection. To maintain blinding, demographic information was not displayed during the image review sessions. The images obtained with the five sequences were displayed simultaneously on the two monitors. Each case was reviewed during two reading sessions performed several weeks apart.

During the first reading session, the liver surface contour was judged to be abnormal (nodular) or normal (smooth) and portal hypertension stigmata (ie, ascites, varices, and/or splenomegaly) were judged to be present or absent. During the second session, the following liver texture features were analyzed:

Qualitative Features
Reticulation score.—The presence of 1–3-mm areas of reticular hyperintensity at each sequence was scored by using a five-point ordinal scale ranging from 0 (reticulations not visible on any section) to 4 (diffuse reticulations obvious on all sections [Fig 2]).


Figure 2
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  		Figure 2a: (a–c) Transverse two-dimensional SPIO-enhanced SPGR MR images obtained with TEs of (a) 2.65 msec, (b) 4.76 msec, and (c) 6.60 msec; (d) transverse T2-weighted echo train spin-echo MR image; and (e) double-enhanced two-dimensional SPGR MR image in 46-year-old man with METAVIR score of F4. Images show diffuse hyperintense reticulations throughout the liver parenchyma. On the SPGR images, reticulations become progressively more visible as TE increases. Visibility of the reticulations in d is intermediate between that in b and c. Highest visibility is achieved in e. Note the aortic ghost artifact (arrow) on the SPGR images. The parameters used to obtain all images are shown in Figure 1.

 

Figure 2
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  		Figure 2b: (a–c) Transverse two-dimensional SPIO-enhanced SPGR MR images obtained with TEs of (a) 2.65 msec, (b) 4.76 msec, and (c) 6.60 msec; (d) transverse T2-weighted echo train spin-echo MR image; and (e) double-enhanced two-dimensional SPGR MR image in 46-year-old man with METAVIR score of F4. Images show diffuse hyperintense reticulations throughout the liver parenchyma. On the SPGR images, reticulations become progressively more visible as TE increases. Visibility of the reticulations in d is intermediate between that in b and c. Highest visibility is achieved in e. Note the aortic ghost artifact (arrow) on the SPGR images. The parameters used to obtain all images are shown in Figure 1.

 

Figure 2
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  		Figure 2c: (a–c) Transverse two-dimensional SPIO-enhanced SPGR MR images obtained with TEs of (a) 2.65 msec, (b) 4.76 msec, and (c) 6.60 msec; (d) transverse T2-weighted echo train spin-echo MR image; and (e) double-enhanced two-dimensional SPGR MR image in 46-year-old man with METAVIR score of F4. Images show diffuse hyperintense reticulations throughout the liver parenchyma. On the SPGR images, reticulations become progressively more visible as TE increases. Visibility of the reticulations in d is intermediate between that in b and c. Highest visibility is achieved in e. Note the aortic ghost artifact (arrow) on the SPGR images. The parameters used to obtain all images are shown in Figure 1.

 

Figure 2
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  		Figure 2d: (a–c) Transverse two-dimensional SPIO-enhanced SPGR MR images obtained with TEs of (a) 2.65 msec, (b) 4.76 msec, and (c) 6.60 msec; (d) transverse T2-weighted echo train spin-echo MR image; and (e) double-enhanced two-dimensional SPGR MR image in 46-year-old man with METAVIR score of F4. Images show diffuse hyperintense reticulations throughout the liver parenchyma. On the SPGR images, reticulations become progressively more visible as TE increases. Visibility of the reticulations in d is intermediate between that in b and c. Highest visibility is achieved in e. Note the aortic ghost artifact (arrow) on the SPGR images. The parameters used to obtain all images are shown in Figure 1.

 

Figure 2
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  		Figure 2e: (a–c) Transverse two-dimensional SPIO-enhanced SPGR MR images obtained with TEs of (a) 2.65 msec, (b) 4.76 msec, and (c) 6.60 msec; (d) transverse T2-weighted echo train spin-echo MR image; and (e) double-enhanced two-dimensional SPGR MR image in 46-year-old man with METAVIR score of F4. Images show diffuse hyperintense reticulations throughout the liver parenchyma. On the SPGR images, reticulations become progressively more visible as TE increases. Visibility of the reticulations in d is intermediate between that in b and c. Highest visibility is achieved in e. Note the aortic ghost artifact (arrow) on the SPGR images. The parameters used to obtain all images are shown in Figure 1.

