Non-invasive methods for the assessment of liver fibrosis and steatosis are replacing invasive liver biopsy due to patient wariness and the low but ever-present morbidity of biopsies. The use of non-invasive markers is also increasing because clinical questions concerning the presence or absence of steatosis, fibrosis and cirrhosis as well as treatment monitoring and follow-up can be sufficiently answered by these tests and procedures. Today, despite the dogma of the biopsy being the gold standard, the use of non-invasive liver fibrosis detection vastly outnumbers biopsies in chronic liver diseases. Non-invasive tests have problems in discriminating accurately between early stages of fibrosis, i.e., F0-F2. Notwithstanding, non-invasive markers can be used as it primarily relevant to discriminate between early stages and advanced fibrosis in clinical practice.
In addition, non-invasive tests carry the potential of being used as screening tools in population-based studies and can detect fibrosis even in individuals with normal liver function tests. Non-invasive markers should be able to reliably identify liver cirrhosis in order to initiate further diagnostic procedures to exclude portal hypertension and to intensify surveillance strategies. Non-invasive strategies are also warranted for monitoring the disease while on therapy and ideally document the regression of fibrosis during follow-up.
Non-invasiveness for the detection of fibrosis has become reality in clinical practice and has been approved for clinical studies but for hepatologists fibrosis assessment is only one puzzle piece and more information is needed. Other endemic conditions such as fatty liver disease with or without inflammatory changes and or fibrosis increase the need for other non-invasive tests that also provide information on hepatic fat contents and inflammation. Whereas ultrasound-based methods such as the controlled attenuation parameter can be used for the rapid and easy assessment of steatosis, specific non-invasive test to classify the mode and extend of inflammation in the liver are still missing.
With most experts agreeing that non-invasive techniques do not replace liver biopsies completely, they have reduced the number of biopsies substantially (Leroy 2007, Pinzani 2005, Sebastiani 2006). Hence, the clinical question remains: Will the information change my practice or advice? Recently three major guidelines have been published on the use of elastography and other methods for non-invasive assessment of liver fibrosis, which are recommended for further reading:
This chapter reviews non-invasive (serum markers and liver stiffness measurement) markers of liver fibrosis as well as fatty liver disease and aims to illustrate what is relevant in clinical practice.
Liver fibrosis is characterised by the loss of hepatocytes, destruction of hepatic (micro)architecture, proliferation of hepatic (myo)fibroblasts, and excess deposition of extracellular matrix (Friedman 2008). The final stage of liver fibrosis (cirrhosis) may result in insufficient detoxification, portal hypertension, renal and pulmonary failure and hepatocellular carcinoma, and is associated with excess mortality. Liver cirrhosis is the common end-stage of chronic liver diseases such as chronic viral hepatitis, non-alcoholic and alcoholic liver diseases as well as autoimmune and metabolic liver diseases. The mechanisms of fibrogenesis in all aetiologies share certain aspects but differ in detail. Consequently, the non-invasive assessment of liver fibrosis also varies between diseases.
A key feature of hepatic fibrosis is the activation and proliferation of fibroblasts and hepatic stellate cells. Chronic liver injury leads to activation of these cells, which become contractile, produce the extracellular matrix components and secrete inflammatory and profibrotic cytokines and chemokines such as transforming growth factor. The activation of these cells is believed to represent the key event in hepatic fibrogenesis (Friedman 2008). Hepatic stellate cell activation depends on signalling by Kupffer cells, endothelial cells, hepatocytes, and platelets. The deposition of the extracellular matrix is constantly opposed by the degradation of these proteins. In progressive liver fibrosis, this balance is skewed in favour of excess extracellular matrix deposition. Matrix metalloproteinases and their regulators (tissue inhibitors of metalloproteinases, TIMPs) control matrix deposition and degradation.
Liver biopsy may be obtained via different routes (Table 1). The most common is the ultrasound-guided percutaneous biopsy.
||Terjung 2003, van der Poorten 2006, Myers 2008, Chi 2017|
||Cholongitas 2006, Wolska-Krawczyk 2013|
||Helmreich-Becker 2003, Denzer 2007|
The quality and reliability of fibrosis staging via histopathological assessment of liver biopsy specimens depends largely on the size of the specimen and the number of portal fields. The biopsy should be at least 20-25 mm long and more than 11 portal tracts should be visible (Bedossa 2003, Chologitas 2006, Rousselet 2005). However, in daily practice these requirements may not be easy to achieve; and even if a large enough biopsy is acquired, the specimen only reflects about 1/50,000 of the whole liver. Thus, liver biopsies are particularly prone to sampling errors and may – like non-invasive markers – have difficulties in discriminating between adjacent stages of fibrosis (i.e., F1 vs. F2 or F2 vs. F3). Discrepancies of more than one stage are rare (Regev 2002, Siddique 2003, Skripenova 2007). Intra- and inter-observer variability may be unaffected by specimen sizes but can lead to discrepancies in up to 20% of cases, even if one stage difference between estimates is accepted (Gronbaek 2002, Petz 2003). Standardised automatic staging via image analysis may improve inter-observer variability (Calvaruso 2009 & 2012, Hui 2004, Isgro 2012).
