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Egyptian Liver Journal
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  • Original Research Article
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Clinical value of acoustic radiation force impulse elastography in the prediction of hepatocellular carcinoma in chronic hepatitis C patients

Egyptian Liver Journal volume 13, Article number: 22 (2023) Cite this article

Abstract

Background and purpose of the study

Acoustic radiation force impulse elastography (ARFI) represents an innovative non-invasive tool for the evaluation of liver fibrosis, cirrhosis, and early identification of neoplastic nodules during the follow-up of cirrhotic patients; however, its diagnostic accuracy in the prediction of hepatocellular carcinoma (HCC) is still controversial.

Purpose of the study

To assess the potential role of ARFI elastography as a non-invasive tool for the prediction of HCC development among chronic hepatitis C (CHC) patients with advanced hepatic fibrosis and liver cirrhosis.

Methods

The present study recruited 440 patients: 349 CHC patients with advanced hepatic fibrosis and cirrhosis and 91 patients with HCC-related hepatitis C virus (HCV). ARFI-imaging of the liver and transient elastography (TE) was carried out in all patients. ARFI imaging indices include the mean shear wave velocity of HCC, peritumoral parenchyma, and hepatic parenchyma in non-HCC patients. The area under the receiver operating characteristic curve (AUROC) and optimal cutoff values were obtained using a receiver operating characteristic curve analysis to assess the diagnostic performance of ARFI elastography in the predication of HCC.

Results

The mean hepatic shear wave velocities by ARFI elastography of peri-tumoral cirrhotic hepatic parenchyma were significantly higher than in hepatic parenchyma in non-HCC patients (3.09 vs. 2.26 m/s, p <0.001). The AUROC for the identification of HCC was 0.8, 0.76, 0.76, 0.66, 0.72, and 0.7 for hepatic ARFI elastography, TE, fibrosis-4 score (FIB-4), AST to Platelet Ratio Index (APRI), AST/ALT ratio (AAR), and Age platelets index (API), respectively. Moreover, univariate regression analysis revealed that hepatic ARFI has the highest odd ratio in the prediction of HCC.

Conclusion

ARFI elastography had a superior diagnostic performance in the prediction of HCC compared to TE and non-invasive markers in CHC patients with advanced fibrosis and cirrhosis, thus putting such patients on the top of the HCC screening list.

Introduction

Hepatitis C virus (HCV) infection is one of the leading contributors of chronic liver disorders worldwide [1]. It represents one of the main etiologies of progressive liver fibrosis which leads to cirrhosis, hepatic decompensation, and hepatocellular carcinoma (HCC) [2]. The annual incidence of HCC, hepatic failure, and death is estimated to be 3.2%, 2.9%, and 2.7%, respectively, if chronic HCV-infected patients with advanced hepatic fibrosis were not treated [3].

Liver fibrosis staging is critical for the management of chronic HCV patients, including the prognosis of chronic liver diseases and making therapeutic decisions [4]. Moreover, the severity of liver fibrosis and advanced liver disease necessitates need for further evaluations for HCV-related complications such as hepatic decompensation, HCC surveillance, and esophageal varices screening.

Liver biopsy (LB) is the reference method for the staging of liver fibrosis [5]; however, it is limited by its invasiveness, sampling error, and unavoidable complications such as bleeding [6].

Several non-invasive approaches have been proposed to stage hepatic fibrosis [7] and gradually replaced LB. These methods consist of serum markers and imaging modalities. The liver fibrosis marker panel consists of direct and indirect serologic tests while imaging modalities commonly consist of ultrasound-based elastography and magnetic resonance elastography (MRE). Transient elastography (TE) and elastographic modalities based on shear waves generated via an acoustic beam, i.e., elastography point quantification (ElastPQ; Philips) and acoustic radiation force impulse elastography (ARFI) or virtual touch tissue quantification (VTTQ; Siemens) and supersonic shear imaging (SSI) [8,9,10].

ARFI elastography is an ultrasound-based, non-invasive imaging technique that is integrated into conventional ultrasound machine for assessing liver stiffness (LS) and predicting the complications of patients with chronic liver disease (CLD) in chronic viral hepatitis such as hepatitis B virus (HBV) or hepatitis C virus (HCV) and non-alcoholic fatty liver disease (NAFLD) [10, 11].