 
Nodularity score.—The presence of subcentimeter hypointense nodules at each sequence was scored by using a five-point ordinal scale ranging from 0 (nodules not visible on any section) to 4 (innumerable nodules obvious on all sections [Fig 3]).


Figure 3
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  		Figure 3a: Transverse MR images of liver in 39-year-old woman with METAVIR score of F4. (a–c) SPIO-enhanced two-dimensional SPGR images obtained with TEs of (a) 2.65 msec, (b) 4.76 msec, and (c) 6.60 msec show innumerable hypointense nodules (*) throughout liver parenchyma. Nodules are not clearly seen on 2.65-msec-TE image but become more visible with increasing TE. (d) Double-enhanced SPGR image obtained at same level shows hyperintense reticulations (arrows) in addition to hypointense nodules. Findings are thought to represent regenerating nodules surrounded by fibrotic septal tissue. The parameters used to obtain all images are shown in Figure 1.

 

Figure 3
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  		Figure 3b: Transverse MR images of liver in 39-year-old woman with METAVIR score of F4. (a–c) SPIO-enhanced two-dimensional SPGR images obtained with TEs of (a) 2.65 msec, (b) 4.76 msec, and (c) 6.60 msec show innumerable hypointense nodules (*) throughout liver parenchyma. Nodules are not clearly seen on 2.65-msec-TE image but become more visible with increasing TE. (d) Double-enhanced SPGR image obtained at same level shows hyperintense reticulations (arrows) in addition to hypointense nodules. Findings are thought to represent regenerating nodules surrounded by fibrotic septal tissue. The parameters used to obtain all images are shown in Figure 1.

 

Figure 3
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  		Figure 3c: Transverse MR images of liver in 39-year-old woman with METAVIR score of F4. (a–c) SPIO-enhanced two-dimensional SPGR images obtained with TEs of (a) 2.65 msec, (b) 4.76 msec, and (c) 6.60 msec show innumerable hypointense nodules (*) throughout liver parenchyma. Nodules are not clearly seen on 2.65-msec-TE image but become more visible with increasing TE. (d) Double-enhanced SPGR image obtained at same level shows hyperintense reticulations (arrows) in addition to hypointense nodules. Findings are thought to represent regenerating nodules surrounded by fibrotic septal tissue. The parameters used to obtain all images are shown in Figure 1.

 

Figure 3
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  		Figure 3d: Transverse MR images of liver in 39-year-old woman with METAVIR score of F4. (a–c) SPIO-enhanced two-dimensional SPGR images obtained with TEs of (a) 2.65 msec, (b) 4.76 msec, and (c) 6.60 msec show innumerable hypointense nodules (*) throughout liver parenchyma. Nodules are not clearly seen on 2.65-msec-TE image but become more visible with increasing TE. (d) Double-enhanced SPGR image obtained at same level shows hyperintense reticulations (arrows) in addition to hypointense nodules. Findings are thought to represent regenerating nodules surrounded by fibrotic septal tissue. The parameters used to obtain all images are shown in Figure 1.

 
Total score.—The nodularity and reticulation scores on each sequence were summed such that a nine-point ordinal scale (0–8) was generated.

T2* decay uniformity.—Liver T2* decay was judged to be uniform if the signal intensity loss on SPIO-enhanced SPGR images was homogeneous as the TE increased and to be nonuniform if the signal intensity loss was heterogeneous. The patterns of nonuniform T2* decay were divided into two groups: perivascular (distinctly shorter T2* decay in the liver parenchyma immediately surrounding visible intrahepatic vessels [Fig 4]) and nonperivascular.


Figure 4
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  		Figure 4a: Transverse two-dimensional SPIO-enhanced SPGR MR images of liver obtained with TEs of (a) 2.65 msec, (b) 4.76 msec, and (c) 6.60 msec in 44-year-old woman with METAVIR score of F4 show progressive signal intensity loss as TE increases; the signal intensity loss is most pronounced in the hepatic tissues surrounding hepatic blood vessels (arrows). Perivascular fat infiltration is unlikely because the signal intensity loss does not oscillate between the in-phase (b) and opposed-phase (a) images. The parameters used to obtain all images are shown in Figure 1.