There is a wide variability in the use of other staging systems in patients with chronic viral hepatitis. In Germany, current guidelines recommend the Desmet & Scheuer staging system (Table 2) (Batts 1995, Desmet 1994, French METAVIR Cooperative Study Group 1994, Ishak 1995, Knodell 1981, Schirmacher 2004).
|Staging System||Fibrosis stages||Remarks|
|METAVIR||F0, F1, F2, F3, F4||Best evaluated in HCV fibrosis||French METAVIR Cooperative Study Group 1994|
|Knodell||F0, F1, F3, F4||No intermediate stage||Knodell 1981|
|Desmet & Scheuer||Analogous to METAVIR||Recommended by the German guidelines for the assessment of liver fibrosis||Desmet 1994, Schirmacher 2004|
|Batts & Ludwig||Similar to METAVIR||Batts 1995|
|Ishak||F0, F1, F2, F3, F4, F5, F6||Ishak 1995|
Liver fibrosis develops as a continuous process rather than in a stepwise manner. Thus, so-called surrogate markers, which are also continuous variables, may provide more precise information. Surrogate markers can be subdivided into two groups (Table 3):
Direct markers reflect changes in the content of extracellular matrix proteins (such as collagen) in the liver.
Indirect markers indicate alterations in hepatic function, increase in portal hypertension with subsequent splenic enlargement, and/or grade of hepatic inflammation that may correlate with fibrosis stage.
Direct and indirect markers may be used alone or, more commonly, in combination (“composite scores”). The calculation of such scores can be simple (e.g., APRI, FIB-4, FORNS) or based on complicated formulas (e.g., Fibrotest, Fibromax, Fibrosure).
Advantages of surrogate markers are (EASL 2015):
Disadvantages of surrogate markers include (EASL 2015):
|Index||Variables||Formula for calculation||Interpretation|
|Direct surrogate marker|
|MP3||PIIINP, MMP-1||0.5901 (logPIINP[ng/mL]) − 0.1749 (logMMP-1[ng/mL])||<0.3 ≈ F0–2 >0.4 ≈ F3–4 <0.3 ≈ F0–1 >0.4 ≈ F2–4|
|Indirect surrogate markers|
|Forns||Age, plt, γGT, cholesterol||7.811 – 3.131 × ln(plt) + 0.781 × ln(γGT) + 3.467 × ln(age) − 0.014 (cholesterol)||>6.9 ≈ Scheuer 2–4 <4.2 ≈ Scheuer 0–1|
|APRI||AST, plt||([AST/ULN]/plt [× 109/L]) × 100||>1.5 ≈ Ishak 3–6 ≤0.5 ≈ Ishak 0–2|
|Fibroindex||Plt, AST, γGT,||1.738 − 0.064 (plt [× 104/mm3]) + 0.005 (AST [IU/L]) + 0.463 × (γGT[g/dL])||≤1.25 ≈ F0–F1 ≥2.25 ≈ F2–F3|
|Testa||Plt, spleen diameter||Plt count/spleen diameter||>1750 ≈ Ishak ≤2 ≤1750 ≈ Ishak >2|
|Fibrosis probability index||AST, cholesterol, past alcohol intake, HOMA, age||Ex/1 + ex, wherex = −10.929 + (1.827 × ln[AST]) + (0.081 × age) + (0.768 × [past alcohol use graded as 0–2]) + (0.385 × HOMA)||<0.2 ≈ F0–F1 ≥0.8 ≈ F2–F4|
|FIB-4||Plt, AST, ALT, age||(Ages × AST)/(plt count ×||<1.45 ≈ Ishak <4–6 >3.25 ≈ Ishak ≥4–6|
|Bonancini||ALT, AST, INR, plt||Sum (range 0–11) of (plt score) + (ALT/AST score) + (INR score) plt (× 109/L): >340 = 0; 280–339 = 1; 220–279 = 2; 160–219 = 3; 100–159 = 4; 40–99 = 5; <40 = 6 ALT/AST ratio: >1.7 = 0; 1.2–1.7 = 1; 0.6–1.19 = 2; <0.6 = 3 INR: \1.4 = 2||>8 ≈ Knodell 3–4|
|Pohl||AST, ALT, plt||Positive if: AST/ALT ≥1 and platelet count <150 × 109/L||Positive ≈ F3–F4|
|Age-Platelet||Plt, age||Age score + plt score (0–10 possible score) age: <30 = 0; 30–39 = 1; 40–49 = 2; 50–59 = 3; 60–69 = 4; ≥70 = 5. Plt (× 109/L): ≥225 = 0; 200–224 = 1; 175–199 = 2; 150–174 = 3; 125–149 = 4; ≥125 = 5||≥6 ≈ F2–F4|
|Combined direct and indirect surrogate markers|
|SHASTA||HA, AST, albumin||−3.84 + 1.70 (1 if HA 41–85 ng/mL, 0 otherwise) + 3.28 (1 if HA >85 ng/mL, 0 otherwise) + 1.58 (1 if HA <3.5 g/dL, 0 otherwise) + 1.78 (1 if AST >60 IU/L, 0 otherwise)||>0.8 ≈ Ishak ≥3 <0.3 ≈ Ishak ≤2|
