THE ROLE OF TRANSIENT ELASTOGRAPHY IN THE DIAGNOSIS OF LIVER FIBROSIS AND PORTAL HYPERTENSION

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LITHUANIAN UNIVERSITY OF HEALTH SCIENCES MEDICAL ACADEMY

Romanas Zykus

THE ROLE OF TRANSIENT

ELASTOGRAPHY IN THE DIAGNOSIS

OF LIVER FIBROSIS AND PORTAL

HYPERTENSION

Doctoral Dissertation Biomedical Sciences, Medicine (06B) Kaunas, 2016 1

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The dissertation was prepared in the Medical Academy of Lithuanian University of Health Sciences during the period of the 2011–2015 year.

Scientific Supervisor

Prof. Dr. Laimas Virginijus Jonaitis (Lithuanian University of Health Sciences, Biomedical Sciences, Medicine – 06B).

Dissertation is defended at the Medical Research Council of the Medical Academy of Lithuanian University of Health Sciences

Chairperson

Prof. Dr. Gediminas Kiudelis (Lithuanian University of Health Sciences, Biomedical Sciences, Medicine – 06B).

Members:

Dr. Juozas Kupčinskas (Lithuanian University of Health Sciences, Biomedical Sciences, Medicine – 06B);

Prof. Dr. Antanas Mickevičius (Lithuanian University of Health Sciences, Biomedical Sciences, Medicine – 06B);

Prof. Dr. Habil. Jonas Valantinas (Vilnius University, Biomedical Sciences, Medicine – 06B);

Assoc. Prof. Dr. Riina Salupere (University of Tartu, Biomedical

Sciences, Medicine – 06B);

Dissertation will be defended at the open session of the Medical Research Council of Lithuanian University of Health Sciences on May 6th, 2016 at 2 p.m. in the Great Auditorium at the Hospital of Lithuanian University of Health Sciences Kauno klinikos.

Address: Eivenių 2, LT- 50161, Kaunas, Lithuania.

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LIETUVOS SVEIKATOS MOKSLŲ UNIVERSITETAS MEDICINOS AKADEMIJA

Romanas Zykus

IMPULSINĖS ELASTOGRAFIJOS

PANAUDOJIMAS DIAGNOZUOJANT

KEPENŲ FIBROZĖS LAIPSNĮ BEI

HIPERTENZIJĄ KEPENŲ VARTŲ

VENOJE

Daktaro disertacija Biomedicinos mokslai, medicina (06B) Kaunas, 2016 3

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Disertacija rengta Lietuvos sveikatos mokslų universitete Medicinos akademijoje 2011–2015 metais.

Mokslinis vadovas

Prof. dr. Laimas Virginijus Jonaitis (Lietuvos sveikatos mokslų univer-sitetas, biomedicinos mokslai, medicina – 06B).

Disertacija ginama Lietuvos sveikatos mokslų universiteto Medicinos akademijos medicinos mokslo krypties taryboje:

Pirmininkas

Prof. dr. Gediminas Kiudelis (Lietuvos sveikatos mokslų universitetas, biomedicinos mokslai, medicina – 06B)

Nariai:

Dr. Juozas Kupčinskas (Lietuvos sveikatos mokslų universitetas, biome-dicinos mokslai, medicina – 06B);

Prof. dr. Antanas Mickevičius (Lietuvos sveikatos mokslų universitetas, biomedicinos mokslai, medicina – 06B);

Prof. habil. dr. Jonas Valantinas (Vilniaus universitetas, biomedicinos mokslai, medicina – 06B);

Doc. dr. Riina Salupere (Tartu universitetas, biomedicinos mokslai, me-dicina – 06B);

Disertacija ginama viešame Lietuvos sveikatos mokslų universiteto Medicinos mokslo krypties tarybos posėdyje 2016 m. gegužės 6 d. 14 val. Lietuvos sveikatos mokslų universiteto ligoninės Kauno klinikų Didžiojoje auditorijoje.

Adresas: Eivenių g. 2, LT- 50161, Kaunas, Lietuva.

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ABBREVIATIONS

ALT – alanine aminotransferase

APRI – aspartate aminotransferase to platelet ratio index AST – aspartate aminotransferase

AUROC – Area under the receiver operating characteristic BMI – body mass index

CSPH – clinically significant portal hypertension F – stage of liver fibrosis

FHVP – free hepatic venous pressure FIB4 – fibrosis 4 score

G – gauge

HBV – hepatitis B virus

HCC – hepatocellular carcinoma HCV – hepatitis C virus

HVPG – hepatic venous pressure gradient INR – international normalized ratio IQR – interquartile range

kPa – kilopascals

NAFLD – non-alcoholic fatty liver disease NASH – non-alcoholic steatohepatitis NPV – negative predictive value PBC – primary biliary cirrhosis PLT – platelet count

PPV – positive predictive value PSC – primary sclerosing cholangitis

ROC curve – receiver operating characteristic curve SD – standard deviation

SPH – severe portal hypertension TE – transient elastography

WHVP – wedged hepatic venous pressure

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INTRODUCTION

Chronic hepatitis is an inflammatory disorder of liver that persists for at least six months and can be caused by different toxic and viral agents or impaired metabolism of various substances. The most common causes of chronic hepatitis are hepatitis B (HBV) and C (HCV) viruses, alcohol abuse and metabolic syndrome. Regardless of the cause, chronic inflammation of liver parenchyma tends to induce liver fibrosis, yet at variable rates depend-ing upon the cause of liver disease [1]. It is generally accepted that at early stages liver fibrosis could be reversible, although the exact point or extent of reversibility remains unclear [2]. In patients with chronic hepatitis, liver fibrosis progresses to cirrhosis stage in a certain period of time, where next to collagen deposition and scarring, the change and distortion of paren-chyma architecture occurs. Liver cirrhosis, as the last stage of fibrosis, has significant influence on the patient’s life expectancy. Patients with liver cirrhosis, along with the impaired liver function, suffer from complications such as hepatocellular carcinoma (HCC), portal hypertension with its manifestations, hepatorenal syndrome, etc. [3]. The staging of liver fibrosis is significant in patients with chronic hepatitis not only for establishing indications or predicting the response to the treatment (especially in viral hepatitis) but also for planning the surveillance if cirrhosis has been diag-nosed. Despite of certain limitations, including invasiveness, sampling variability [4], inter-observer variability [5], liver biopsy is still a primary standard to evaluate liver fibrosis in patients with chronic liver disease. In order to overcome these limitations non-invasive fibrosis tests are developed and gradually introduced into clinical practice. There are many non-invasive direct and indirect liver fibrosis tests with different specificity and sensi-tivity. Some of them are easily applicable in daily practice (aspartate aminotransferase to platelet ratio index (APRI), fibrosis 4 score (FIB4)), while others are more complex (Fibrotest) or require specific devices (tran-sient elastography (TE)). World Health Organization suggests that the most efficient non-invasive tests, to assess the stage of fibrosis in patients with HCV hepatitis, are APRI and FIB4, due to excellent viability, easy repro-ducibility and low cost. However, transient elastography is also recom-mended where it is available [6].

