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DOI:10.2214/AJR.06.0322
AJR 2007; 188:758-764
© American Roentgen Ray Society


Original Research

Real-Time Elastography for Noninvasive Assessment of Liver Fibrosis in Chronic Viral Hepatitis

Mireen Friedrich-Rust1, Mei-Fang Ong1, Eva Herrmann1, Volker Dries2, Panagiotis Samaras1, Stefan Zeuzem1 and Christoph Sarrazin1

1 Department of Internal Medicine II, Saarland University Hospital, Kirrbergerstrasse, Bldg. 41, Homburg/Saar 66421, Germany.
2 Institute of Pathology, Mannheim, Germany.

Received March 3, 2006; accepted after revision July 31, 2006.

 
Address correspondence to M. Friedrich-Rust (mireen.friedrich.rust{at}uniklinikum-saarland.de).


Abstract
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
 
OBJECTIVE. Recently, transient elastography (FibroScan) has been introduced for noninvasive staging of liver fibrosis. Here, we investigated a novel approach for noninvasive assessment of liver fibrosis using sonography-based real-time elastography, which can be performed with conventional ultrasound probes during a routine sonography examination.

MATERIALS AND METHODS. Real-time elastography was performed in 79 patients with chronic viral hepatitis and known fibrosis stage and in 20 healthy volunteers. A specially developed program was used for quantification of tissue elasticity. Stepwise logistic regression analysis was performed to define an elasticity score using variables with high reproducibility in a preceding analysis of data from 16 different patients. In addition, aspartate transaminase-to-platelet ratio index (APRI) and routine laboratory values were included in the analysis.

RESULTS. The Spearman's correlation coefficient between the elasticity scores obtained using real-time elastography and the histologic fibrosis stage was 0.48, which is highly significant (p < 0.001). The diagnostic accuracy expressed as areas under receiver operating characteristic (ROC) curves were 0.75 for the diagnosis of significant fibrosis (fibrosis stage according to METAVIR scoring system [F] ≥ F2), 0.73 for severe fibrosis (F ≥ F3), and 0.69 for cirrhosis. For a combined elasticity-laboratory score, the areas under the ROC curves were 0.93, 0.95, and 0.91, respectively.

DISCUSSION. Real-time elastography is a new and promising sonography-based noninvasive method for the assessment of liver fibrosis in patients with chronic viral hepatitis.

Keywords: elastography • fibrosis • hepatitis • liver biopsy • liver disease • real-time elastography • sonography


Introduction
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
 
Chronic infection with viral hepatitis is an important cause of liver cirrhosis and its sequelae [1-3]. A precise estimation of the degree of liver fibrosis is important for estimation of prognosis, surveillance, and treatment decisions in patients with chronic viral hepatitis [4-7]. At present, liver biopsy is still the gold standard for the assessment of liver fibrosis. However, it is an invasive method associated with patient discomfort and, in rare cases, with serious complications [8-10]. In addition, the accuracy of liver biopsy is limited because of significant intra- and interobserver variability and sampling errors [11-14]. High interobserver variability has been reported between two pathologists when analyzing the same biopsy sample [12]. Furthermore, studies have shown a great sampling variability in biopsies if consecutive percutaneous samples were taken by redirecting the biopsy needle through a single entry sight and when comparing surgical samples with individual virtual biopsies or biopsy samples taken from the right and left hepatic lobes [11, 13, 14]. Therefore, research has been focused on the evaluation of noninvasive methods for the assessment of liver fibrosis. The different approaches include routine hematologic and biochemical tests, surrogate fibrosis markers in the blood and their algorithms (i.e., FibroTest [BioPredictive], Forns score, aspartate transaminase-to-platelet ratio index [APRI]), glycomics, proteomics, and recently transient elastography (FibroScan, Echosens) [15-30]. Using a combination of different blood markers and the assessment of tissue elasticity based on transient elastography has shown promising results in the determination of the exact degree of liver fibrosis [26, 27, 31, 32].