 

Figure 4
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  		Figure 4b: Transverse two-dimensional SPIO-enhanced SPGR MR images of liver obtained with TEs of (a) 2.65 msec, (b) 4.76 msec, and (c) 6.60 msec in 44-year-old woman with METAVIR score of F4 show progressive signal intensity loss as TE increases; the signal intensity loss is most pronounced in the hepatic tissues surrounding hepatic blood vessels (arrows). Perivascular fat infiltration is unlikely because the signal intensity loss does not oscillate between the in-phase (b) and opposed-phase (a) images. The parameters used to obtain all images are shown in Figure 1.

 

Figure 4
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  		Figure 4c: Transverse two-dimensional SPIO-enhanced SPGR MR images of liver obtained with TEs of (a) 2.65 msec, (b) 4.76 msec, and (c) 6.60 msec in 44-year-old woman with METAVIR score of F4 show progressive signal intensity loss as TE increases; the signal intensity loss is most pronounced in the hepatic tissues surrounding hepatic blood vessels (arrows). Perivascular fat infiltration is unlikely because the signal intensity loss does not oscillate between the in-phase (b) and opposed-phase (a) images. The parameters used to obtain all images are shown in Figure 1.

 
Quantitative Features
A representative section of the liver that was subjectively coregistered at each sequence was selected. Three operator-defined regions of interest were placed in the liver on each section at similar distances from the phased-array coils: in the most hyperintense zone, in the most hypointense zone, and in a representative (standard) zone. Liver regions of interest were chosen to avoid fat, visible blood vessels, prominent artifacts, and sharp changes in signal intensity. A fourth region of interest was placed in the air to the right of the abdominal wall on the same section. Corresponding regions of interest at different sequences were similar in size (±10% in pixel number) and shape and were registered as closely as possible at all sequences.

For each region of interest, the mean signal intensity (± the standard deviation) was calculated by using the picture archiving and communicating system software. The four regions of interest were used to generate quantitative measurements of liver texture heterogeneity—specifically, contrast-to-noise ratios (CNRs), coefficients of variation (CVs), and corrected CVs.

The CNR between the most hyperintense and the most hypointense regions of the liver on the representative section was calculated as follows: CNR = (SIhype – SIhypo)/SDair, where SIhyper is the mean signal intensity of the most hyperintense region of the liver, SIhypo is the mean signal intensity of the most hypointense region of the liver, and SDair is the standard deviation of the mean air signal intensity.

The CV for the standard liver region of interest was calculated as follows: CV = SDliver/SIliver, where SDliver is the standard deviation of the mean liver parenchyma signal intensity and SIliver is the mean signal intensity of the liver parenchyma. The CV was used as a measure of regional liver texture heterogeneity. The rationale is that the fibrotic liver has a more heterogeneous texture (hyperintense reticulations against a dark liver background) than does the homogeneous normal liver. Compared with the mean, the CV is a dimensionless measure of relative data dispersion.

Because image noise contributed to the variance in liver signal intensity, we also calculated a corrected CV (CVcorr), which we believe is a more meaningful measure of liver texture heterogeneity, by subtracting the standard deviation of the mean air signal intensity from the standard deviation of the mean liver parenchyma signal intensity in the numerator: CVcorr = (SDliver – SDair)/SIliver.

Statistical Analyses
The clinical and pathology data were analyzed descriptively. Image scores were correlated with METAVIR scores for each sequence independently by using Spearman rank correlation analysis. For the other statistical tests, the five-point METAVIR scale was dichotomized into F2 or less severe and F3 or more severe disease groups. The demographic data and imaging scores for the patients with F2 or less severe disease (F2 or lower group) were compared with those for the patients with F3 or more severe disease (F3 or higher group) by using the Fisher exact test for frequency data, the Mann-Whitney U test for ordinal data, and the unpaired Student t test for normally distributed continuous data. Receiver operating characteristic curves for comparisons between these two groups were generated for image scores. Areas under the receiver operating characteristic curve (Az values) were obtained and compared in a pairwise manner (28). Optimal operating points were calculated (29), and diagnostic performance was assessed. All statistical tests were two tailed at an {alpha} of .05 and performed by using computer software (SPSS for Windows, version 12.0.1; SPSS, Chicago, Ill). We did not correct for multiple comparisons.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 ADVANCE IN KNOWLEDGE
 References
 