Portal hypertension is one of the most common and important findings in patients with cirrhosis of any aetiology, leading to further complications and decreased patient survival [7, 8]. Direct measurement of portal hypertension is invasive and rarely used in clinical practice due to potential complica-tions. Measurement of hepatic venous pressure gradient (HVPG) is

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established as a primary standard for evaluation of portal vein pressure, particularly in patients with hepatic (sinusoidal) portal hypertension. HVPG of less than 5 mm Hg is considered to be normal, while 6-9 mm Hg has been determined as subclinical portal hypertension [8]. It has been shown that portal pressure can determine different outcomes in patients with portal hypertension. HVPG ≥10 mm Hg is considered as clinically significant portal hypertension (CSPH) and is linked to the risk of oesophageal varices formation [9], clinical decompensation [10], development of hepatocellular carcinoma (HCC) [11] or death after liver resection due to HCC [12]. He-patic venous pressure gradient ≥12 mm Hg reflects severe portal hyper-tension (SPH) and was found to be prognostic for acute variceal bleeding [13]. HVPG ≥16 mm Hg is a predictor of poor survival in cirrhotic patients [13]. Despite of overall safety of HVPG measurement, there are some limitations related to availability of this diagnostic procedure, personal training, experience, increased health care costs and patient discomfort. Therefore, different non-invasive tests that could potentially replace HVPG measurement are under investigation. Liver stiffness could predict portal pressure by measuring physical properties of structural changes emerging in last stages of liver fibrosis; therefore, liver transient elastography could be a potentially accurate tool for stiffness assessment. Spleen elastography has been investigated as a tool to reflect dynamic (vascular) component, next to the structural part, of portal hypertension.

The aim of the study

The aim of the study was to evaluate the role of transient elastography as a non-invasive method to diagnose liver fibrosis and portal hypertension in patients with chronic liver diseases.

The objectives of the study

1. To evaluate the correlation between liver stiffness determined by tran-sient elastography and histological stage of liver fibrosis in patients with chronic liver diseases.

2. To determine optimal liver stiffness cut-off values for assessment of the stage of liver fibrosis.

3. To compare the diagnostic value of liver stiffness with other non-in-vasive tests – APRI (aspartate aminotransferase to platelet ratio index) and FIB4 (fibrosis 4 score) for prediction of the stage of liver fibrosis. 4. To evaluate the correlation between liver stiffness and hepatic venous

pressure gradient in patients with chronic liver diseases. 8

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5. To determine optimal cut-off values of liver stiffness for the assessment of clinically significant portal hypertension and severe portal hyper-tension.

6. To evaluate the correlation between spleen stiffness and hepatic venous pressure gradient in patients with chronic liver diseases.

7. To determine optimal cut-off points of spleen stiffness for assessment of clinically significant portal hypertension and severe portal hypertension.

Novelty of the study

Diagnostic and therapeutic procedures have become less invasive in the last decades and evaluation of liver fibrosis may stand as a perfect evidence of the progress. Since the only verified procedure to evaluate liver fibrosis was liver biopsy, the demand for less invasive method was increasing. As liver ultrasonography is not the most appropriate method to distinguish the stages of liver fibrosis (with the exception of decompensated liver cirrhosis), serum based non-invasive markers have been elaborated [14, 15]. However, the accuracy of these tests is not sufficient. Transient elastography appeared in years 2003–2005 as the non-serum based approach to measure liver fibrosis [16–18]. Multiple studies were conducted in the last decade to verify TE accuracy in the evaluation of liver fibrosis for various liver disea-ses [19]. TE was shown to have sufficient accuracy to determine liver cirrhosis, yet it has displayed significantly worse results in determining lower stages of fibrosis [19]. Taking into consideration the cut-off values for different stages of fibrosis, results vary in between the studies and no equivocal agreement has been reached. The differences between cut-off’s could be explained by different rates of fibrosis stages among the studies [20]. Therefore, some authors suggest that individual cut-off values must be defined at each center, according to different populations with different prevalence of fibrosis stages [21]. The first part of our study was dedicated to define liver fibrosis cut-off values within the population in our region. It is the first study in Lithuania analysing this topic.

Increasing evidence of transient elastography in diagnosis of liver fibrosis provided insights for broadening of TE indications. It is estimated that liver stiffness could reflect portal pressure by measuring physical properties of structural changes emerging in the last stages of liver fibrosis. A small number of studies investigated TE as a tool to determine clinically significant (HVPG>10 mm Hg) or severe portal hypertension (HPVG>12 mm Hg) in patients with various parenchymal liver diseases [22–31]. At the beginning of our study, there were only 6 studies published in this particular

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field. Therefore, the measurement of HVPG and determination of its correlation to non-invasive TE is a novel and original scientific approach.

Another novelty of our research is the measurement of spleen elasto-graphy. Portal hypertension consists of two components – structural and dynamic in its pathogenesis. Spleen elastography has been investigated as a tool to reflect dynamic (vascular) component, along with the structural part, of portal hypertension. The latest trend in the expansion of TE indications is spleen elastography which is aimed to predict portal hypertension. Currently there are only 4 studies published in this field – two of them were available at beginning of our study [32–35]. In our study, we measured spleen stiff-ness alongside with liver stiffstiff-ness, thus contributing to a deeper under-standing of the role of TE in hepatology. Therefore, the second part of our study is substantially innovative and original as investigating liver and spleen TE and HVPG.

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1. REVIEW OF LITERATURE

1.1. Liver fibrosis and portal hypertension

Tissue fibrosis is a highly significant feature of tissue healing, in which inflammation induces extracellular matrix production and proliferation. Regardless of the cause, chronic active liver inflammation induces progress-sion of liver fibrosis; however, the rates depend upon the cause of liver disease [1]. Although liver fibrosis at the early stages is asymptomatic, it may lower patient life expectancy at late stages – especially when cirrhosis occurs [3]. Therefore, the evaluation of liver fibrosis in different chronic liver diseases is an important attribute in patient care [36]. Despite of certain limitations, including invasiveness, sampling variability [4], inter-observer variability [5], liver biopsy is still a primary standard to evaluate liver fibrosis in patients with chronic liver disease. There are several scales for histological grading of fibrosis and inflammatory activity. The most adopted and widely applied scales are METAVIR and Ishak scales, developed for histological evaluation of HCV hepatitis [37, 38]. Due to its simplicity, METAVIR score is used in most of the studies, comparing non-invasive liver fibrosis tests with histological grade of fibrosis [19]. METAVIR score is a two letter – two number histological grading score. It measures activity of necroinflammation and is classified into A0–A3 grades, where A0 represents no activity, A1 – mild activity, A2 – moderate activity, A3 – severe activity. Fibrosis in METAVIR score is divided into F0 – F4 grades, where F0 represents no fibrosis, F1 – stellate enlargement of portal tract without septa formation, F2 – enlargement of portal tract with rare septa formation, F3 – numerous septa formation without cirrhosis, F4 – cirrhosis (Fig. 1.1.1) [38].

As fibrosis progresses, the change and distortion of liver parenchyma architecture occurs with the development of liver cirrhosis, along with colla-gen deposition and scarring. One of the most important features of liver cirrhosis is portal hypertension, which has a significant impact on survival of the patients [7,13]. The pathogenesis of increased portal pressure in cirrhosis stage of chronic liver disease is caused by two mechanisms. The first is called “structural” component of portal hypertension. It is related to blood flow obstruction due to distorted architecture of parenchyma by fib-rosis, nodule formation, angiogenesis and vascular occlusion [8]. The se-cond component in pathogenesis of portal hypertension is called “dynamic” and reflects increased hepatic vascular tone, due to contraction of activated hepatic stellate cells, myofibroblasts or smooth muscle cells around hepatic

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Fig. 1.1.1. METAVIR stages of liver fibrosis (Shimizu, 2012) [39]

sinusoids and the hepatic vasculature [8]. The rationale for elastography in portal pressure determination lies upon the evaluation of structural component of portal hypertension by measuring liver stiffness. As spleen is a part of portal vein system (Fig. 1.1.2), it is expected that evaluation of spleen stiffness could cover both components.

Fig. 1.1.2. Schematic representation of hepatic portal vein system

The spleen connects to portal vein trough splenic vein; thereby the portal veins pressure transmits to spleen, changing its elasticity and stiffness.