Transient elastography (FibroScan) is performed with an ultrasound transducer probe mounted on the axis of a vibrator. A vibration transmitted from the vibrator toward the tissue induces an elastic shear wave that propagates through the tissue. These propagations are followed by pulse-echo sonographic acquisitions and their velocity, which is directly related to tissue stiffness, is measured: The harder the tissue, the faster the shear wave propagates [26, 27, 29, 33].

Real-time elastography is a new method for measurement of tissue elasticity integrated in a sonography machine (Hitachi EUB-8500 and EUB-900) and is technically different from transient elastography. With conventional ultrasound probes, echo signals before and under slight compression are compared and analyzed [34]. Because tissue elasticity cannot be measured directly from reflected ultrasound echoes, in previous studies using the elastography principle, methods analyzing the displacement of phases (e.g., cross-correlation method) were investigated [35-44]. However, these measurements were associated with strong aliasing. To overcome these restrictions, Hitachi Medical Systems developed real-time elastography based on the combined autocorrelation method and 3D tissue model for the determination of phase displacement in real time without aliasing [34, 45-47].

In recent studies, researchers have evaluated real-time elastography for the characterization and detection of focal lesions in the breast, thyroid gland, and prostate gland [34, 48-52]. Here, we present a proof-of-principle study to evaluate the value of realtime elastography for the assessment of liver fibrosis. Results of real-time elastography were compared with fibrosis stage obtained by assessing liver biopsy samples and with the APRI [25].

The aims of the study were, first, to establish a formula to obtain a first liver elasticity score for this new method (i.e., real-time elastography); second, to determine the accuracy of elasticity scores for correct prediction of liver fibrosis stage; third, to assess the diagnostic accuracy of predicting significant fibrosis (fibrosis stage according to METAVIR scoring system [F] 3 F2); and, fourth, to optimize the accuracy of fibrosis stage prediction by the combination of real-time elastography with simple laboratory parameters.


Materials and Methods
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
 
Patients
Fifty-nine patients with chronic viral hepatitis and histologic results for fibrosis stage, 20 patients with chronic viral hepatitis and proven liver cirrhosis, and a control group of 20 healthy volunteers were included in the study. In all patients, chronic viral hepatitis was proven by the presence of hepatitis C virus (HCV) antibodies and HCV RNA or hepatitis B surface antigen (HBsAg) in serum. In 50 of 59 patients with chronic viral hepatitis, liver biopsy was performed 1 day before real-time elastography; in four patients, liver biopsy was performed 1 day after real-time elastography; and in the remaining five patients, the time interval between liver biopsy and real-time elastography was 3-20 months (mean, 7 months).

Because the mean progression rate of liver fibrosis has been estimated to be 0.133-0.154 fibrosis stages on the METAVIR scoring system per year [53], the five patients with a longer time interval between liver biopsy and real-time elastography were enrolled in the present study. The 59 patients who underwent a liver biopsy did not have overt signs of cirrhosis on sonography or MRI. However, in four of these 59 patients, fibrosis stage 4 (cirrhosis) was diagnosed on liver biopsy. None of the 59 patients received antiviral therapy between liver biopsy and real-time elastography.

For the additional 20 patients with chronic viral hepatitis and liver cirrhosis, no liver biopsy had been performed during the previous 2 years. In these patients, obvious clinical signs of liver cirrhosis were present at the time of presentation in the outpatient clinic. The definition of liver cirrhosis in these patients was based on results of sonography or MRI (liver surface nodularity, hypertrophy of segment I, signs of portal hypertension) or on historical histology results and on clinical and biochemical signs of cirrhosis (thrombocytopenia, low serum albumin, hyperbilirubinemia, endoscopic signs of portal hypertension, history of ascites).

All patients were enrolled consecutively for realtime elastography between January and August 2005 on the basis of the time of presentation in the hepatology outpatient clinic of Saarland University Hospital.

Blood parameters were obtained on the same day that real-time elastography was performed; for further description, see the Materials and Methods section, Blood Markers subheading.

The control group consisted of healthy adult volunteers with normal liver enzyme levels, negative anti-HCV antibodies, and negative HBsAg who did not have a history of relevant concomitant illness, such as heart, lung, or liver disease or neoplasia. All healthy volunteers did not take any medication or drugs and did not have an excessive daily alcohol intake (> 15 g/d).