Patients
During the study period, 369 patients underwent double-enhanced MR imaging: 101 (27%) of them had a reliable reference standard for the diagnosis of fibrosis (histopathologic analysis for 89 patients, clinical examination for 12 patients), and their data were included in the study. The F2 or lower and F3 or higher groups had similar mean ages (P = .91) (Table 1). The F2 or lower group comprised a smaller percentage of men than did the F3 or higher group (45% vs 62%), but the difference was not significant (P = .12). The most common causes of liver disease were hepatitis C, alcohol consumption, and hepatitis C combined with alcohol consumption (Table 2). The 12 patients with clinical F0 disease had no risk factors. Among the patients with F4 disease, the proportion with clinically obvious versus the proportion with clinically occult disease could not be determined retrospectively. Of the 89 patients with histopathologic findings, 45 had iron-staining results recorded in the pathology report: 26 (58%) had no detectable iron at histologic analysis, 18 (40%) had minimal iron, and one (2%) had moderate iron.


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  		Table 1. Distribution of Patients and Truth Standards

 

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  		Table 2. Causes of Liver Disease

 
Correlation with METAVIR Scores
The correlation between liver texture features (on MR images) and METAVIR scores was higher with use of qualitative scores than with use of quantitative scores (Table 3). For each of the six scored features (reticulation, nodularity, total score, CNR, CV, and corrected CV), the two sequences with the highest correlation were SPIO-enhanced SPGR with a 6.60-msec TE and double-enhanced SPGR with a 4.76-msec TE. The correlation increased with increasing TE at the SPIO-enhanced SPGR sequences. Double-enhanced MR imaging with a 4.76-msec TE yielded a higher correlation than did SPIO-enhanced SPGR MR imaging with a 4.76-msec TE. Correlations were higher for corrected CV scores than for CV scores at all sequences except T2-weighted SPIO-enhanced spin echo; with this sequence, correlations were particularly weak for both CV and corrected CV. The correlation was also weak for the CNR score at SPIO-enhanced SPGR MR imaging with a 2.65-msec TE.


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  		Table 3. Spearman Rank Correlations between MR Imaging Texture Features and METAVIR Scores

 
Comparison of F2 or Lower and F3 or Higher Groups
For each sequence, median qualitative (Fig 5) and mean quantitative (Fig 6) liver texture scores were higher for the patients with F3 or more severe disease than for those with F2 or less severe disease. In pairwise comparisons, differences in qualitative scores between the F2 or lower and F3 or higher groups were significant at all five sequences (P < .001). Differences in quantitative scores were significant at most sequences (Fig 6). Differences in scores tended to increase with increasing TE at the SPIO-enhanced SPGR sequences. Differences in scores at double-enhanced SPGR MR imaging with a 4.76-msec TE were higher than those at SPIO-enhanced SPGR MR imaging with a 4.76-msec TE. Also, differences in corrected CV scores were greater than differences in CV scores.


Figure 5
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  		Figure 5a: Box plots show median (a) reticulation, (b) nodularity, and (c) total qualitative scores per sequence per fibrosis group. Scores were higher for the F3 or higher group (dark gray boxes) than for the F2 or lower group (light gray boxes) at all sequences (P < .001). Differences between the groups increased with increasing TE at the two-dimensional SPGR sequences (SPIO-2.6, SPIO-4.7, SPIO-6.6). For all scores, the difference was higher at the double-enhanced (DE) sequence than at the SPIO-enhanced sequences performed with the same TE. Thick dark lines represent median values. Boxes represent interquartile ranges. Error bars represent scores of up to 1.5 box lengths above or below the upper or lower edge of the box. Small circles and squares are outliers. Total score refers to sum of reticulation and nodularity scores. Each sequence is described in Figure 1.

 

Figure 5
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  		Figure 5b: Box plots show median (a) reticulation, (b) nodularity, and (c) total qualitative scores per sequence per fibrosis group. Scores were higher for the F3 or higher group (dark gray boxes) than for the F2 or lower group (light gray boxes) at all sequences (P < .001). Differences between the groups increased with increasing TE at the two-dimensional SPGR sequences (SPIO-2.6, SPIO-4.7, SPIO-6.6). For all scores, the difference was higher at the double-enhanced (DE) sequence than at the SPIO-enhanced sequences performed with the same TE. Thick dark lines represent median values. Boxes represent interquartile ranges. Error bars represent scores of up to 1.5 box lengths above or below the upper or lower edge of the box. Small circles and squares are outliers. Total score refers to sum of reticulation and nodularity scores. Each sequence is described in Figure 1.