|FM||plt, PI, AST, HA, α2-MC, gender, age||−0.007 plt (G/L) − 0.049 PI (%) + 0.012 AST (IU/L) + 0.005 α2-MC (mg/dL) + 0.021 HA (μg/L) − 0.270 urea (mmol/L) + 0.027 age (years) + 3.718||≥F2|
|Hepascore||HA, α2-MC, γGT, age, gender||y/1 + y, where y = exp [−4.185818 − (0.0249 × age) + (0.7464 × sex) + (1.0039 × α2-MC) + (0.0302 × HA) + (0.0691 × bilirubin) − (0.0012 × γGT)]||≥0.5 ≈ F2–F4 <0.5 ≈ F0–F1|
Primary endpoints of the studies that evaluated surrogate markers vary from discrimination of no fibrosis and cirrhosis to the determination of the stages of fibrosis. With the occurrence of the new antiviral treatment options for HCV patients that allow the treatment even in decompensated patients with advanced cirrhosis, the detection of fibrosis in HCV patients has become a less relevant clinical information. However, in areas with limited treatment access where treatment is prioritised the determination of advanced fibrosis stages may guide the decision of whom to treat first. In addition patients with liver cirrhosis need continuous monitoring even after viral elimination due to an increased risk of the occurrence of hepatocellular carcinoma.
From the whole range of surrogate markers only a few are in clinical use. The simple APRI score has been widely studied in HBV and HCV as well as in co-infected patients (Cacoub 2008, Lebensztejn 2005, Vallet-Pichard 2008, Wai 2006). A recent comprehensive meta-analysis of the performance of the APRI test showed that its major strength is the exclusion of significant fibrosis, defined as F2-F4, or cirrhosis with cut-offs of 0.5 and 1.5, respectively. Importantly, the test performance varied with the quantity of advanced fibrosis in the different patient groups (Shaheen 2007 & 2008). Fibrotest has also achieved some clinical significance. However, this test may not be available for all patients. Recent meta-analyses of the predictive performance of Fibrotest summarise that the reliability for the detection of advanced fibrosis or cirrhosis is adequate for clinical practice, and a cut-off of 0.6 has been suggested (Poynard 2007, Shaheen 2007 & 2008). Of note, the reliability for the detection of earlier fibrosis stages appears to be relatively low (Poynard 2007, Shaheen 2008).
It has to be pointed out that the performance of these markers differs among liver diseases. For instance, a study evaluating indirect markers in >2,000 patients with chronic liver diseases detected a higher accuracy for detecting significant fibrosis in HCV patients than in NALFD (Sebastian 2011). A recent comprehensive paper reviewing the diagnostic accuracy of surrogate markers of fibrosis in HCV patients from 172 studies concluded that these tests based on different biomarkers are equally effective in diagnosing cirrhosis (Chou 2013). Combinations of different scores may be more effective in avoiding biopsies.
Non-invasive markers have potential value beyond the prediction of fibrosis. Surrogate markers and in particular elastography techniques have been evaluated for the prediction of liver-related complications and mortality. A number of studies aimed to test composite scores in this context for a variety of liver diseases such as PBC, alcoholic liver disease or HCV as well as mixed cohorts, describing AUROCs of 0.73 - 0.86 for mortality prediction (Mayo 2008, Naveau 2009, Parkes 2010, Vergniol 2011).
In summary, surrogate markers may support the clinical decision making process, but a single surrogate marker or score cannot replace liver biopsy. On the other hand, attempts have been made to combine different surrogate markers and biopsy in clinical decision algorithms that aim to reduce the need for liver biopsy.