In addition, for statistical reasons, real-time elastography was evaluated twice in 16 different patients with liver disease for a preceding analysis to assess the reproducibility of different variables characterizing elasticity. These two examinations were performed on the same day by two different operators to define variables with the lowest interobserver variability of real-time elastography. The two operators were blinded to each other's findings and to the clinical and histologic data of the patients.

The present study was performed in accordance with the ethical guidelines of the Declaration of Helsinki.

Liver Histology
Liver biopsy samples were taken via a right intercostal space from the right liver lobe. First, sonography was performed to find the safest and best accessible intercostal space from which to obtain a biopsy sample. After disinfection and local anesthesia of the skin, intercostal space, peritoneum, and liver capsule, liver biopsy was performed at the previously marked site with the Hepafix set (B. Braun Melsungen AG) for percutaneous liver biopsy using an 18-gauge needle (Menghini needle, B. Braun Melsungen) with an outer diameter of 1.2 mm.

Local anesthesia and liver biopsy were performed without direct sonographic guidance. Liver biopsy specimens were fixed in formalin and embedded in paraffin. Four-micrometer-thick sections were stained with H and E stain and elastica van Gieson stain. An experienced pathologist blinded to the results of realtime elastography analyzed all the biopsy specimens.

Liver fibrosis stages were evaluated semiquantitatively according to the METAVIR scoring system [54]. Liver fibrosis was staged on an F0-F4 scale: F0, no fibrosis; F1, portal fibrosis without septa; F2, portal fibrosis with few septa; F3, numerous septa without cirrhosis; and F4, cirrhosis [54]. Steatosis was assessed according the number of hepatocytes with fatty degeneration: 0, none; 1, 1-10% of hepatocytes; 2, 11-33% hepatocytes; 3, 34-66% hepatocytes; and 4, 67-100% hepatocytes. The biopsies were judged as adequate if the number of portal tracts was at least six.

Blood Markers
The following blood parameters were determined in the same laboratory: platelet count, aspartate aminotransaminase level (AST), alanine aminotransaminase level (ALT), {gamma}-glutamyl transpeptidase (GGT) level, and total bilirubin level. Enzymatic activity was measured at 37°C, according to International Federation of Clinical Chemistry standards.

The APRI index was calculated as follows: AST (x upper limit of normal range) x 100/platelet count (109/L). The upper limit of normal of AST for women was 35 IU/mL, and the upper limit of normal for men was 50 IU/mL [25].

Real-Time Elastography Principle
Real-time elastography is an imaging technique that can reveal the physical property of tissue using conventional ultrasound probes. Although used for clinical studies with sonography devices manufactured by different companies [34, 48-52], to our knowledge currently real-time elastography is commercially available only in the Hitachi EUB-8500 and EUB-900 machines. The tissue elasticity distribution can be calculated by the strain and stress of the examined tissue.

In a first step, the amount of displacement of the reflected ultrasound echoes before and under compression are measured (stress field). In hard tissue, the amount of displacement of the reflected ultrasound echoes before and under compression is low, whereas in elastic or soft tissue, the amount of displacement is high because soft tissue can be compressed more than hard tissue. In addition, with the combined autocorrelation method, echo-frequency patterns of parallel ultrasound echoes are compared to detect possible lateral evasion of hardened tissue areas.


Figure 1
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Fig. 1 Tissue elasticity distribution represented as color-coded images over conventional B-mode image. Image presents example of 34-year-old healthy female subject.

 
In a second step, a strain field is reconstructed from the measured displacements (strain image). Conclusions concerning the elasticity of the underlying tissue can be drawn from these reconstructions abutted to a spring model. Areas of high elasticity (i.e., soft tissue) appear as places of high strain, areas with low elasticity (i.e., hard tissue) appear as places of low strain. By using the 3D tissue model (finite-element method), the examined tissue is divided in up to 30,000 finite elements of equal stiffness before compression. During compression, the displacement of each element is measured. The finite-element method can then determine the tissue elasticity from the calculation of each element. The calculation of tissue elasticity distribution is performed in real time, and the examination results are represented as color-coded images with the conventional B-mode image in the background [34, 36, 40-42, 46, 47].