The current study aimed at comparing the parenchymal stiffness of the hepatic tissue adjacent to HCC to hepatic parenchymal stiffness in HCV patients with advanced fibrosis (≥F3) and cirrhosis (F4) using the ARFI 2D images in order to set a cutoff value of hepatic parenchymal stiffness that could predict the development of HCC in HCV patient with advanced hepatic fibrosis and cirrhosis, thus putting such patients on the top of the HCC screening list.

Methods

Patient population

The present retrospective case-control study was carried out at Cairo University Center for Hepatic Fibrosis (CUC-HF), Endemic Medicine Department, Faculty of Medicine, Cairo University, during the period from January 2015 to July 2016.

Over the study period, 94 patients with post-hepatitis C HCC diagnosed according to the European Association for the Study of the Liver (EASL) guidelines [12], as well as 349 patients with HCV-related advanced hepatic fibrosis (≥F3) and cirrhosis (F4) as measured by TE were enrolled consecutively.

Inclusion criteria

For CHC patients, chronic HCV infection was established with the positivity of anti-HCV antibody and HCV ribonucleic acid (RNA) polymerase chain reaction (PCR) for more than 6 months, the presence of advanced hepatic fibrosis (≥9.5 kPa; ≥F3) and cirrhosis (≥12.5 kPa; F4) as detected by TE while for HCC patients that they had the history of HCV infection and were diagnosed according to the latest EASL guidelines [12].

Exclusion criteria

The HCC patients had a history of any previous local therapy, i.e., radiofrequency ablation (RFA), percutaneous ethanol injection (PEI), patients with hepatic focal lesions other than HCC (i.e., metastasis, hemangioma), and patients with ARFI failure.

Collected data

Demographic characteristics and laboratory findings were obtained for each patient at the time of TE measurements and ARFI imaging. The presence of HCC was assessed. Furthermore, the assessment of the degree of liver dysfunction and the presence of hepatic decompensation were recorded.

Imaging technique

Abdominal ultrasonography and TE were done for all patients. TE examination was performed using FibroScan® 502 Touch according to the manufacturer’s recommendations taking into consideration the reliability criteria of at least ten successful attempts with a success rate >60% and an interquartile range (IQR) <30% [13].

After a B-mode US image, the ARFI 2D images were carried out by Virtual Touch TM tissue imaging button which was operated by 2 expert hepatologists who were blind to patients’ data. The part of hepatic parenchyma to be examined for elastic properties is described utilizing a Region of Interest (ROI), defined by a box with a fixed dimension of 1 cm × 0.5 cm and a maximum depth of 5.5 cm. The ROI did not include any vessels or biliary structures, and any potential presence of fibrotic scar was excluded from the ROI. The target hepatic parenchyma is mechanically “pushed” by short-duration forces (less than 1 m/s) that produce localized displacements. The shear waves generated propagate perpendicular to the acoustic pulse away from the target ROI. The shear wave velocity (SWV) was expressed in meters per second (m/s). To reduce cardiac- and respiration-related tissue motion in the ROI, all measurements were done in the right hepatic lobe by the intercostal approach during a brief breath hold (neither full inspiration nor full expiration). Successful ARFI liver elastography was only considered if 10 attempts could be obtained with a success rate of ≥60% and the interquartile range (IQR) was <30% of the mean value. Non-valid measurements due to the inability to hold breath as required or an inappropriate ROI positioning (i.e., vessels or biliary structures within the ROI), expressed by the system as “N/A” (not-available) or “XXXX” or “0”, were ruled out. In the absence of validated quality criteria, ARFI failure was established as the acquisition of fewer than 10 valid measurements [14]. The hepatic shear wave velocity (SWV) by ARFI was calculated for HCC, hepatic parenchyma adjacent to HCC, and compared to the ARFI values in patients with advanced fibrosis and cirrhosis in the non-HCC group.

Calculated scores

The following scores were used in predicting HCC.

  • AST to Platelet Ratio Index (APRI) score = (AST/upper limit of normal)/platelet count (expressed as platelets × 109 /L) × 100 [15].

  • Fibrosis-4 score (FIB-4) = Age (y) × AST (IU/l)/platelet count (×109/liter) ×√ALT (IU/l)) [16].

