**3. The principle of unidimentional transient elastography**

**2. Liver biopsy – An imperfect gold standard**

*Liver biopsy provides a lot of information* [2-6]:

confirms if cirrhosis is present or not;

**•** it can determine treatment efficiency.

possible in 0.0088-0.3% of the cases [7-11].

from the same area occurs in 45% of the cases [14].

an imperfect "gold standard".

its evaluation (steatosis, iron overload, etc);

**•** provides important etiology data;

**•** helps establish the prognosis;

named after him [1].

210 Liver Biopsy – Indications, Procedures, Results

Liver biopsy was performed by P Ehrlich in 1883 and became a common exploration meth‐ od in 1958, when G Menghini introduced the first biopsy technique with a needle that was

**•** it represents the gold standard for a positive and differential diagnosis of diffuse liver diseases;

**•** allows for the evaluation of the necroinflammatory activity, evolutive stage (fibrosis) and

**•** identifies concomitent morphological alterations that may influence therapy response and

At the same time, one can not ignore the fact that liver biopsy has significant limitations: possible complications, including mortality; important sampling errors; high cost; subjective

Biopsy complications may vary in magnitude and frequency depending on the subjacent liv‐ er pathology. Among these can be listed: pain (epigastric area, right shoulder, right hypo‐ condrium); vagal response; hemorrhagic accidents (hemoperitoneum, hemobilia, liver hematoma); bile peritonitis, bilioma; bacteremia; infections and abscesses; pneumothorax and/or pleural reactions; hemothorax; arteriovenous fistula; subcutaneous emphysema; ad‐ verse reactions caused by the anesthetic; breaking of the biopsy needle; penetration of other organs: lung, kidney, colon. The mortality associated with this technique is low, but it is

The most significant problem encountered when interpreting a biopsy is represented by samplig error. Considering the fact that the tissue sample obtained through liver biopsy rep‐ resents approximately 1/50.000-1/100.000 of the liver volume, it can be inadequate for the di‐ agnosis of diffuse liver conditions, as the histopathological changes may be spread unevenly [5]. Even though liver biopsy is considered the standard exploration in the evaluation of liv‐ er diseases, it has an accuracy of only 80% in staging fibrosis and it can miss cirrhosis in 30% of the cases [12]. For example, Ragev reported that in HCV patients, there is a discrepancy of at least 1 stage between the right and left lobe in 33% of the patients [13]. At the same time, Siddique observed that a difference of at least one stage between 2 samples (15 mm long) cut

Considering all these observations, the results of the studies performed to validate a noninvasive diagnosis method must be interpreted with caution, since they are compared with

appreciations that may be due to important intra and interobserver variations.

The divice consists of a special transducer, that is placed in the axis of a mechanical vibrator. The vibrator generates pain-free vibrations that produce a train of elastic waves that will be transmited through the skin and subcutaneous tissue to the liver. At the same time with acti‐ vating the vibration, the probe performs a number of ultrasound acquisitions (the same process of emision-reception used in conventional ultrasonography), with a frequency of 4 kHz. Reports on the tissues deformation caused by elastic wave transmission can be formu‐ lated by comparing the succesive ultrasound (US) signals acquired in this manner. The time necessary for the train of waves to propagate along the area of interest, as well as propaga‐ tion velocities are being measured. This way liver stiffness can be determined using the fol‐ lowing formula: E = 3ρVs<sup>2</sup> (E – elasticity module, ρ – density, a constant of the material; Vs – propagation velocity within the liver parenchyma). The more rigid the material, the higher the velocity of propagation [15-17].

During the examination, the patient is lying down, face-up, with his right arm placed in hy‐ perextension and above the head for an adequate exposure of his right hypocondrium. The probe is placed in contact with the patient's skin, at the level of an intercostal space, in an area of full liver dullness and avoiding any large vessels.

When the button on the probe is pushed, the vibration that will be transmitted through the liver is activated. By analyzing tissue deformation report, the software of the equipment will measure the liver stiffness (LS). The results are given in kiloPascals (kPa) and correspond to a median value of 10 valid measurements. The machine can determine values between 2.5 and 75 kPa.

The monitor of the machine will display data regarding the patient's identity, diagnosis, name of the examining physician, the instantaneous value of liver stiffness (CS), the median stiffness resulted from 10 valid measurements, the success rate (SR), as well as the variation of the 10 values compared with the median value (IQR).

To be in agreement with the recommendations of the producer, the success rate must be at least 60% and IQR must not exceed 30% of the median liver stiffness [16], even though it seems that the best concordance with liver biopsy is obtained when this value does not ex‐ ceed 20% of the median [18].

There are no studies that especially focus on the issue of the variability of LS measurements and therefore the interpretation of the results is done according to the experience of the ex‐ aminer and the recommandations of the producer [19]. It is not known whether this variabil‐ ity is encountered only in the diseased liver or whether it is present in the healthy liver as well and to what degree this affects the interpretation of the results. The cause of this prob‐ lem can be an inadequate technique or the liver pathology itself (for example, in macronod‐ ular cirrhosis, liver stiffness can be different in different areas of the liver). When there is a high variability of the results, it is important to check whether the probe is placed perfectly perpendicular on the thoracic wall, if the transmited vibration does not encounter the ribs and if the waves are transmited vertically, strictly between the ribs. If the generated wave is large, bifid or angulated, than the software of the machine will reconstruct the velocity curve in different points of the wave and therefore lead to variations of the acquired values. In order to obtain an accurate elastogram the transducer must be placed in the middle area of the right lobe, avoiding contact with the ribs that may lead to vibration distorsion and absorbtion [19].