Elasticity Score
Patients and control subjects underwent real-time elastography (EUB-8500, Hitachi Medical Systems; 9-MHz probe). The patients were examined in a supine position with the right arm elevated above the head. Patients were instructed to continue breathing as usual. Because each elastography image is obtained in a few milliseconds, breathing did not cause any motion artifacts. The examination was performed on the right lobe of the liver through the intercostal space in all patients because, first, liver biopsy was also performed on the right lobe; second, a subcostal approach cannot be achieved in all patients; and, third, the compressions performed were micrometer compressions only, which could be performed intercostally without having to apply great pressure. An area was chosen where the liver tissue was at least 6 cm thick and was free of large blood vessels.

The examination was performed with a 9-MHz transducer because, similar to B-mode imaging, higher frequencies allow better analysis of areas close to the transducer, and assessment of real-time elastography is optimized by the manufacturer on superficial tissues. The measurement depth was between 20 and 50 mm (mean, 35 mm) with a 350-500 mm2 area of measurement (mean, 420 mm2). The results were considered reliable only if a pressure of 3-4 on a scale of 0-6 arbitrary units was applied for measurement (Fig. 1). Ten valid measurements were performed in each subject and recorded as colorcoded images. The entire examination lasted approximately 5-10 minutes per patient.

Because this study was, to our knowledge, the first application of real-time elastography for evaluating liver tissue elasticity, a new elasticity score had to be established. For each pixel, the value of the elasticity distribution was calculated on a scale of 0 to 1 (0 = maximum elasticity, 1 = minimum elasticity) from the color-coded bit-map image yielded by a computer program specially developed by our study group using Matlab (version 6, MathWorks). These results were summarized by descriptive statistics as mean, median, minimum, maximum, and the frequency of pixel values above 0.75 of a single measurement.

In a second step, further descriptive statistics were obtained taking into account images from all measurements with standardized pressure. In this way, we obtained a large number (> 250) of summarizing variables for characterization of real-time elastography using a professional computer program for statistical analysis (SPSS version 12.0, SPSS). To avoid over-fitting and to exclude unreliable variables, the final analysis was based on only 10 such summarizing variables that characterized elasticity with high reproducibility in a small preceding analysis of realtime elastography in 16 different patients. For the final analysis, we used stepwise multivariate logistic regression for prediction of significant fibrosis to define an elasticity score and also a combined elasticity-laboratory score with a mean value of approximately 100 and an SD of approximately 10 in patients with no or minor fibrosis.

Statistical Analysis
Because elasticity-laboratory scores were not normally distributed we used the nonparametric Jonckheere-Terpstra test to compare these scores with histologic fibrosis stage. The results are illustrated as the median and 25th- to 75th-percentile values (box plot). The correlations between both scores and the histologic fibrosis stage were also assessed using Spearman's correlation coefficient.

The diagnostic performance of the elasticity score, APRI, and the combination of the elasticity score and laboratory values was assessed by receiver operating characteristic (ROC) curves. The ROC curve represents sensitivity versus 1 minus the specificity for all possible cutoff values for prediction of significant and severe fibrosis, respectively. The areas under the ROC curve (AUCs) and 95% CIs of AUC were calculated (SPSS version 12.0). Here, AUC values close to 1.0 indicate the highest diagnostic accuracy. Cutoff values defining prediction regions for each fibrosis stage were defined by a common optimization step maximizing the sum of the sensitivities in predicting the single stages. Finally, sensitivity, specificity, and positive and negative predictive values were calculated without further adjustments on the basis of the same data set using Matlab. Thereby, the whole study population was analyzed; the group of patients with proven liver cirrhosis was assigned to METAVIR fibrosis stage F4.