 

Figure 5
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  		Figure 5c: Box plots show median (a) reticulation, (b) nodularity, and (c) total qualitative scores per sequence per fibrosis group. Scores were higher for the F3 or higher group (dark gray boxes) than for the F2 or lower group (light gray boxes) at all sequences (P < .001). Differences between the groups increased with increasing TE at the two-dimensional SPGR sequences (SPIO-2.6, SPIO-4.7, SPIO-6.6). For all scores, the difference was higher at the double-enhanced (DE) sequence than at the SPIO-enhanced sequences performed with the same TE. Thick dark lines represent median values. Boxes represent interquartile ranges. Error bars represent scores of up to 1.5 box lengths above or below the upper or lower edge of the box. Small circles and squares are outliers. Total score refers to sum of reticulation and nodularity scores. Each sequence is described in Figure 1.

 

Figure 6
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  		Figure 6a: Graphs illustrate mean (±95% confidence intervals) (a) CNR, (b) CV, and (c) corrected CV scores for F2 or lower (F≤2) versus F3 or higher (F≥3) groups with each pulse sequence. Scores were higher for the F3 or higher group than for the F2 or lower group at all sequences. Differences between the two groups increased with increasing TE at the two-dimensional SPGR sequences, and differences in all scores were higher at double-enhanced (DE) MR imaging than at SPIO-enhanced MR imaging performed with the same TE. Each sequence is described in Figure 1.

 

Figure 6
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  		Figure 6b: Graphs illustrate mean (±95% confidence intervals) (a) CNR, (b) CV, and (c) corrected CV scores for F2 or lower (F≤2) versus F3 or higher (F≥3) groups with each pulse sequence. Scores were higher for the F3 or higher group than for the F2 or lower group at all sequences. Differences between the two groups increased with increasing TE at the two-dimensional SPGR sequences, and differences in all scores were higher at double-enhanced (DE) MR imaging than at SPIO-enhanced MR imaging performed with the same TE. Each sequence is described in Figure 1.

 

Figure 6
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  		Figure 6c: Graphs illustrate mean (±95% confidence intervals) (a) CNR, (b) CV, and (c) corrected CV scores for F2 or lower (F≤2) versus F3 or higher (F≥3) groups with each pulse sequence. Scores were higher for the F3 or higher group than for the F2 or lower group at all sequences. Differences between the two groups increased with increasing TE at the two-dimensional SPGR sequences, and differences in all scores were higher at double-enhanced (DE) MR imaging than at SPIO-enhanced MR imaging performed with the same TE. Each sequence is described in Figure 1.

 
T2* decay was nonuniform in 54% of the 72 patients with F3 or more severe disease and in 10% of the 29 patients with F2 or less severe disease (P < .001) (Table 4). Liver contour was abnormal in 62 (86%) patients in the F3 or higher group and in no patients in the F2 or lower group. Portal hypertension was evident in 61 (85%) patients in the F3 or higher group and absent in 20 (69%) patients in the F2 or lower group.


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  		Table 4. Uniformity of T2* Decay

 
Receiver Operating Characteristic Analysis
Az values ranged from 0.396 to 0.980, depending on the sequence and the image score (Table 5). In general, Az values were higher for the qualitative scores than for the quantitative scores. The total score consistently had the highest Az value. CNRs tended to have higher Az values than did corrected CVs, which consistently had higher Az values than did CVs (Tables 5 and 6).


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  		Table 5. Analysis of Receiver Operating Characteristic Curves

 

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  		Table 6. Pairwise Comparisons of Az Values for MR Imaging Sequence Scores

 
For all six scored features, Az values increased with increasing TE at SPIO-enhanced SPGR MR imaging and were higher at double-enhanced SPGR imaging with a 4.76-msec TE than at SPIO-enhanced SPGR imaging with a 4.76-msec TE (Tables 5 and 7).