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For patients with cirrhosis of any aetiology, it is highly advisable to evaluate portal hypertension and determine various adverse events as well as plan surveillance and treatment [40]. Although direct measurement of portal pressure is invasive and has significant risk of adverse events, HVPG measurement is the best and mostly applied method to assess portal pres-sure. A transducer is introduced into the vein of liver during investigational procedure. The occlusion and free pressure of liver vein is measured and the difference between them is considered as hepatic venous pressure gradient (Fig. 1.1.3). Since variations between different significant pressure cut-offs

Fig. 1.1.3. Procedure of HVPG measurement

A – Pressure measurement in non-occluded right hepatic vein – free hepatic venous pressure (FHVP). D – Pressure measurement in occluded branch of right hepatic vein –

wedged hepatic venous pressure (WHVP). Catheter tip occlusion technique is used to occlude the veins branch. C – Difference between WHVP and FHVP is considered as

hepatic venous pressure gradient.

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are small – for example 10mmHg versus 12 mm Hg – strict compliance to methodology needs to be applied. Detailed technique is described by R.Groszmann et al. [41]. HVPG of less than 5 mm Hg is considered to be normal, while 6-9 mm Hg has been determined as subclinical portal hyper-tension [8]. HVPG ≥10 mm Hg was considered as clinically significant portal hypertension and was linked to the risk of oesophageal varices formation [9], clinical decompensation [10], development of hepatocellular carcinoma (HCC) [11] or death after liver resection due to HCC [12]. Hepatic venous pressure gradient ≥12 mm Hg was considered as severe portal hypertension and was found to be prognostic for acute variceal bleeding [13]. HVPG ≥16 mm Hg was the predictor of poor survival in cirrhotic patients [13].

1.2. Tissue elastography and transient elastography

Since the early stages of modern medicine, elasticity of soft tissue was used to diagnose different pathological conditions, such as breast or thyroid nodules, or enlarged and cirrhotic liver. Palpation of various organs is an inseparable part of medicine propaedeutic and mechanical properties such as elasticity and stiffness are important elements of palpation. However, since part of inspection is based on subjective human sensation, elasticity or stiffness could not provide reliable data if considered separately. Despite of the fact that first data on measurement of tissue elasticity by different acoustic and mechanical methods appeared in 1950s, a major upsurge in development of ultrasound based methods for elasticity imaging started in the late 1980s and early 1990s. Almost all aspects of the present ultrasound based elasticity imaging methods emerged in the studies initiated in that period [42].

Tissue elastography evolved into different elasticity imaging methods, though all of them may be grouped by deformation force type and mechanical response measurement type [42]. Due to its low cost and wide accessibility, mechanical excitation and acoustic radiation force are most widely used methods to provide deformation force to tissue and ultrasound imaging is used to detect mechanical response (usually shear wave propa-gation) to it [42]. Ultrasound based elastography as a branch of elasticity imaging evolved into various elastography methods with different strengths and weaknesses [43]. Some of them are aimed at the improvement of tissue visualisation during ultrasonography procedure [44, 45], while others are aimed at estimation of mechanical properties of target tissue [19, 46]. Liver stiffness quantitative measurement, defining liver fibrosis (and to a lesser extent portal hypertension), is the most widely used indication for

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graphy in gastroenterology with transient elastography as most widely investigated method in this field [19, 42].

Transient elastography is on-axis ultrasound based elasticity measu-rement method with pulse type (50 Hz) mechanical excitation deformation force (Fig. 1.2.1) [42]. The technique was developed into device called FIBROSCAN® by Echosens (Paris, France) and was introduced in 2003 (Fig. 1.2.2) [16]. Depending on the type of transducer, it measures shear wave propagation through tissue (liver or spleen) from 15 to 75 mm and calculates tissue stiffness expressed in kilopascals (kPa) (Fig. 1.2.3) [47]. Despite its wide-spread use, the technology has certain limitations – it does not visualize the tissue, therefore it is impossible to choose the desired place of measurement. It is also limited by measurement depth, so obese patients or patients with ascites could not always be investigated by TE. There are also other issues with application of the TE related to tissue elastography in general. Results are affected by other conditions changing tissue stiffness, such as tissue oedema, steatosis, inflammation, biliary or venous hyper-tension [48–51].

Fig. 1.2.1. Principles of liver transient elastography

Transient elastography probe induces elastic wave using mechanical excitation force. Elastic secondary wave, or so called elastic shear wave, propagates trough the liver. The

speed of elastic shear wave is measured in the region between 2 and 6 cm deep by ultrasound transducer and is converted into stiffness.

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Fig. 1.2.2. Device of transient elastography (FIBROSCAN®)

Fig. 1.2.3. Transient elastography data sheet

Ten measurements of liver stiffness are performed during the procedure and median stiffness as the final results is provided. Interquartile range/median (IQR/Median) <30%

and success rate >60% are considered as a good quality criteria for TE procedure.

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1.3. Liver transient elastography and liver fibrosis

Transient elastography has been under investigation for determining liver fibrosis for more than 10 years [16]. It has been shown that liver stiffness, measured by transient elastography, correlates with liver stiffness [21, 52, 53]. Correlation coefficient varies from 0.74to 87.2 in different studies and it is considered to be a strong or a very strong correlation [21, 52, 54]. The overall AUROC is 0.84 for stage of fibrosis (F) ≥2, 0.89 for F≥3, 0.94 for F=4 [55]. According to meta-analysis by Tsochatzis et al., the overall sensitivity of TE for cirrhosis (F=4) detection has sensitivity of 0.83 and specificity of 0.89 with the mean cut-off point 15 ± 4.1 kPa and the range of values from 9.0 to 26.5 kPa. The overall sensitivity for precirrhosis (F≥3) has sensitivity of 0.82 and specificity of 0.86 with the mean cut-off point 10.2±1.9 kPa and the range of values from 7.3 to 15.4 kPa. The overall sensitivity for advanced fibrosis (F≥2) has sensitivity of 0.79 and specificity of 0.78 with the mean cut-off point 7.3±1.4 kPa and the range of values from 4.0 to 10.1 kPa. The overall sensitivity for F≥1 has sensitivity of 0.78 and specificity of 0.83 with the mean cut-off point 6.5±1.1 kPa and the range of values from 4.9 to 8.8 kPa [19].

Although TE correlates with liver fibrosis, there are some variations of AUROC curves or cut-off values for different stages of liver fibrosis de-pending on the aetiology of liver disease. It is explained by various features that modify liver stiffness, including steatosis, activity of inflammation or biliary hypertension depending on the cause of the disease [48–51].

1.3.1. HCV and HBV hepatitis

Although there is a lack of reliable epidemiological data on HCV and HBV infections in Europe, it is known that prevalence of HCV varies between 0.13% and 3.26% and prevalence of HBV ranges from 0.1–0.7% [56]. Liver cirrhosis occurs in up to 30% of patients chronically infected with HBV and 10–20% with HCV. Estimation of liver fibrosis is recom-mended in these patients not only to evaluate status of liver injury but also to define optimal time for treatment, response to treatment and define surveillance periodicity – especially if cirrhosis is present [6]. According to meta-analysis by Tsochatzis et al., diagnostic accuracy of TE did not significantly differ between hepatitis B and hepatitis C in any stage of fibrosis. The main difference was observed on the cut-off values for the stage of fibrosis with slightly higher values in hepatitis C population. The cut-offs of liver stiffness were 7.6 (5.1–10.1), 10.9 (8.0–15.4), and 15.3 (11.9–26.5) kPa for F≥2, 3, and 4, respectively, in chronic hepatitis C.

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Sensitivity and specificity in F≥2 and F4 subgroups were 0.78, 0.83 and 0.80, 0.90 respectively. The cut-offs of liver stiffness were 7.0 (6.9–7.2), 8.2 (7.3–9.0) and 11.3 (9.0–13.4) kPa for F≥2, 3, and 4, respectively, in chronic hepatitis B. Sensitivity and specificity in F≥2 and F4 subgroups were 0.84, 0.78 and 0.80, 0.89 respectively [19]. There are less data available for the cut-off for F≥1 than other stages of fibrosis, and the cut-offs between 4.8 kPa and 5.3 kPa were observed in hepatitis C patients [21, 57].