Results
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
 
Altogether 79 patients with chronic hepatitis B or C and 20 healthy subjects were included in the study. Demographic, biochemical, and virologic characteristics according to liver fibrosis stage are shown in Table 1. None of the patients with histologic assessment of liver fibrosis had METAVIR fibrosis stage F0. Four patients without clinical or biochemical evidence of cirrhosis were staged as METAVIR fibrosis stage F4 by liver histology. Healthy subjects did not undergo a liver biopsy, but they were evaluated as having fibrosis stage F0 in the statistical analysis. Patients with proven liver cirrhosis were classified as METAVIR fibrosis stage F4.


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TABLE 1: Patients' Characteristics According to Fibrosis Stage and Control Subjects' Characteristics

 


Figure 2
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Fig. 2A —Box plots show correlation between noninvasive tests and histologic results from liver biopsy. Top and bottom of boxes represent first and third quartiles, respectively. Length of box represents interquartile range within which 50% of values are located. Thick line through each box represents median. Error bars mark minimum and maximum values (range). Small circles represent outliers. Real-time elastography. Skewed data for control subjects might be explained by inhomogeneous group of patients, whereas skewed data for fibrosis stage F2 can be explained by small number of patients in this group.

 


Figure 3
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Fig. 2B —Box plots show correlation between noninvasive tests and histologic results from liver biopsy. Top and bottom of boxes represent first and third quartiles, respectively. Length of box represents interquartile range within which 50% of values are located. Thick line through each box represents median. Error bars mark minimum and maximum values (range). Small circles represent outliers. Aspartate transaminase-to-platelet ratio index (APRI). Skewed data are equalized when using log scale for APRI score.

 


Figure 4
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Fig. 2C —Box plots show correlation between noninvasive tests and histologic results from liver biopsy. Top and bottom of boxes represent first and third quartiles, respectively. Length of box represents interquartile range within which 50% of values are located. Thick line through each box represents median. Error bars mark minimum and maximum values (range). Small circles represent outliers. Elasticity-laboratory combination values for each fibrosis stage.

 


Figure 5
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Fig. 3 Receiver operating characteristic curves for realtime elastography (light gray), aspartate transaminase-to-platelet ratio index (dark gray), and combination of real-time elastography and blood markers (black) for diagnosis of significant fibrosis (F ≥ F2).

 
Generation of an Elasticity Score
The definition of the overall elasticity score was based on stepwise multivariate logistic regression of 10 variables characterizing elasticity with high reproducibility in a preceding analysis of 16 different patients with unknown fibrosis stage.

The overall elasticity score was defined as a linear combination of descriptive statistics using only the upper half of the single images. The elasticity score is calculated with the following formula:

177 + 50 x log10 median(freq(pixel ≥ 0.75)) - 13,000 x min(min(pixel with values > 0))

where freq is frequency, and min is minimum. The elasticity scores ranged from 65 to 122.

Adding information from blood markers may improve the diagnostic accuracy of real-time elastography. Therefore, a logistic regression analysis was performed including a few routine laboratory parameters. The best accuracy could be achieved by combining the elasticity score with platelet count and GGT calculated by the following formula:

combined elasticity - laboratory score = 158 + 0.28 x elasticity score - 38 x log10 platelet count [103/mm3] + 0.3xlog10 GGT [x ULN]

where ULN is the upper limit of the normal range for GGT. The upper limit of normal of GGT for women was 39 IU/mL, and the upper limit of normal of GGT for men was 66 IU/mL. The combined elasticity-laboratory score ranged from 82 to 137.

Liver Histology
The mean number of histologic cores was two (range, 1-5). The mean number of portal tracts was nine (range, 6-15). The mean length of liver biopsy samples was 27.1 ± 14.6 mm.

Relationship Between Liver Elasticity and Liver Histology
Interestingly, all 10 elasticity variables used in the multivariate logistic regression were significantly associated with the fibrosis stage and, in all but one variable, the Jonckheere-Terpstra test resulted in a p value below 0.0001. For comparison of histologic liver fibrosis stages and real-time elastography elasticity scores, a high correlation of increasing elasticity scores with increasing stage of fibrosis was observed (Fig. 2A). The Spearman's correlation coefficient between the elasticity scores and the histologic fibrosis stages was highly significant, with a value of 0.48 (p < 0.001).