Several methods for ultrasound-based elastography of the liver have been developed. These methods can be subdivided into two categories. The readouts of these measurements are either kPa or m/s, or both. Transient elastography has been available and evaluated since 2005, whereas the other technologies have become commercially available thereafter. Hence, transient elastography is the most common elastography method today but the success in non-invasive evaluation of liver fibrosis obviously has stimulated others manufacturers of ultrasound machines to promote their own specific technology. However, although similar in read-outs, not all specific machines have been evaluated in detail.
1. Shear wave speed techniques and readout values
2. Strain/displacement techniques
Initially elastography was used to assess liver fibrosis stages without the need for biopsy and to exclude cirrhosis. Over time clinicians and researchers broadened the application and tried to answer more questions using elastography:
Transient elastography (TE) is a non-invasive technique to assess liver fibrosis (Sandrin 1999). TE allows the assessment of liver fibrosis by calculating the velocity of a low-frequency transient shear wave produced by a mechanical probe that is placed directly on the skin of the patient. The velocity of the wave that penetrates the liver tissue depends on the stiffness of the liver, which in turn correlates with the extent of liver fibrosis. In practice, a probe is placed in an intercostal space at a position that is comparable to the position for standard liver biopsy. Ten successful measurements are usually necessary for the assessment of liver stiffness. This can be done in less than 5 minutes. At present TE machines are exclusively available from Echosens (FibroScan®). Liver stiffness is expressed in kilo Pascal (kPa). The method is easy to learn and quick, results are available immediately, and a technical assistant can perform the procedure. In most studies, TE displays robust intra- and inter-observer variability (Fraquelli 2007) and may be used in children as well as adults (de Ledinghen 2007).
Normal liver stiffness
Evaluation of liver stiffness in subjects without apparent liver disease shows that liver stiffness is influenced by sex and body mass index (BMI). In general, liver stiffness is higher in men than in women (5.8±1.5 vs. 5.2±1.6 kPa) and in obese vs. non-obese (6.5±1.6 vs. 5.3±1.5 kPa). (Roulot 2008). Interestingly, TE may be used as a screening tool for the general population to identify patients with unrecognised liver disease (Ginès 2016, Roulot 2011).
Taken together one might say that liver stiffness values < 7.5 kPa appear to reflect the normal range, i.e. the absence of advanced liver fibrosis (Castera 2008, Ferraioli 2015).
Common sources of false interpretation of results (usually elevated liver stiffness measurements) have been identified and should be taken into account when setting up TE measurements in clinical routine (Table 4). Acute liver injury such as acute viral or alcoholic hepatitis, or chronic viral hepatitis flares can lead to overestimation of liver fibrosis (Arena 2008, Coco 2007, Sagir 2008). Other interfering conditions include cardiac failure, Valsalva manoeuvre, pulmonary hypertension, amyloidosis, pregnancy, cholestasis, or steatosis, with the latter being more relevant in HCV than in HBV (Arena 2008, Fraquelli 2007). Another relevant artefact is the examination of a patient within 2 hours after a meal, which increases resistance by up to 2 kPa (Mederacke 2009). Special probes have been developed to overcome problems with measurements in children and in obese patients ("S-probe", "XL-probe") (Engelmann 2011).
|Obesity (BMI >30 kg/m2)||Use XL Probe||Cut-offs may be slightly lower with XL probe|
|Age >52 years|
|Steatosis||Relevant only in HCV patients|
|Non-fasting||Re-measure after 3–6 h fasting period|
|Cardiac failure||Reassessment after cardiac recompensation|
|High necroinflammatory activity (AST/ALT ratio)||Reassessment after cessation of inflammatory flare|
|Ascites||Use other non-invasive procedures such as ARFI, SSI or MR elastography, or re-measure after complete paracentesis|
|Cholestasis||Decompression||Stiffness reduction in PSC is incomplete after stenting, but changes in stiffness during long-term follow-up are associated with severity of fibrosis and outcomes|
Common quality criteria applied to certify an acceptable quality of TE measurements are: 10 successful measurements with >60% successful measurements and an interquartile range (IQR)/median (M) ratio <0.30. However, the relevance of these criteria has been questioned, and a three-category classification system of reliability has been suggested: “very reliable” (IQR/M ≤0.10), “reliable” (0.10 < IQR/M ≤ 0.30, or IQR/M >0.30 with median liver stiffness <7.1 kPa), and “poorly reliable” (IQR/M >0.30 with median liver stiffness ≥7.1 kPa). Applying these categories to the clinical endpoint “cirrhosis” leads to the correct classification of 90.4%, 85.8% and 69.5% patients, respectively (Boursier 2012). In a large overview of 12,000 examinations 4% of measurements with the M-probe were not successful, and 17% were rated as unreliable (Castera 2010). Multivariate assessment of factors responsible for failure or unreliability were obesity and limited operator experience. Interestingly, not BMI in general but a lipohypertrophy in the thoracic belt in particular was the limiting factor for the success rate. It is important to note that the applicability of TE is limited to relatively lean patients (BMI <28 kg/m2), patients without ascites, and “cooperative” patients. The special "XL-probe" for obese patients has broadened the applicability of TE and is recommended for patients with a skin-capsule distance of >2.5 cm (but below 3.5 cm) (Myers 2011).