1.3.2. Non-alcoholic liver disease

Transient elastography was investigated most widely in viral hepatitis population; therefore, there are less data associated with other aetiologies. Non-alcoholic fatty liver disease (NAFLD) is common in the contemporary society due to broad prevalence of obesity, metabolic syndrome and diabetes [58]. It has a wide range of clinical manifestations from asympto-matic liver steatosis to non-alcoholic steatohepatitis (NASH) [59]. Mortality in NAFLD population has increased with liver related mortality becoming the third after malignancy and cardiovascular disease. Therefore, estimation of liver fibrosis becomes an important factor in surveillance of NAFLD patients [60]. According to meta-analysis by Musso et al., the AUROC is 0.84 for F≥2 and 0.84 for F≥3. The mean cut-off point of 7.0 kPa has sensitivity of 0.79 and specificity of 0.76 for F≥2 detection. The mean cut-off point of 8.7 kPa has sensitivity of 0.94 and specificity of 0.95 for F≥3 detection [59]. AUROC for cirrhosis stage (F=4) was 0.95 – 0.99 [61, 62]. The cut-off point of 10.3 kPa revealed sensitivity of 0.92 and specificity of 0.87 [61]. One of the most significant limitations of transient elastography in NAFLD patients is a substantial failure rate reaching up to 15% of all patients [59].

1.3.3. Alcoholic liver disease

High alcohol consumption is one of the main aetiologies of liver disease and is an important cause of liver associated deaths in Europe [56]. The extent of chronic liver injury in alcohol abusers may be assessed by deter-mining liver fibrosis. In patients with alcoholic liver disease transient elastography has been found to have an AUROC curve of 0.84 for F≥1, 0.91 for F≥2, 0.90 for F≥3 and 0.92 for F=4 [63]. The cut-off values were observed 5.7–5.9 kPa in F≥1, 7.8–8.3 kPa in F≥2, 11–17.5 kPa in F≥3 and 19.5–40.9 kPa in F=4 kPa [63, 64]. Sensitivity, specificity, PPV and NPV were 80%, 90.5%, 93% and 70% for F≥2, and 85.7%, 84.2%, 68.6% and 87.9% for F=4 [63]. The higher cut-offs, especially in cirrhosis group,

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reflect the ongoing alcohol abuse with steatohepatitis and increased inflame-mation impact to liver stiffness.

1.4. Transient elastography and portal hypertension 1.4.1. Liver transient elastography

Up to date, several studies that evaluated liver elastography for determi-nation of clinically significant portal hypertension have been published [26-28, 30, 31, 65–67]. In these studies AUROC curve for determination of CSPH varies between 0.81 and 0.94 with optimal cut-offs between 16.8 and 21.95 kPa with sensitivity and specificity of 73.7–89.7% and 73.7–82.2%, respectively [28, 30, 66, 67]. Nevertheless, applicability of optimal cut-off points is questionable due to the risk of patient misclassification; therefore, cut-off points with 100% sensitivity or specificity are more useful to assess portal hypertension non-invasively, especially in HCC patients referred for surgery to evaluate contraindications for performing liver resection. It was found that liver stiffness >29.0 kPa predicts CSPH with 71.9% sensitivity and 100% specificity [65]. Similar observations were made in other studies where liver stiffness of >21 kPa in HCV patients predicted CSPH with sensitivity of 42% and specificity of 100% [31] or ≥24.2 kPa with sen-sitivity 52.3% and specificity 97.1% [33]. The rule out cut-off point was found to be <16 kPa with sensitivity of 95.4% and specificity of 68.6%.

Few studies investigated liver TE in SPH, where AUROC curve was found to be between 0.79 and 0.92 [22, 23, 30, 67]. The optimal cut-offs to predict SPH varied between 17.6 and 24.2 kPa with sensitivity and spe-cificity of 82.9-94% and 66.6–81%, respectively [22, 23, 30, 67].

1.4.2. Spleen transient elastography

Studies analysing correlation between spleen stiffness measured by transient elastography and HVPG are still scarce. Colechia et al., found a strong correlation between spleen stiffness and HVPG (r – 0.88) [33]. Marginal cut-off points were calculated to rule in or rule out CSPH or SPH. For CSPH cut-off 40.0 kPa had sensitivity of 98.5% and specificity of 74.3% and cut-off 52.8 kPa 76.9% and 97.1%, respectively. For SPH cut-off 41.3 kPa had sensitivity of 98.1% and specificity of 67.4% and cut-off 55.0 kPa – 72.2% and 97.8%, respectively. Another study observed no signi-ficant differences in spleen stiffness measured by TE between groups

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analysing CSPH or SPH [34], although the study was underpowered in-cluding only 35 patients with three patients without CSPH.

1.5. Serum based non-invasive liver fibrosis tests

To overcome the limitations of liver biopsy, especially the invasiveness, various serum-based formulas were tested. The rationale behind it was the notion that different compounds of liver metabolism in blood were changing during the evolution of liver fibrosis. All serologic liver fibrosis tests could be divided into indirect and direct serum fibrosis markers [68]. Direct markers represented various molecular aspects of liver fibrosis pathogenesis and reflected extracellular matrix metabolism, while indirect markers in-cluded various serologic biochemical tests altered by damaged liver function or liver fibrosis [68]. Direct serum based liver markers were represented by collagen type IV [69], hyaluronic acid [70] or by more complex markers like FibroSpect II [70, 71] or Enhanced Liver Fibrosis panel [72]. Indirect liver fibrosis markers were represented by APRI, FIB4, FibroTest or FibroSure panels [15, 73–75]. Nevertheless, most of these tests were too complex or too expensive to be applied in everyday use. Consequently, only APRI and FIB4 were suggested as best serum based non-invasive tests due to excellent viability, easy reproducibility and low cost by World Health Organization to assess the stage of fibrosis in HCV hepatitis [6].

APRI is a simple, easily reproducible non-invasive test for detection of liver fibrosis first described by Wai et al. in 2003 [14]. APRI score includes AST and platelet count (PLT) to determine the stage of fibrosis. It is calculated using the following formula: (AST/upper limit of normal AST)/ platelet count (109)×100 [14]. As noted in the last meta-analysis, the range of cut-off values of APRI for different stages of fibrosis are rather wide [76]. The range for ≥2 stage of fibrosis varies from 0.5 to 1.5 with the optimal threshold of 0.7 with 77% sensitivity and 72% specificity. The APRI cut-off range for fibrosis stage ≥3 varies from 0.5 to 2 with optimal threshold 1 with 61% sensitivity and 64% specificity. The recommended cut-offs for F4 stage were 1 and 2 with sensitivity and specificity 76%, 72% and 46%, 91% respectively.

FIB4 is described as simple but more complex score to predict liver fibrosis. It includes age, AST, ALT and platelet count to determine liver fibrosis and is calculated using the following formula: (age [yr] × AST [U/L]) / ((PLT [10(9)/L]) × (ALT [U/L])^(1/2)) [77]. Few studies were performed in patients with HCV infection to establish the best threshold for detection of liver fibrosis. Cut-off of 1.26 for F≥2 showed sensitivity and specificity of 64% and 75%, respectively [78], while lower threshold of 1

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had lower sensitivity and specificity (71% and 50%) [79]. For F≥3 optimal threshold varied between 1.45 and 1.81 with sensitivity 74.3%, 74% and specificity 80.1%, 77% respectively [15,79,80]. The cut-off 2.25 had sen-sitivity and specificity of 82% and 83% respectively for discriminating cirrhosis from other fibrosis stages [79].

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2. METHODS

2.1. Ethics

The study was approved by Kaunas regional Ethics Committee for Biomedical Research (No. BE-2-26). All patients have signed an informed consent form before inclusion.