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  		Table 7. Pairwise Comparisons of Az Values for MR Imaging Sequence Scores

 
Diagnostic Performance
At the optimal operating point, sensitivity ranged from 68% to 96%; specificity, from 21% to 97%; and accuracy, from 72% to 93%, depending on the sequence and the imaging score (Table 8). For all three scores (total, CNR, and corrected CV), the highest and second highest accuracies were achieved with double-enhanced 4.76-msec-TE SPGR MR imaging and SPIO-enhanced 6.60-msec-TE SPGR MR imaging, respectively. Diagnostic accuracy increased with increasing TE at SPIO-enhanced SPGR MR imaging (P = .02) and was higher at double-enhanced 4.76-msec-TE SPGR MR imaging than at SPIO-enhanced 4.76-msec-TE SPGR MR imaging (P = .008). Total scores were consistently more accurate (mean, 0.851) than CNR (mean, 0.786) and corrected CV (mean 0.776) scores. With use of the SPIO-enhanced 6.60-msec-TE and double-enhanced 4.76-msec-TE SPGR sequences, the total score yielded sensitivity, specificity, accuracy, and positive predictive values higher than 91% and negative predictive values higher than 82%. The diagnostic performances of liver surface contour and portal hypertension stigmata also are shown in Table 8. Nonuniform T2* decay had low sensitivity (54%) but high specificity (90%) in the F3 or higher group. The positive predictive values of nonuniform decay and a perivascular pattern were 93% and 95%, respectively.


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  		Table 8. Diagnostic Performance Values

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
ADVANCE IN KNOWLEDGE
 References
 
Despite having multiple limitations, biopsy remains the clinical reference standard for the detection of liver fibrosis (1,30,31). Serum biomarkers for liver fibrosis (1,32–34) have been described, but their clinical effectiveness has not been proved.

The development of noninvasive imaging methods to detect and grade fibrosis throughout the entire liver would represent a major advance in the management of liver disease. These capabilities would enable serial follow-up of patients, documentation of temporal changes, and assessment of therapy response; provide direct benefits to patients; and serve as a powerful research tool for therapy development.

Cross-sectional imaging findings of cirrhosis have been described; most are based on morphologic changes in the liver (31,35–37) or secondary signs of portal hypertension (18,19,36). These findings have limited utility for the detection of early fibrosis and the grading of advanced fibrosis. Some investigators have proposed that it may be possible to diagnose and grade fibrosis with MR imaging by measuring alterations in hepatic blood flow (17) or water diffusion (38).

A fundamentally different approach is to directly visualize fibrotic tissue. In previous works, fibrosis has been depicted as hyperintense reticulations against a hypointense liver background after the administration of gadolinium-based contrast material (23) or SPIOs (22). It has also been suggested that texture feature analysis of MR images could be used to differentiate cirrhotic from normal livers (39).

Herein, we provide proof of the concept that use of a double-enhanced MR imaging protocol enables accurate differentiation between advanced and less severe hepatic fibrosis; although diagnostic performance depended on the sequence and the scoring system, sensitivity, specificity, and accuracy values higher than 90% were achievable. Combining texture, surface, and secondary imaging features would probably further improve diagnostic performance, although this was not tested in this study.

Accuracy tended to be greater at SPIO-enhanced SPGR MR imaging than at T2-weighted echo train spin-echo MR imaging and improved with increasing TE at SPIO-enhanced SPGR imaging. Our observation that accuracy improved as T2* weighting increased was expected; it is known that functional reticuloendothelial cells are present in spared liver but are diminished or dysfunctional in fibrotic tissue (25,40,41). Accuracy was also higher on the double-enhanced compared with SPIO-enhanced SPGR images obtained by using the same TE. This result is consistent with previous observations that gadolinium causes delayed T1 shortening of liver fibrosis (23). Considered together, our results help to corroborate our central hypothesis that gadolinium chelates and SPIOs have synergistic effects in the demonstration of liver fibrosis—namely, SPIOs darken spared liver, while gadolinium chelates brighten fibrotic reticulations.

The accuracy of the qualitative scoring methods was consistently higher than the accuracy of the quantitative scoring methods. One explanation is that we based our quantitative analysis on simple texture measurements that can be performed at virtually any picture archiving and communicating system workstation. More sophisticated texture features (39) can be assessed on off-line computers and may facilitate better performance. Although the readers assessed the liver surface and portal hypertension during a session separate from the liver texture analysis, the presence of ascites, splenomegaly, abdominal varices, and/or surface nodularity may have influenced the texture scores for some patients. To reduce this possible bias in future work, we will assess the liver texture on representative intrahepatic regions of interest that do not include liver surface and extrahepatic tissues.