Unlike liver histology, no published data is available on the variability (“sampling error”) of TE results. TE correlates well with other surrogate markers of liver fibrosis such as APRI and FIB-4 (Vidovic 2010). In patients with chronic liver disease eligible for TE, liver stiffness values correlate with the stage of fibrosis, irrespective of the underlying disease aetiology. TE has been evaluated in patients with chronic viral hepatitis, PBC, PSC, NASH, haemochromatosis, and Wilson disease. Due to high acceptance by patients, it can easily be used to monitor progression or regression of fibrosis in patients under observation or on therapy (Wilson 2006, Wong 2011). TE has been evaluated for the detection of liver fibrosis in patients with acute and chronic viral hepatitis and has also been positively evaluated for HCV/HIV-coinfected patients and in patients with HCV recurrence posttransplantation (Carrion 2006, de Ledinghen 2006, Maida 2007).
Cut-offs for liver fibrosis
Recent studies comparing TE with liver biopsy demonstrate both high sensitivity and specificity for the detection of advanced fibrosis and cirrhosis. However, TE performance is less reliable for the detection of fibrosis stages ≥F2 as compared to more advanced stages of liver fibrosis (sensitivity 56-67%), resulting in moderate negative predictive values. Thus, the assessment of liver fibrosis by TE alone may result in the underestimation of liver fibrosis in some patients. Vice versa, if TE predicts significant fibrosis, a biopsy will not be necessary.
An authoritative meta-analysis that evaluated the predictive performance of TE in patients with chronic liver disease suggested that the optimal cut-off value for the diagnosis of significant fibrosis is 7.65 kPa and 13.0 kPa for cirrhosis (Friedrich-Rust 2008). For chronic liver diseases other than HCV the specific cut-off values for cirrhosis are 11.7 kPa in HBV, 10.3 kPa in non-alcoholic fatty liver disease, 17.9 kPa in biliary liver diseases, and 22.7 kPa in alcoholic liver disease if drinking and 12.5 kPa if abstinent (Trapper 2015).
A recent meta-analysis of the performance of TE in patients with alcoholic liver disease is less enthusiastic about the exactness of TE in this context and suggests to use both TE and liver biopsy sequentially in some cases to establish the correct fibrosis stage in all patients; the authors stress the importance of TE in ruling out cirrhosis or advanced fibrosis rather than defining exact fibrosis stages (Pavlov 2015).
Apparently different diseases have somewhat different cut-offs. However, rather than using fixed cut-offs the application of TE in a more continuous manner and follow-up procedure to assess changes in liver stiffness (Castera 2008). Whereas liver stiffness values >12.5 kPa are highly suggestive for advanced liver fibrosis or cirrhosis, patients with lower values (<7.5 kPa) are unlikely to suffer from advanced disease (Figure 1). Intermediate patients may qualify for liver puncture to clarify fibrosis stage if not answered by other non-invasive procedures (Table 2).
Elastography may be used for monitoring stiffness changes over time. Rather than focusing at a given stiffness at a certain time point clinicians may use stiffness measurements for monitoring changes in liver stiffness. Recent studies highlighted that the consecutive increase of liver stiffness is related with higher mortality and liver-related events such as variceal bleeding or hepatic encephalopathy, especially in patients with liver stiffness >12.5 kPa (Perrez-Latorre 2016, Vergiol 2014).
TE may be used to monitor changes in liver stiffness following either the natural course or changes in stiffness on and after treatment. Whereas in the first scenario prediction of disease progression rates may be useful, the latter reflects the regression of inflammation and/or fibrosis. The longitudinal monitoring of patients with chronic HBV and HCV infections has documented reduction in liver stiffness upon treatment response (Andersen 2011, Fung 2011, Hezode 2011).
In addition to the assessment of liver fibrosis stages, TE might be used to predict the presence of portal hypertension (Rockey 2008). Of note, a cut-off value of >25 kPa has been associated with a >45-fold increased risk of developing HCC in viral hepatitis. However, the risk seems to increase in a linear fashion starting from 10 kPa (Fung 2011, Masuzaki 2009). Furthermore, TE values >21 kPa are associated with portal hypertension as well as the risk of portal hypertension-related complications and indicate that endoscopy is indicated to assess oesophageal varices as well as the need for primary prophylaxis with non-selective β-blockers (Castera 2011, Robic 2011).