2.2. Patient selection criteria 2.1.1 Inclusion criteria:

• Patients with chronic parenchymal liver disease regardless of aetio-logy, at any suspected stage of fibrosis, who were scheduled for liver biopsy and/or HVPG measurement;

• Patients with focal liver disease of any aetiology, who were scheduled for focal lesion biopsy along with parenchyma biopsy.

2.2.2 Exclusion criteria:

• Focal liver lesion biopsy without parenchymal biopsy or HVPG measurement;

• Focal liver disease with outspread tumour in the liver; • Portal or hepatic vein thrombosis;

• Acute or acute on chronic hepatitis of any aetiology;

• Use of medications to treat portal hypertension in HVPG analysis group.

2.3. Design of the study 2.3.1 Target population

Our study included all patients with chronic liver disease who were referred to Gastroenterology department for liver biopsy and/or HVPG measurement in 2013–2015. All patients included into this study were re-ferred by referring gastroenterologists for liver biopsy or HVPG measu-rement with or without transjugular liver biopsy. Decision to measure HVPG or to obtain liver biopsy was made clinically by gastroenterologists and was not influenced by our research.

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2.3.2 Selection and flow-chart

Patients that meet inclusion criteria completed survey for medical anam-nestic data had objective clinical examination and abdominal ultrasound to evaluate exclusion criteria. In the absence of exclusion criteria, additional demographical and clinical data was collected. Laboratory investtigations were also performed before liver biopsy or HVPG measurement. Liver and spleen (in case of HVPG measurement) TE was performed to patients included into study before liver biopsy or HVPG measurement. Patients with unsuccessful liver transient elastography were considered as drop-outs. Collected data is summarized in Tables 2.3.2.1 and 2.3.2.2. The study flow chart is presented in Fig. 2.3.2.1.

Table 2.3.2.1. Baseline clinical data collected during the study

Demographical data Clinical data Laboratory data Gender

Age

Height Weight

Cause of chronic liver disease

Complete blood count Bilirubin

Liver enzymes Albumin

Prothrombin time ALT, AST AST – aspartate aminotransferase, ALT – alanine aminotransferase.

Table 2.3.2.2. Data acquired by instrumental or interventional methods

Liver and spleen TE data Liver biopsy data Other data Median

IQR IQR/median SR

Grade of fibrosis by METAVIR Number of portal tracts in specimen

HVPG Spleen size

IQR – interquartile range, SR – success rate, HVPG – hepatic venous pressure gradient.

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Fig. 2.3.2.1. Flow chart of the study

2.3.3 Transient elastography

Liver stiffness was measured using FIBROSCAN® (Echosens, Paris, France) device. Patients were in fasting state. Procedure was performed in accordance with manufacturer recommendations. Interquartile range / me-dian <30% and success rate >60% was considered as a good quality criteria for transient elastography procedure. Ten successful measurements were performed for each patient.

Assessment of spleen stiffness was performed using the same metho-dology as for liver elastography. The quality criterion (interquartile range/ median, success rate and number of successful measurements) for spleen stiffness was the same as for liver stiffness. If typical elastography picture could not be found using FIBROSCAN device, exact point for spleen stiff-ness measurement was found using Toshiba Xario 200 ultrasound device (Toshiba Medical Systems Corporation, Japan).

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2.3.4 Serum based non-invasive tests

APRI was calculated using the following formula: (AST/upper limit of normal AST)/platelet count (109) × 100 [14] and FIB4 using the following: (age [yr] × AST [U/L]) / ((PLT [109]) × (ALT [U/L])^(1/2)) [77]. Upper limits for ALT and AST were 45 U/l, 35 U/l respectively (Fig. 2.3.4.1) [77, 14].

Fig. 2.3.4.1. The formulas of APRI and FIB4 scores

2.3.5 Liver biopsy

Liver biopsy was obtained using spring-loaded core biopsy instrument with 22 mm shooting length. 14G biopsy needle was used to obtain liver tissue (Fig. 2.3.5.1). Liver biopsy specimen was placed in formalin and processed routinely by the pathologists. Histological fibrosis grade was evaluated using METAVIR score by the expert pathologist. Pathologist was blinded to the results of non-invasive fibrosis tests.

Fig. 2.35.1. Spring-loaded core biopsy instrument with 14G biopsy needle

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2.3.6 Hepatic venous pressure gradient

HVPG was measured in fasting state. None of the patients have received medications affecting portal pressure before the HVPG measurement. The standard criteria for HVPG measurement was applied [41]. HPVG was measured using catheter wedge technique by experienced radiologist apply-ing judkins right 6fr catheter (Boston Scientific, USA, Marlborough). Right hepatic vein was selectively cannulated and catheter position was confirmed by vein angiogram. The occluded position of the catheter was checked by absence of reflux after the injection of 2 mL of a contrast medium and appearance of sinusoidogram (Infinity R50, Drager, Germany). The mean of at least 3 readings was taken for further analysis. If the difference between the readings was greater than 1 mmHg, all the previous recordings were cancelled and new readings were taken. Radiologist was blinded to the clinical data and liver/spleen stiffness results. Collected data acquired by instrumental or interventional methods are summarized in Table 2.3.2.2.

2.3.7 Calculation of the sample size and study power

Calculation of the sample size and study power was made using STATISTICA 6.0 software by StatSoft Inc. (Tulsa, USA). Two samples t-test for independent samples were used. Means and case numbers of independent samples with standard deviation of the whole population were used. In case the distribution of liver stiffness across groups was not normal and medians or interquartile range (IQR) were available, central limit theorem was still applied. In this case, it was assumed that distribution was highly skewed and 10% of sample size was added. As the most important points of HVPG were 10 mm Hg and 12 mm Hg, calculations for HVPG<10 mm Hg versus HVPG≥10 mm Hg and HVPG<12 mm Hg versus HVPG≥12 mm Hg groups were made. We calculated power and sample size for F0/F1 versus F2/F3/F4 and F0/F1/F2/F3 versus F4 groups, as these liver fibrosis points were most important in clinical setting for treatment and surveillance planning.

2.3.7.1 HVPG < 10 mm Hg versus HVPG ≥ 10 mm Hg

Studies by M. Lemoine et al. and C. Bureau et al. were used to calculate power and minimal N of the sample for HVPG<10 mm Hg versus HVPG≥10 mm Hg [26, 28]. The data are presented in Table 2.3.7.1.

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Table 2.3.7.1. HVPG<10 mm Hg versus HVPG≥10 mm Hg M. Lemoine et al. (26) Liver stiffness <10 mm Hg ≥10 mm Hg Power calculation Required N per group if power is equal to 1 Required N per group if power is equal to 0.95 N 18 74 1.0 38 16 Mean in kPa 18.4 43.1 SD 8.8 21.8 SD of population 18.5 C. Bureau et al. (28) N 74 76 1.0 53 22 Median in kPa 7.9 43.3 IQR of population (Q3 - Q1) 31.1

SD – standard deviation, kPa – kilopascals, IQR – interquartile range.

2.3.7.2 HVPG < 12 mm Hg versus HVPG ≥ 12 mm Hg

Paper by M. Sánchez-Conde et al., was used to calculate power and minimal N of the sample for HVPG < 12 mm Hg versus HVPG ≥ 12 mm Hg [23]. The data are presented in Table 2.3.7.2.

Table 2.3.7.2. HVPG<12 mm Hg versus HVPG≥12 mm Hg

M. Sánchez-Conde et al. [23]

Liver stiffness <12 mm Hg ≥12 mm Hg Power calculation

Required N per group if power is equal to 0,8 N 15.0 23.0 0.4 49 Median in kPa 21.1 39.1 IQR (Q3-Q1) 11.9 38.0

IQR – interquartile range, Q3 – third quartile, Q1– first quartile, kPa – kilopascals.