The AUCs, a measurement of the diagnostic accuracy of a test, were 0.75 for the diagnosis of significant fibrosis (F ≥ F2), 0.73 for the diagnosis of severe fibrosis (F ≥ F3), and 0.69 for the diagnosis of cirrhosis (F = F4) (Fig. 3 and Table 2). With regard to the distribution of elasticity scores according to METAVIR fibrosis stages, the cutoff values were determined as 100.1 for F ≥ F2, 102.5 for F ≥ F3, and 111.75 for F = F4 (Table 3). Altogether, 80% of the patients with significant fibrosis (F ≥ F2) could be correctly identified with the real-time elastography (sensitivity). In patients with an elasticity score of less than 100.1, the presence of significant fibrosis (F ≥ F2) could be excluded in 78.6% of cases (negative predictive value) (Table 3). Excluding liver biopsy length shorter than 25 mm did not improve the results. Elasticity scores were not influenced by the degree of steatosis in the liver.


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TABLE 2: Areas Under Receiver Operating Characteristic (ROC) Curve for Elasticity Scores, APRI, and the Combined Elasticity and Laboratory Score According to METAVIR Fibrosis Stage (F)

 

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TABLE 3: Cutoff Values of Real-Time Elastography (Elasticity Score) for the Diagnosis of METAVIR Fibrosis Scores (F)

 

Relationship Between APRI Index and Liver Histology
A high correlation of increasing elasticity scores with increasing stage of fibrosis was observed (Fig. 2B). The Spearman's correlation coefficient between the APRI index and the histologic fibrosis stages was highly significant, 0.77 (p < 0.001). The AUCs for the APRI index were 0.87 for the diagnosis of significant fibrosis (F ≥ F2), 0.88 for the diagnosis of severe fibrosis (F ≥ F3), and 0.88 for the diagnosis of cirrhosis (F = F4) (Fig. 3 and Table 2).

Relationship Between the Combined Elasticity-Laboratory Score and Liver Histology
The best diagnostic accuracy was obtained by combining the variables used for the calculation of the elasticity score with platelet count and GGT. A high correlation of increasing combined elasticity-laboratory scores with increasing stage of fibrosis was observed (Fig. 2C). Spearman's correlation coefficient between these scores and the histologic fibrosis stage was highly significant with 0.78 (p < 0.001). The AUCs for the combined scores were 0.93 for the diagnosis of significant fibrosis (F ≥ F2), 0.95 for the diagnosis of severe fibrosis (F ≥ F3), and 0.91 for the diagnosis of cirrhosis (F = F4) (Table 2). With regard to the distribution of elasticity-laboratory scores according to METAVIR fibrosis stages, the cutoff values were determined to be 99.1 for F ≥ F2, 99.7 for F ≥ F3, and 114.7 for F = F4 (Table 4). The sensitivity for the detection of significant fibrosis was 84.4% (Table 4).


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TABLE 4: Cutoff Values of the Combined Elasticity and Laboratory Score for the Diagnosis of METAVIR Fibrosis Scores (F)

 


Discussion
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
 
In patients with chronic viral hepatitis, the identification of those with significant fibrosis (F ≥ F2) is of special interest because the presence of fibrosis is an important parameter for evaluation of indications for antiviral treatment. Therefore, a test with a high diagnostic accuracy for the determination of significant fibrosis is of great therapeutic value. In previous studies, estimation of liver fibrosis was performed with transient elastography (Fibro-Scan) and was shown to have a high diagnostic accuracy for the prediction of significant fibrosis [26, 27, 29]. In the present study, we have shown that real-time elastography can also be used as a sonography-based method for noninvasive measurement of liver fibrosis.

Patients with ascites were excluded from the study because real-time elastography, similar to FibroScan, works only with close contact to the liver. However, the development of ascites is a strong indicator for the presence of cirrhosis that makes noninvasive staging of fibrosis unnecessary. In the present study, patients with a body mass index (BMI) of up to 30 were enrolled, and real-time elastography was performed successfully in all included patients. Whether real-time elastography can be performed successfully in patients with a BMI > 30 needs to be addressed in future studies. The examination was performed through a right intercostal space, and patients did not need to hold their breath during the examination. Furthermore, no influence of the degree of steatosis in the liver on elasticity scores was observed in the present study. Similar results have been reported from studies analyzing transient elastography with FibroScan [55, 56].