A combination of non-invasive tests in the form of surrogate markers, elastography methods or both have the potential of reducing the number of biopsies, lead priorisation strategies for treatment and surveillance and predict morbidity and mortality. Despite a number of studies in this field we currently do not have a definite algorithm that is widely accepted in clinical practice. However, the WHO highlights the combination of APRI, FIB-4 and TE in order to identify patients at risk and to start treatment in HCV-infected patients (WHO 2014).
The recent EASL guidelines for the use of non-invasive assessement of liver fibrosis suggest a number of distinct algorithms for different liver disease. The proposed algorithm for HCV patients is shown in Figure 2. The basic principle is that TE is combined with a serum marker test for liver fibrosis. Concordant results may reduce the need for biopsy while inconclusive results may be a reason for biopsy. The experience of the authors of this chapter is however that for the sake of determining the stage of liver fibrosis it is hardly ever necessary to perform biopsy unless other information is needed (e.g., evidence for autoimmune hepatitis); furthermore, patients are reluctant to undergo biopsy due to the widespread information on non-invasive alternatives.
Besides TE as the primary tool, shear wave technology to assess liver fibrosis, ARFI and SSI have now been more intensively studied for the assessment of fibrosis, cirrhosis and complications. ARFI and SSI both use a region of interest that can be adapted by the investigator. ARFI is implemented in Philips and Siemens ultrasound machines. Ideally, the region of interest (10×5 mm) is set 1-2 cm below the liver capsule. As in TE, ten sequential measurements are performed and the interquartile range is used to assess the accuracy of fibrosis evaluation. Although ARFI and SSI can be used in obese patients and patients with ascites, there is a subgroup of patients in whom reliable results may not be obtained (Cassinotto 2014), comprising up to 3% in ARFI cohorts and up to 11% in SSI studies (Cassinotto 2014). A recent meta-analysis reported that the accuracy for the prediction of fibrosis stages ≥F2, ≥F3 and cirrhosis were 0.87, 0.91 and 0.93, respectively (Friedrich-Rust 2012). A recently published head-to-head analysis comparing TE with ARFI showed comparable results for both methods (Colombo 2012). However, ARFI was less prone to methodological failure than TE. Both methods seem reliable for the detection of advanced fibrosis (Colombo 2012, Rizzo 2011, Sporea 2012). As with TE, many procedure- and patient-related factors may influence test results, in particular increased stiffness during hepatitis flares (Chen 2012, Karlas 2011).
Another shear wave-based technology has recently been introduced for the diagnosis of liver fibrosis (real-time SSI by Supersonic Imaging), combining TE stiffness calculations with the possibility of defining regions of interest as in ARFI. While this method has not yet been widely used, early studies show a comparable diagnostic accuracy compared to TE (Ferraioli 2012a, Ferraioli 2012b). A recent comparison of all three methods (ARFI, TE, SSI) with liver biopsy in patients with fatty liver disease did not reveal substantial differences although SSI may be more reliable in the diagnosis of >F4 fibrosis in these cases but no differences between SSI and TE or ARFI and TE have been reported in this context. Interestingly in this patient cohort the cut-offs were very close for SSI and TE and substantially lower than for patients with chronic viral hepatitis (6.3/6.2 kPa for ≥F2, 8.3/8.2 kPa for ≥F3, and 10.5/9.5 kPa for F4, respectively) (Cassinotto 2015). In principle these results were confirmed in unselected cases of patients with chronic liver disease (Gerber 2015).
Concerning data on correlation with histological fibrosis stages, TE, ARFI and SSI all suffer from the same limitations with overlapping ranges of stiffness results for individual fibrosis stages. However, they all seem adequate in detecting the presence of fibrosis and cirrhosis. Numerous comparisons have been made in order to detect an advantage of one machine over another. In the end none of these studies identified substantial differences for choosing one method over the other. A detailed critical review on available ultrasound methods with all pros and cons of each single methods has been published recently and is recommended for further reading (Ferriaioli 2015).
Computational methods may improve the specifity and sensitivity for the diagnosis of liver fibrosis stages. For 2D-Shear wave elastography a neuronal network was applied and predictions were compared to histology stages. This approach may maximise sensitivity and specificity (Wang 2018), but predictions for lower fibrosis stages were not as markedly improved as for advanced fibrosis. These techniques highlight the potential of smart computer algorithms ("artificial intelligence") to support non-invasive assessment of liver phenotypes.
A number of different imaging techniques such as conventional ultrasound, real-time elastography, portal venous transit time, MR imaging have been used for the assessment of liver fibrosis. None of these methods has yet achieved an overall clinical acceptance regarding the assessment of liver fibrosis, either due to low sensitivity and/or specificity, or high costs.