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According to calculations, it was assumed that 100 patients are sufficient to observe significant differences between HVPG of <10 mm Hg and HVPG≥10 mm Hg with the power between 0.95 and 1, depending on patient volume distribution between groups. Considering the same calculations, it was assumed that 100 patients is a sufficient number to observe significant differences between HVPG of <12 mm Hg and HVPG≥12 mm Hg with the power of 0.8. With respect to low number of cases in a paper by M.

Sán-chez-Conde et al. which was used to calculate sample size and power, we

anticipated that real power with planned sample size is more similar to HVPG<10 mm Hg versus HVPG≥10 mm Hg group.

2.3.7.3 F0/F1 versus F2/F3/F4 and F0/F1/F2/F3 versus F4

One of the largest studies conducted by M. Lupsor Platon et al. that evaluated TE correlation with liver fibrosis has been used to calculate power and minimal N of the sample for F0/F1 versus F2/F3/F4 and F0/F1/F2/F3 versus F4 groups [21]. Calculations are presented in Tables 2.3.7.3 and 2.3.7.4.

Table 2.3.7.3. Sample calculation for F0/F1 versus F2/F3/F4

M. Lupsor Platon et al. [21]

Liver stiffness F0/F1 F2/F3/F4 Power

calculation

Required N per group if power is equal to 1 N 426 776 1 74 Mean 5.9 19.4 SD 1.97 15.8 SD pop 14.3

SD – standard deviation, SD pop – standard deviation of whole population, F – stage of fibrosis.

Table 2.3.7.4. Sample calculation for F0/F1/F2/F3 versus F4

M. Lupsor Platon et al. [21]

Liver stiffness F0/F1/F2/F3 F4 Power

calculation

Required N per group if power is equal to 1 N 828 374 1 27 Mean 7.6 30.2 SD 4.1 16.3 SD pop 14.3

SD – standard deviation, SD pop – standard deviation of whole population, F – stage of fibrosis.

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Based on the calculations, it was assumed that 150 patients is a sufficient number to observe significant differences between groups with the power of 1.

2.3.8 Power calculation of the study

We conducted power calculations of our study after all patients were included. The results are presented in Table 2.3.8.1.

Table 2.3.8.1. Power calculation of our study HVPG<10 mm Hg versus HVPG≥10 mm Hg N1 = 29 N2 = 78 Mean1 = 11.2 Mean2 = 40.1 SD = 22.4 Power = 1 HVPG<12 mm Hg versus HVPG≥12 mm Hg N1 = 40 N2 = 67 Mean1 = 14.2 Mean2 = 43.0 SD = 22.4 Power = 1 F0/F1 versus F2/F3/F4 N1 = 111 N2 = 99 Mean1 = 6.79 Mean2 = 20.7 SD = 13.7 Power = 1 F0/F1/F2/F3 versus F4 N1 = 164 N2 = 46 Mean1 = 8.3 Mean2 = 31.2 SD = 13.7 Power = 1

HPVG – hepatic venous pressure gradient, F – stage of fibrosis.

2.3.9 Statistical analysis

Statistical analysis was performed using statistical software SPSS 20.0. Kolmogorov–Smirnov test was used to check data normality. For descript-tive statistics frequencies, means, medians and standard deviations were calculated. Liver fibrosis evaluated by METAVIR score was compared with liver stiffness expressed in kPa using non-parametric Spearman correlation. According to METAVIR score patients were categorised into:

1. F0 versus F1/F2/F3/F4, (F≥1) 2. F0/F1 vs F2/F3/F4, (F≥2) 3. F0/F1/F2 vs F3/F4, (F≥3) 4. F0/F1/F2/F3 vs F4, (F=4)

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HVPG scores were compared with liver and spleen stiffness expressed in kPa using non-parametric Spearman correlation. Based on HVPG, patients were categorized into groups with and without CSPH or into those with and without SPH. Comparisons between patients with and without CSPH or SPH were made using Mann-Whitney Test. Areas under the receiver operat-ing characteristic curve were calculated and points for best specificity and sensitivity established, positive predictive value (PPV), negative predictive value (NPV) and accuracy were calculated. P-values less than 0.05 were considered to be statistically significant.

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3. RESULTS

3.1. Fibrosis and non-invasive tests

Baseline demographic and biochemical characteristics are represented in Table 3.1.1. The mean age was 47.6 years with similar gender distribution. HCV related chronic liver disease was predominant (66.7%) and most patients had compensated liver disease (Child Pugh grade A). Distribution of aetiology is shown in Table 3.1.2. As determined by the Kolmogorov– Smirnov test, the distribution of liver stiffness, APRI and FIB4 were not normal. Spearman correlation analysis revealed that TE, APRI and FIB4 correlated with the stage of fibrosis. Strong correlation of TE (r=0.734, p<0.01) and FIB4 (r=0.654, p<0.01) with stage of fibrosis was found. APRI correlation with the stage of liver fibrosis is moderate (r=0.551, p<0.01). Using the Fisher r-to-z transformation, significance of the difference between TE and FIB4 correlation coefficients, as well as TE and APRI, was calculated. We did not find significant difference between TE and FIB4 correlation coefficients (p=0.11). TE correlation coefficient was statistically higher than APRI correlation coefficient (p=0.001). Comparisons of mean scores of TE, APRI and FIB4 in different stages of fibrosis are presented in Figs. 3.1.1–3.1.3 and Tables 3.1.3–3.1.5.

All patients were categorised into groups based on liver fibrosis: 1. F0 versus F1/F2/F3/F4 (F≥1), 46 versus 164 patients.

2. F0/F1 vs F2/F3/F4 (F≥2), 109 versus 101 patients. 3. F0/F1/F2 vs F3/F4 (F≥3), 129 versus 81 patients. 4. F0/F1/F2/F3 vs F4 (F=4), 146 versus 64 patients.

The ROC curve analysis was performed. ROC curves for each category of fibrosis are presented in Figs. 3.1.4–3.1.7 and AUROC data in Tables 3.1.6, 3.1.8, 3.1.10, 3.1.12.

Based on coordinate points of the ROC curve, the values for different groups of fibrosis stage with the highest sensitivity and specificity (optimal cut-off points) were chosen. According to optimal cut-off points negative predictive values (NPV), positive predictive values (PPV) and accuracy were calculated and are represented in Tables 3.1.7, 3.1.9, 3.1.11, 3.1.13.

Comparison between AUROC curves of TE and APRI or FIB4 was made and p-values depicted in Table 3.1.14.

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Table 3.1.1. Demographic, clinical and laboratory characteristicsof the patients Patients (n=210) Gender, N (%) Female Male 91 (43.3) 119 (56.7)

Age, years, mean (± SD) 47.6 (±12.3)

BMI, kg/m², mean (± SD) 26.0 (±4.4)

Platelet count, /Lx109 , mean (± SD) 182.4 (±73.6)

ALT, IU/L, mean (± SD) 100.2 (±86.7)

AST, IU/L, mean (± SD) 80.6 (±71.9)

INR, mean (± SD) 1.07 (±0.1)

Bilirubin µmol/l, mean (± SD) 25.3 (±30.0) Child – Pugh score, N (%)

A B C 192 (91.4) 18 (8.6) 0 (0) Portal tracts number, mean (± SD) 13.9 (±5.1) Liver fibrosis stage, N (%)

F0 F1 F2 F3 F4 30 (14.3) 81 (38.6) 33 (15.7) 20 (9.5) 46 (21.9)

SD – standard deviation, BMI – body mass index, AST – aspartate aminotransferase, ALT – alanine aminotransferase, INR – international normalized ratio, F – stage of fibrosis.