To our knowledge, the reticulation and nodularity scores described herein have not been used previously. Although internal nodules and surface nodularity are well-described imaging features of the cirrhotic liver, a scoring system based on internal nodularity had not been devised previously. Lucidarme et al (22) described fibrotic reticulations in the SPIO-enhanced cirrhotic liver but did not create a reticulation scoring system to grade the fibrosis.

Nonuniform T2* decay on SPIO-enhanced SPGR MR images was a reliable predictor (93% positive predictive value) of advanced fibrosis. In some patients, the perivascular tissues showed strikingly shorter T2* than the rest of the liver parenchyma; this perivascular pattern was observed almost exclusively in the patients with F3 or more severe disease. We assume that the nonuniform T2* decay reflected uneven SPIO uptake, as previously observed (21). Hemosiderosis is an unlikely explanation for nonuniform T2* decay, as the histopathologic specimens that we collected usually showed no or minimal iron. Elucidation of the potential mechanisms that underlie nonuniform SPIO uptake will require further research.

A limitation of our study was its retrospective design. Most patients had advanced fibrosis with obvious imaging stigmata of liver disease. Because the number of patients with histopathologic analysis–proved F0–F3 disease was small, we included a cohort of patients with clinical F0 disease and pooled the F2 or lower and F3 or higher groups for most analyses. We did not compare patients who had mild (F1–F2) fibrosis with those who had no (F0) fibrosis because of the small number of patients with mild fibrosis. The small number of patients with mild fibrosis was a definite limitation of our study but was unavoidable because of the retrospective design: Patients with mild fibrosis rarely undergo biopsy at our institution. Overcoming this limitation likely will require a funded prospective study. Also, we could not retrospectively determine the proportion of patients with clinically obvious F4 disease, in whom noninvasive detection has lower clinical value. We did not compare double-enhanced MR imaging with other noninvasive methods or with gadolinium-enhanced MR imaging alone, which is much more commonly used in the imaging community. Therefore, we cannot determine the incremental diagnostic benefit of SPIOs for fibrosis detection.

Our double-enhanced MR protocol was not optimized for fibrosis detection. Fibrosis detection probably would be improved by the manipulation of technical parameters such as voxel size, repetition time, TE, flip angle, bandwidth, and spoiling. Further increasing the T2* weighting of SPIO- and/or double-enhanced gradient echoes should be beneficial.

Images were interpreted by two experienced MR radiologists in consensus. Thus, our results may not be generalizable to clinical practice. In our future works, analysis of the inter- and intraobserver variability in qualitative and quantitative scoring will be performed.

Histopathologic analysis findings are an imperfect reference standard. It is known that the fibrosis scores of biopsy specimens may be underestimations of the fibrosis severity (12,13,15). The global correlation of MR imaging and histopathologic findings is desirable but difficult to achieve in human subjects. Subjective histopathologic analysis also has the potential for interobserver variability. To minimize observer variability, we used the METAVIR scoring system, which yields greater inter- and intraobserver concordance than other scoring methods (1,42).

In conclusion, our study results represent proof of the concept that advanced liver fibrosis can be detected by using double-enhanced MR imaging. On the basis of these preliminary results, we are now actively optimizing double-enhanced MR imaging parameters, recruiting patients with milder fibrosis, implementing more sophisticated texture analysis, and developing new pulse sequences and image-processing algorithms.


   ADVANCE IN KNOWLEDGE
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCE IN KNOWLEDGE
References
 


   FOOTNOTES
 

Abbreviations: Az = area under receiver operating characteristic curve • CNR = contrast-to-noise ratio • CV = coefficient of variation • SPGR = spoiled gradient echo • SPIO = superparamagnetic iron oxide • TE = echo time

Authors stated no financial relationship to disclose.

See also Science to Practice in this issue.

Author contributions: Guarantors of integrity of entire study, all authors; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; manuscript final version approval, all authors; literature research, D.A.A., C.A.B., T.I.H.; clinical studies, all authors; statistical analysis, D.A.A., C.B.S.; and manuscript editing, all authors


   References
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ADVANCE IN KNOWLEDGE
 References
 

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