The prediction model computed from this study [25] can be expressed as follows:

ty grade.

the same fibrosis stage.

**HCV patients**

hepatitis type C [21, 26].

F3 than from F1 to F2 [12].

**4.1. The diagnosis of liver fibrosis stages**

Liver stiffness (log-transformed) = 0.493 + 0.180\*fibrosis stage +0.034\*steatosis + 0.033\*activi‐

Non-Invasive Evaluation of Liver Steatosis, Fibrosis and Cirrhosis in Hepatitis C Virus Infected Patients Using

Unidimensional Transient Elastography (Fibroscan®)

http://dx.doi.org/10.5772/52621

213

Therefore, our studies showed that fibrosis is indeed the main predictor of liver stiffness, but the activity and steatosis cannot be neglected, and may explain the LS variability within

**4. Performance of TE for the noninvasive evaluation of liver fibrosis**

The first condition that benefited from unidimensional transient elastography was chronic

Studies performed on a large number of HCV patients indicate that the LS value is highly correlated with the stage of fibrosis. The practical utility of the method is based on establish‐ ing cutoff values for each stage of fibrosis. A diagnosis of stage F ≥2, F ≥3 and F4 (cirrhosis) is based on measurements of liver stiffness that vary, according to some studies, from 6.2 to

There are some meta-analyses addressing the issue of diagnosis performance of TE. Fifty studies were included in the analysis performed by Friedrich Rust et al. The mean AUROC for the diagnosis of significant fibrosis, severe fibrosis, and cirrhosis were 0.84, 0.89 and 0.94, respectively [31]. In Stebbing's meta-analysis, a total of 22 studies were selected, comprising 4430 patients, most of them suffering from a virus C liver infection. The pooled estimates for significant fibrosis (≥F2) measured 7.71 kPa (LSM cutoff value) with a sensitivity of 71.9% and a specificity of 82.4%, whereas for cirrhosis (F4) the results showed a cutoff of 15.08 kPa

It must be underlined that, in spite of the very good areas under the ROC curves, overlaps of the stiffness values were registered in adjacent stages, especially for early fibrosis [33]. The increase of liver stiffness is higher between stage F2 (6.6 kPa) and F3 (10.3 kPa) of fibro‐ sis than between F1 (5.5 kPa) and F2 (6.6 kPa), a fact that is in agreement with the morpho‐ logical data according to which the increase in fibrotic tissue is more significant from F2 to

The diagnosis accuracy of TE is much better in predicting cirrhosis. In Friedrich-Rust metaa‐ nalysis [31], the AUROC mean for the diagnosis of cirrhosis was 0.94 and the performance estimated by Talwalkar [34] was also very good: sensitivity 87%, specificity 91%, positive

probability rate 11.7, and negative probability rate 0.14 (95% CI 0.10-0.20).

8.8 Kpa, 7.7 to 10.8 kPa and from 11 to 14.8 kPa (Table 1) [24, 26-30].

with a sensitivity of 84.45% and a specificity of 94.69% [32].

The technique measures the stiffness of a volume that is equivalent with that of a cilinder of 1 cm in diameter and 4 cm in length (the measurement can be performed on a distance of 25 to 45 cm from the skin). This volume, representing about 1/500 of the liver volume, is at least a 100 times larger than the one obtained through liver biopsy and it is therefore more repre‐ sentative for the whole liver parenchyma [20, 21].

The examination can be performed by a technician following a short period of training (ap‐ proximately 100 cases) [22-23], while the clinical interpretation of the results must always be done by an expert who would consider the demographic data, the etiology of the disease and the biochemical profile of the patient at the moment of the examination [21].

A multivariate analysis of the relationship between liver stiffness and fibrosis, necroinflam‐ matory activity and steatosis Showed, in some studies, that there is a significant correlation with fibrosis, but no correlation with necroinflammatory activity and steatosis [16, 24]. Nev‐ ertheless, the authors of the initial concept acknowledged, following in vitro studies, that it is unlikely that a single physical parameter (liver stiffness) would describe entirely a com‐ plex biological system in which fibrosis is only a part [15].

A prospective assessment of the role of the histopathological parameters seen in LB in ex‐ plaining the variance of liver stiffness was performed on 345 chronic hepatitis C patients that all underwent liver biopsy [25]. First, LS correlated highly with the degree of fibrosis assessed by liver biopsy,, but we also found a weak correlation with hepatic iron deposition and steatosis and a mild correlation with activity. In multiple regression analysis, fibrosis, activity, and steatosis independently influenced LSM. Iron deposition does not seem to in‐ fluence the liver stiffness in CHC patients. Fibrosis, activity, and steatosis together explained 62.4% of the variance of the LS. The three significant parameters uniquely explained 45.95% of the amount of LS, with fibrosis making the most unique contribution (44.49%); the differ‐ ence of 16.25% (62.4%-45.95%) was accounted for by the joint contribution of the three pa‐ rameters. The size and the direction of the relationships suggest that higher LS values are obtained for patients with advanced fibrosis, increased necroinflammatory activity and in‐ creased steatosis. Among these three, however, the stage of fibrosis is the single most impor‐ tant predictor, as suggested by the squared partial correlation [25].

The prediction model computed from this study [25] can be expressed as follows:

Liver stiffness (log-transformed) = 0.493 + 0.180\*fibrosis stage +0.034\*steatosis + 0.033\*activi‐ ty grade.

Therefore, our studies showed that fibrosis is indeed the main predictor of liver stiffness, but the activity and steatosis cannot be neglected, and may explain the LS variability within the same fibrosis stage.