Table 3.1.2. Distribution of chronic liver disease aetiology Aetiology of chronic liver

disease N (%)

Age, years, mean (±SD) Male/Female, N/N (%) HCV 140 (66.7) 47.0 (±11.3) 90/50 (64.3/35.7) HBV 19 (9.0) 42.9 (±13.8) 12/7 (63.2/36.8) Alcohol 10 (4.8) 50.6 (±9.8) 3/7 (30/70) Cryptogenic 8 (3.8) 44.7 (±8.4) 4/4 (50/50) Non-alcoholic steatohepatitis 8 (3.8) 54.7 (±13.1) 3/5 (37.5/62.5) PBC 7 (3.3) 56.5 (±11.7) 0/7 (0/100) Autoimmune 6 (2.9) 45.3 (±17.1) 0/6 (0/100) Wilson disease 5 (2.4) 38.6 (±15.7) 0/5 (0/100) Hemochromatosis 5 (2.4) 61.0 (±12.1) 5/0 (100/0) PSC 2 (1.0) 28.5 (±9.1) 2/0 (100/0)

HCV – hepatitis C virus, HBV – hepatitis B virus, PBC – primary biliary cirrhosis, PSC – primary sclerosing cholangitis

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Fig. 3.1.1. Comparison of TE means between stages of liver fibrosis

Table 3.1.3. P-values between TE means of different fibrosis stages

F 0 1 2 3 4 0 0.616 0.78 0.001 0.001 1 0.616 0.434 0.002 0.001 2 0.078 0.434 0.041 0.001 3 0.001 0.002 0.041 0.001 4 0.001 0.001 0.001 0.001

Comparison between means of liver stiffness, measured by transient elastography, of different stages of liver fibrosis was made and p-values represented. P-values <0.05 are marked bold.

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Fig. 3.1.2. Comparison of FIB4 means between stages of liver fibrosis

Table 3.1.4. P-values between FIB4 means of different fibrosis stages

F 0 1 2 3 4 0 0.429 0.630 0.202 0.001 1 0.429 0.468 0.504 0.001 2 0.063 0.468 0.999 0.001 3 0.202 0.504 0.999 0.301 4 0.001 0.001 0.001 0.301

Comparison between means of FIB4 score of different stages of liver fibrosis was made and p-values represented. P-values < 0.05 are marked bold.

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Fig. 3.1.3. Comparison of APRI means between stages of liver fibrosis

Table 3.1.5. P-values between APRI means of different fibrosis stages

Stage of fibrosis 0 1 2 3 4 0 0.284 0.96 0.319 0.001 1 0.284 0.987 0.969 0.001 2 0.096 0.987 1 0.027 3 0.319 0.969 1 0.267 4 0.001 0.001 0.027 0.267

Comparison between means of APRI of different stages of liver fibrosis was made and p-values represented. P-values < 0.05 are marked bold.

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Fig. 3.1.4. ROC curves for F≥1.

APRI – aspartate aminotransferase to platelet ratio index, FIB4 – fibrosis 4 score.

Table 3.1.6. AUROC data of TE, FIB4 and APRI for all groups of liver

fibrosis stages

Area under the curve Std. error P-value

F≥1 (F0 vs. F1/F2/F3/F4)

TE 0.818 0.042 <0.001

FIB4 0.781 0.044 <0.001

APRI 0.779 0.047 <0.001

TE – transient elastography.

Table 3.1.7. Cut-off values for liver fibrosis ≥1 Fibrosis stage Method Cut- off Sensitivity, % Specificity, % PPV, % NPV, % Accuracy, % ≥1 TE, kPa 5.4 85.0 63.3 93.2 41.3 81.9 FIB4 0.98 78.8 66.6 93.4 34.4 77.1 APRI 0.58 67.7 66.6 92.4 25.6 67.6 TE – transient elastography in kPa.

APRI – aspartate aminotransferase to platelet ratio index, FIB4 – fibrosis 4 score, PPV – positive predictive value NPV – negative predictive value.

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Fig. 3.1.5. ROC curves for F≥2.

APRI = aspartate aminotransferase to platelet ratio index, FIB4 = fibrosis 4 score

fibrosis stages

F≥2 (F0/F1 vs. F2/F3/F4)

TE 0.858 0.026 <0.001

FIB4 0.832 0.029 <0.001

APRI 0.766 0.034 <0.001

APRI – aspartate aminotransferase to platelet ratio index, FIB4 – fibrosis 4 score.

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Fig. 3.1.6. ROC curves for F≥3

APRI = aspartate aminotransferase to platelet ratio index, FIB4 = fibrosis 4 score.

fibrosis stages

F≥3 (F0/F1/F2 vs. F3/F4)

TE 0.941 0.018 <0.001

FIB4 0.857 0.034 <0.001

APRI 0.789 0.029 <0.001

APRI – aspartate aminotransferase to platelet ratio index, FIB4 – fibrosis 4 score.

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Fig. 3.1.7. ROC curves for F=4

APRI = aspartate aminotransferase to platelet ratio index, FIB4 = fibrosis 4 score

fibrosis stages

F=4 (F0/F1/F2/F3 vs. F4)

TE 0.959 0.012 <0.001

FIB4 0.912 0.021 <0.001

APRI 0.840 0.031 <0.001

Table 3.1.13. Cut-off values for liver cirrhosis (F=4) Fibrosis stage Method Cut- off Sensitivity, % Specificity, % PPV, % NPV, % Accuracy, % =4 TE, kPa 12.1 95.6 87.8 68.7 98.6 89.5 FIB4 3.07 82.6 85.9 62.2 94.6 85.2 APRI 1.4 76.0 84.1 57.3 92.6 82.3 TE – transient elastography in kPa.

APRI – aspartate aminotransferase to platelet ratio index, FIB4 – fibrosis 4 score, PPV – positive predictive value, NPV – negative predictive value.

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Table 3.1.14. Comparison between AUROC curves of TE and APRI or FIB4

F≥1 F≥2 F≥3 F=4

TE vs APRI p=0.44 p=0.03 p=0.0003 p=0.006

TE vs FIB4 p=0.46 p=0.51 p=0.02 p=0.10

Comparison between AUROC curves of TE and APRI or FIB4 was made and p-values represented. P-values < 0.05 are marked bold.

3.2. Subgroup analysis of HCV infected patients

The most notable difference in HCV infected group compared to overall study population is the increase of AUROC curves, and as a consequence in specificities, sensitivities, NPV, PPV and accuracies, for all tests in all stages of liver fibrosis. Cut-off values of TE remained unchanged.

The demographic data, cut-offs, specificities, sensitivities, NPV, PPV and accuracies of TE, APRI and FIB4 in HCV hepatitis subgroup are presented in table 1 and table 2 of the publication by R. Zykus et al. [54]. Additionally, comparison of AUROC curves for HCV infected patients is shown in Table 3.2.1.

Table 3.2.1. Comparison between AUROC curves of TE and APRI or FIB4

in patients with HCV hepatitis

F≥1 F≥2 F≥3 F=4

TE vs APRI p=0.2 p=0.1 p=0.004 p=0.06

TE vs FIB4 p=0.055 p=0.6 p=0.08 p=0.4

Data is presented as p-value. TE – transient elastography,

3.2.1.Transient elastography and hepatic venous pressure gradient

Strong correlation with HVPG was found for liver TE (r – 0.75, p<0.001) and for spleen TE (r – 0.62, p<0.001). The cut-off points with sensitivity, specificity, PPV, NPV and accuracy for clinically significant portal hyper-tension and severe portal hyperhyper-tension are presented in Table 3.2.1.1. The rule in and rule out cut-off points of liver TE for clinically significant portal hypertension and severe portal hypertension are presented in Table 3.2.1.2. The demographic data, comparison between means, cut-off points, spe-cificities, sensitivities, NPV, PPV and are presented in the publication by R. Zykus et al. [81].