Non-invasive markers for the staging of liver fibrosis are at the edge of replacing liver histology as the gold standard, at least in hepatitis C. This is due to the fact that outcome studies with clear endpoints like mortality are available (Vergniol 2011, Pakres 2010, Naveau 2009, Mayo 2008) or under investigation (NCT01241227, NCT02037867 and others). The advantages of these non-invasive tests in comparison to liver biopsy are striking. In order to overcome test limitations and to benefit from their specific advantages, a frequent strategy is to combine different non-invasive tests, using liver biopsy only in case of doubt. However, algorithms vary greatly in performance and acceptance. Whereas some authors have estimated a reduction in liver biopsies of 30%, others have estimated reductions of up to 80% (Leroy 2007, Sebastiani 2004, Sebastiani 2006, Sebastiani 2007). New strategies with sophisticated algorithms may overcome these limitations and a combination of TE with FibroMeter give results that may be detailed and reliable on liver fibrosis stage without any need for histology. However, only one study from France has described this method, which needs to be cross-validated by independent groups (Boursier 2011a, Boursier 2011b).
Patients not being in regular care are diagnosed in late stages when liver decompensation or liver cancer develops. The diagnosis is rarely made in early stages-when liver fibrosis is mild to moderate but cirrhosis is not yet established-because the disease is asymptomatic. Liver biopsy is not a suitable procedure for population-based screening for fibrosis and/or fatty liver but non-invasive methods might be. A recent comprehensive survey on the frequency of liver fibrosis in population-based studies revealed progressive disease in up to 25.7% of participants (Harris 2017). In a population-based screening study using transient elastography, prevalence estimates of increased liver stiffnesss (≥6.8, ≥8.0, and ≥9.0 kPa) were 9.0%, 5.8%, and 3.6%, respectively. Elastography was more accurate than alanine aminotransferase, NAFLD fibrosis score, or FIB-4. Liver stiffnes <9.2 kPa predicts the absence of significant liver fibrosis with high accuracy and could be used for screening purposes (Caballería 2018).
Nowadays virus-induced chronic liver diseases can be effectively treated by well tolerated antiviral drug regimens, but the epidemic of non-alcoholic fatty liver disease (NAFLD) demonstrates an exponential increase in burden of disease. The mechanisms contributing to hepatic steatosis and the development of an inflammatory state with progression to liver disease are under intense investigation. Patients with NAFLD, in particular with non-alcoholic steatohepatitis (NASH), suffer from an increased risk of advancing to progressive liver disease with fibrosis, eventually resulting in cirrhosis and the need for liver transplantation.
The challenges for the development non-invasive diagnostic strategies are:
As for liver fibrosis serological markers either as single markers or combined in scores are being evaluated in comparison to liver histopathology. It is debated whether non-invasive tests are comprehensive for the detection and classification of disease severity of NAFLD (Bedossa 2018; Castera 2018). It can be expected that non-invasive techniques will play a more important role in the diagnostic work-up of patients with fatty liver disease.
Serological markers of steatosis in NAFLD are also being evaluated. Similarly to the history of non-invasive fibrosis assessment, attempts are made to established steatosis-specific markers and scores that aim to diagnose steatosis by the combination of different parameters with more or less specificity for steatosis and inflammation in fatty liver disease.
Studies also aim to distinguish the necoinflammatory state, i.e. NASH, from simple steatosis. A comprehensive review on this topic has been published by Vilar-Gomez and Chalasani (Vilar-Gomez 2018). Examples of specific markers for NAFLD/NASH are cytokeratin 18 and fibroblast growth factor 21, which are released into the circulation in response to oxidative stress, hepatocyte apoptosis and inflammation. However, a recent meta-analysis came to the conclusion that current non-invasive tests do not accurately differentiate NASH from simple steatosis (Verhaegh 2018).Further efforts are needed to identify more sensitive and specific markers and scores.
As for liver fibrosis, several studies aim to increase the diagnostic accuracy by combining different tests in NAFLD. In the case of NAFLD-associated fibrosis, the sequential use of liver stiffness measurement, NFS and FIB-4 has led to an improvement of correct classification. However, the best combination and sequence of makers is yet to be defined (Petta 2017). In the recent German guideline, two scores that combine a number of factors have been included (Table 5). The guideline has also suggested an algorithm for the diagnostic work up of NAFLD (which needs more evaluation). It concludes that non-invasive steatosis assessment may be done by applying the FLI or MRI criteria. For the assessment of advanced fibrosis in NAFLD, the NFS score is applicable.
While the detection of liver fibrosis via elastography may be hampered by number of factors this may also be true for serum-markers for NAFLD. For instance it could be shown that the listed NAFLD fibrosis score (and the FIB-4 score) is inaccurate especially in patient aged 65+ (McPherson 2017).