In the present study, we found highly significant positive correlation between elasticity scores obtained with real-time elastography and the METAVIR fibrosis stage. An AUC value of 0.75 was obtained using realtime elastography (elasticity score) for the diagnosis of significant fibrosis (F ≥ F2). In comparison, three recent studies analyzing the noninvasive assessment of liver fibrosis with FibroScan revealed AUCs between 0.75 and 0.84 for the diagnosis of significant fibrosis (F ≥ F2) [26, 27, 29]. Nevertheless, this is the first evaluation of real-time elastography for the diagnosis of liver fibrosis.

It is likely that the diagnostic accuracy of real-time elastography may be improved by further optimization of the images using different ultrasound probes, refined selection of the analyzed area of liver tissue, and a more refined statistical assessment of the elasticity images for a larger data set or a larger number of images for each patient. Especially the diagnosis of cirrhosis seems to be improvable if more reliable assessments of the variability between the single images are available. It is known that the accuracy of liver biopsy is limited because of significant intra- and interobserver variability and sampling errors [11-14]. Nevertheless, because this is the first study assessing real-time elastography for the detection of liver fibrosis, liver biopsy was used as a gold standard without further analysis of possible false staging of biopsy.

The diagnostic accuracies obtained for the APRI in the present study (AUC: 0.87 for F 3 F2, 0.88 for F ≥ F3, and 0.88 for F = F4) were similar to those revealed in the large APRI evaluation study by Wai et al. [25] (AUC: 0.80 and 0.88 for F ≥ F2, and 0.89 and 0.94 for F = F4), but they were higher than in previous studies comparing the APRI with the FibroTest or FibroScan (AUC: 0.74-0.75 for F ≥ F2, 0.80-0.82 for F = F4) [27, 57]. These differences might be due to the relatively large group of patients without significant fibrosis in the present study (including the healthy subjects) and in the study by Wai et al. (50%) compared with the other studies (25%). Although the definition of the upper limit of the normal range differs and limits the use of APRI according to the literature, it did not seem to affect the results in our study because only the correlation and AUC were determined, not specific cutoffs.

The results of the APRI were superior to the real-time elastography findings, although the highest diagnostic accuracy in the present study was obtained by a mathematic combination of the elasticity score and two routine laboratory values (platelet count and GGT) (i.e., combined elasticity-laboratory score), achieving AUCs of 0.93 for the diagnosis of significant fibrosis (F ≥ F2).

Recently, Castera et al. [27] compared transient elastography (FibroScan), FibroTest, APRI, and liver biopsy for the assessment of liver fibrosis in a large number of patients. Interestingly, the authors reported the best performance also by a combination of liver elasticity with blood markers (FibroScan and FibroTest) with a comparable AUC value of 0.88 for the diagnosis of significant fibrosis (F ≥ 2).

In conclusion, real-time elastography is a new and promising sonography-based noninvasive method for the assessment of liver fibrosis in patients with chronic viral hepatitis. In combination with simple laboratory values, real-time elastography can further improve the discrimination of different fibrosis stages, which plays a decisive role in the management of patients with viral hepatitis.

Future studies on larger patient cohorts are necessary for improvement and also validation of the elasticity scores and their cutoffs obtained in the present study because the analyses of sensitivity and specificity in the present study were performed on the same data set as the calculation and optimization of the elasticity scores and cutoffs. Results of further studies are needed before real-time elastography can be introduced in clinical practice. In addition, the combination of real-time elastography with other blood tests such as FibroTest may further improve specificity and sensitivity for the noninvasive estimation of liver fibrosis. A head-to-head comparison of transient elastography (FibroScan) and real-time elastography would be of future interest as well.


Acknowledgments
 
We are grateful to Professor Klaus Remberger (Institute of Pathology, Saarland University Hospital, Homburg/Saar, Germany) for providing the histologic specimens and helpful discussions.


References
Top
Abstract
Introduction
Materials and Methods
Results
Discussion
References
 

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