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Table 3.2.1.1. Optimal cut-offs of liver and spleen stiffness for prediction

of clinically significant (≥10 mm Hg) and severe (≥12 mm Hg) portal hypertension HVPG Method Cut-off, kPa Sensitivity, % Specificity, % PPV, % NPV, % Accuracy, % ≥10 mm Hg Liver TE 17.4 88.0 87.5 95.8 74.2 88.7 Spleen TE 47.6 77.3 79.2 92.0 52.7 77.7 ≥12 mmHg Liver TE 20.6 82.8 80.0 88.8 75.0 83.1 Spleen TE 50.7 78.1 77.1 86.2 65.8 77.7 HVPG – hepatic venous pressure gradient, TE – transient elastography,

PPV – positive predictive value, NPV – negative predictive value.

Table 3.2.1.2. Rule in and rule out cut-offs of liver stiffness for prediction

of clinically significant (≥10 mm Hg) and severe (≥12 mm Hg) portal hypertension

HVPG Method Cut-off, kPa Sensitivity, % Specificity, %

≥10mmHg Liver TE 11.4 21.9 100 74.4 55.2 100 ≥12mmHg Liver TE 12.1 35.0 100 58.2 50.0 100 HVPG – hepatic venous pressure gradient, TE – transient elastography.

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4. DISCUSSION

4.1. Transient elastography and fibrosis

Our results clearly show that transient elastography has an appropriate specificity and sensitivity to determine histological stages of liver fibrosis, especially in the higher stages. These observations are evident in the AUROC curves, where areas for F4 and ≥F3 are 0.950 and 0.941, respect-tively. AUROC curve close to 1 reflects reliable diagnostic test [82]; therefore, liver TE is a reliable non-invasive test for diagnosing cirrhosis and precirrhotic stage. AUROC curves for lower stages of liver fibrosis are less accurate with 0.858 and 0.818 for F≥2 and F≥1, respectively. Our data is comparable with the results of last meta-analysis by Tsochatzis et al.[19]. According to latter meta-analysis the cut-offs of liver stiffness were 7.6 (5.1–10.1), 10.9 (8.0– 15.4), and 15.3 (11.9–26.5) kPa for F ≥2, 3, and 4, respectively, in chronic hepatitis C. Sensitivity and specificity in F≥2 and F4 subgroups were 78%, 83% and 80%, 90%, respectively [19]. The cut-offs, sensitivity and specificity in our study are comparable with the results of latter meta-analysis. A wide range of different cut-offs could be explained by different variability in stages of fibrosis across different studies [20]. There are less data available on the cut-off values for F≥1, but cut-offs ranging between 4,8kPa and 5,3kPa were observed [21, 57]. Reported data is similar to our findings.

Based on our data analysis, it is evident that statistical significance between fibrosis stages is higher in HCV patient subgroup than in overall population of our study. The same findings can be deduced from ROC curves, where areas are greater for all fibrosis groups in HCV population. Most significant difference could be observed in F≥1 group, where AUROC curve increased from 0.818 to 0.974. It is known that inflammation can change liver stiffness dramatically [48]; therefore, the difference between AUROC curves in HCV and overall population could be explained by the different inflammatory activity in patients with various liver diseases. It is particularly relevant for patients with alcoholic hepatitis or HBV hepatitis, where inflammatory activity may increase during flares of the disease or due to persistent consumption of alcohol.

Although AUROC curves for the groups of lower stages of fibrosis are less distinguished, it is evident that PPV for F ≥1 is high and reaches 93.2%. This data indicates that with the help of TE a substantial proportion of patients may avoid unnecessary interventional investigations in everyday clinical setting.

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In conclusion, liver TE is a reliable diagnostic tool for diagnosing precirrhosis, cirrhosis and patients without any liver fibrosis. Liver TE could replace liver biopsy in these groups of patients and HCV hepatitis subgroup in particular. In intermediate stages of fibrosis TE is less accurate and may lead to patient misclassification.

4.2. Transient elastography versus serum based tests

The need for non-invasive estimation of liver fibrosis led to the develop-ment of simple serum based liver fibrosis tests, as they are easy to perform in clinical setting. APRI and FIB4 were developed almost in parallel with transient elastography and showed promising results [14, 78]. As TE is more expensive and less accessible, it became questionable if this is the most efficient way of determining liver fibrosis. Later studies showed that TE is more efficient in determining liver fibrosis especially in the higher stages [18, 83, 84]. Our study data revealed similar results with higher AUROC curve for TE in all groups of liver fibrosis stages. It is most evident in F4 and F≥3 stages, where AUROC curve for TE was 0.959 versus 0.912 for FIB4 (p=0.1) and 0.840 for APRI (p<0.01) in F4 group. In F≥3 group TE had AUROC curve of 0.941 versus 0.857 for FIB4 (p=0.02) and 0.789 for APRI (<0.01). The difference between AUROC curves was less pronounced in HCV group; however, TE versus APRI for F≥3 remained statistically different. Nevertheless, the largest values of AUROC curves were found for TE test. This observation could be also explained by the effect of inflame-mation to non-invasive tests in various aetiologies of liver disease as discussed above. APRI and FIB4 are very susceptible tests because direct serum markers of liver parenchyma injury – ALT and AST, are included in formulas of both tests [14, 77].

4.3. Transient elastography and hepatic venous pressure gradient

Cirrhotic patients with the end stage liver disease have worse survival and increased complication rates. They are related not only to liver fibrosis and subsequent insufficiency of liver function, but also to portal hyper-tension causing life-threatening complications such as variceal bleeding or ascites with spontaneous bacterial peritonitis. As noted in the review section, HVPG measurement has been proven to predict various outcomes in this group of patients [9, 10, 12, 13].

Up to date, several studies evaluated liver elastography for determination of clinically significant portal hypertension [26–28, 30, 31, 65–67]. AUROC curve for determination of CSPH varies between 0.81 and 0.94 with optimal cut-offs between 16.8 and 21.95 kPa with sensitivity and specificity of

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73.7–89.7% and 73.7-82.2%, respectively [28, 30, 66, 67]. Both AUROC curves and optimal cut-offs observed by other authors are comparable with our data that displays AUROC curve of 0.949 and optimal cut-off 17.4 kPa with 88% sensitivity and 87.5% specificity. The tests with AUROC curves close to 1 represents excellent reliability as medical tests [82, 85].

Nevertheless, applicability of optimal cut-off points is questionable due to the risk of patient misclassification. Therefore, cut-off points with 100% sensitivity or specificity (rule-out or rule-in) could be more useful to assess portal hypertension non-invasively. In clinical setting, the benefit of optimal versus marginal cut-off points depends on the expectations and goals of the test. If the test is used for patient risk stratification and helps identifying those with the need for interventional testing (e.g. endoscopy to evaluate oesophageal varices) the optimal cut-offs should be accurate enough. Yet, if the test is considered to replace interventional testing, as HVPG measu-rement or endoscopy, the rule-in or rule out cut-off points are better to discern target group without the need for further testing. This is extremely important in HCC patients referred for surgery in evaluating contraindi-cations for liver resection, where HVPG ≥10mmHg is a solid indicator of higher mortality and liver dysfunction after liver resection [12]. Therefore, by having rule-in and rule-out cut-off points, HVPG measurement could be restricted only to patients in “grey zone”, between rule-in and rule-out points, avoiding unnecessary HVPG measurement if TE measurement is outside the “grey zone” (Fig. 4.3.1).

Fig. 4.3.1. Grey zones of liver stiffness at predicting portal hypertension

Inside grey zones, there is a risk of patient’s misclassification as having or not having portal hypertension. Patients outside grey zones could be identified, as having or not having portal

hypertension with 100% specificity or sensityvity. 44

THE ROLE OF TRANSIENT ELASTOGRAPHY IN THE DIAGNOSIS OF LIVER FIBROSIS AND PORTAL HYPERTENSION

Romanas Zykus