Which may explain the results of However a recent meta-analysis (#326, Verhaegh P et al. EASL 2016) that did showed that the majority of non-invasive markers have no sufficient diagnostic value in order to reliably diagnose steatosis and NASH. Further efforts are needed to identify more sensitive and specific markers and scores.
As in liver fibrosis authors aim to further increase the diagnostic accuracy by combining different tests in fatty liver disease. In the case of liver fibrosis in NAFLD the sequential use of liver stiffness measurement, NFS and FIB-4 lead to an improvement of correct classification. However, the best combination and sequence of markers is yet to be defined (Petta S 2017).
|Index||Variables||Formula for calculation||Interpretation|
|Fatty liver Index (FLI)||BMI, γGT, triglycerides, waist circumference||(e 0.953*loge (triglycerides) + 0.139*BMI + 0.718*loge (GGT) + 0.053*waist circumference - 15.745) / (1 + e 0.953*loge (triglycerides) + 0.139*BMI + 0.718*loge (ggt) + 0.053*waist circumference - 15.745) * 100||Cut off <30: Likelihood-ratio (LR) of 0.2 with a sensitivity of 82% that no steatosis is present
Cut off had specificity of 86 % and positive LR of 4.3 that steatosis is present
|NAFLD fibrosis score (NFS)||Age, BMI, diabetes, AST, ALT, plt, albumin||−1.675 + 0.037 × age (years) + 0.094 × BMI (kg/m2) + 1.13 × IFG/diabetes (yes = 1, no = 0) + 0.99 × AST/ALT ratio − 0.013 × platelets (×109/l) − 0.66 × albumin (g/dL).||Cut off < -1.455: Absence of significant fibrosis (93% certainty)
Cut off > 0.676
Presence of significant fibrosis (90% certainty)
Can elastography reliably assess fibrosis in these patients and what are the precautions we need to consider?
Up to date there is no conclusive evidence that increased liver stiffness is a good predictor for the presence and severity of lipid storage in the liver in patients suspected of NAFLD. In addition, TE and other shear wave elastography methods can reliably predict cirrhosis (F4: sensitivity 92%, specificity 92%), but the detection of early fibrosis stages appears to be limited (Kwok 2014). Finally, elastography is not a reliable tool to detect necroinflammatory changes in the liver.
Liver fat content has been historically assessed by ultrasound using a semi-quantitative estimate or by liver histology. Steatosis is a growing problem whether in the context of non-alcoholic steatohepatitis or as a co-factor in the metabolic syndrome and other liver diseases. Until recently reliable quantitative measures of the degree of steatosis were missing. A novel tool to overcome this diagnostic gap may be the Controlled Attenuation Parameter (CAP). This analysis is available in TE machines from Echosens that measure the attenuation of the intensity of the echo from the ultrasound signal in the liver (available for the M-probe and the XL-probe). It is calculated only for reliable TE measurements and does not lengthen the TE procedure. The measurement is expressed in dB/m. Korean investigators defined a normal upper range of 266 dB/m in potential liver donors, all with histology proven fat contents <5%. However, in a less strictly selected patient population defined as a “health check-up” cohort, a higher upper limit of normal of 288 dB/m was defined, which may be due to the inclusion of patients with diabetes (Chon 2014). A recent study defined histopathological categories of liver steatosis (S) grades (S0: ≤10%, S1: 11 – 33%, S2: 34 – 66%, S3: ≥67%) and correlated these with CAP results. Using receiver operating statistics, the authors defined cut-offs with a sensitivity >90% for all grades of steatosis (215 dB/m for S ≥1, 252 dB/m for S ≥2, 296 dB/m for S3) (de Ledinghen 2012). In patients with chronic hepatitis C, corresponding cut-off values of 222 dB/m, 233 dB/m and 290 dB/m were identified for discriminating the steatosis grades (Sasso 2012).
As with TE, CAP results are also influenced by multiple factors and vary with the cause of the disease (de Ledinghen 2014). A recent meta-analysis focused on the confounders of high CAP values and found that besides NAFLD, diabetes and BMI are independently influencing CAP values. The authors also point out that the influence of these confounders may change according to the prevalence of steatosis in the studied population. According to their results in 2,735 patients, they determined the following cut-offs for >S0, >S1 and >S2: 248, 268, and 280 dB/m, respectively (Karlas 2017).
Non-invasive tests have still not completely replaced liver biopsies, but smart combinations of non-invasive tools avoid this more invasive procedure in many patients. Whatever the current standard of care, the patient should be informed about the non-invasive tests, their applicability, and their limitations. The decision to perform a liver biopsy should ultimately be made together with the informed patient.
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