  • Age platelets index (API) = Age (year)/PLT (× 109/L) [17]

  • AST/ALT ratio (AAR) = AST (IU/l)/ALT (IU/l) [18]

Statistical analyses

STATA 14 software was used to validate and analyze the data. Patients’ demographic and routine laboratory values were expressed as number (percent) for categorical variables and as mean (± SD) or median (inter quartile range) for continuous variables. All quantitative parametric and non-parametric variables were analyzed using either Students’ t test or Mann-Whitney test for comparison of the HCC group and non-HCC group whenever appropriate. The non-HCC group of patients was further stratified according to hepatic stiffness measured by TE into patients with fibrosis stage 3 (F3, stiffness 9.5–14.4 kPa) and patients with fibrosis stage 4 (F4, stiffness ≥14.5 kPa). A comparison of 3 groups was done using Kruskal-Wallis for non-parametric or ANOVA (analysis of variance) test for parametric variables whenever appropriate. Chi-square test was used for comparison of categorical data. A univariate logistic regression model was constructed to identify significant predictors for HCC in our cohort. The diagnostic performance of hepatic parenchymal stiffness measured by ARFI in the prediction of HCC occurrence among patients with post hepatitis C significant hepatic fibrosis was evaluated using receiver operator characteristic (ROC) curves. The area under the ROC curves (AUROC) and the 95% confidence interval (95%CI) were used as indexes of accuracy. All statistical analyses were based on two-sided hypothesis tests with a significance level of p < 0.05.

Results

From January 2015 to July 2016, a total of 443 CHC patients were recruited. Of these, three patients were ruled out because of ARFI measurement failure due to the inability to hold their breath as required or poor compliance of patients. Finally, 440 CHC patients with ten valid ARFI measurements obtained from the right lobe of the liver were enrolled and they were further classified as 349 CHC patients with advanced hepatic fibrosis (≥F3) and cirrhosis (F4) and 91 patients with HCV-related HCC.

Demographic and laboratory parameters in both groups were shown in Table 1. Patients with HCC were significantly older with male predominance (76.9%) than non-HCC patients (p=<0.001).

Table 1 Demographic and laboratory data of the studied patients (n= 440)
Full size table

Regarding fibrosis scores, they were significantly higher in HCC patients than in non-HCC patients as shown in Table 2.

Table 2 Liver stiffness measurements and fibrosis scores in the studied patients (n=440)
Full size table

Liver stiffness measurement (LSM) by TE displayed a highly significant difference (p<0.001) between the non-HCC (22.2 ± 12.8 kPa) and the HCC group (38.1 ± 21.4 kPa). The mean hepatic SWV by ARFI of peri-tumoral cirrhotic hepatic parenchyma was significantly higher than in hepatic parenchyma in non-HCC patients (3.09 vs. 2.26 m/s, p <0.001) as shown in Fig. 1A and Table 2. Moreover, a significant difference was found between the mean of hepatic SWV within HCC nodules and peri-tumoral cirrhotic hepatic parenchyma and hepatic parenchyma in non-HCC patients (2.09 vs. 3.09 vs. 2.26 m/s, p <0.001) as shown in Fig. 1B.

Fig. 1
figure 1

A Acoustic radiation force impulse (AFRI) values in non-hepatocellular carcinoma (HCC) group and HCC group. B AFRI values in HCC nodule vs. liver parenchyma beside HCC nodule vs. non-HCC liver parenchyma

Full size image

AUROC for predicting HCC was 0.8 and 0.76 for hepatic ARFI and TE, respectively, with a cutoff value of 2.28 m/s for hepatic SWV by ARFI and 28.8 kPa by TE. Hepatic ARFI displayed 95.6% sensitivity and 54.2% specificity while TE displayed 65% sensitivity and 80.2% specificity as shown in Table 3 and Fig. 2.

Table 3 Diagnostic performance, optimal cutoffs, and validity of hepatic ARFI, TE, and fibrosis scores for the prediction of HCC among patients with advanced hepatic fibrosis (≥F3) and cirrhosis (F4)
Full size table
Fig. 2
figure 2

Receiver–operator curve (ROC) curve of ARFI elastography and TE for diagnostic performance in the prediction of HCC occurrence in patients with advanced hepatic fibrosis (≥ F3) and cirrhosis (F4)

Full size image

The AUROC for FIB-4, APRI, AST/ALT ratio, and API were 0.76, 0.66, 0.72, and 0.7, respectively, for predicting HCC with a p value =< 0.01 for all methods. The best cutoff levels for FIB-4, APRI, AST/ALT ratio, and API were 3.2, 1, 1.4, and 8, respectively, with a sensitivity of 63.7%, 67.03%, 56.04%, and 70.3%, respectively, and a specificity of 73.7%, 61.7%, 81.1%, and 68%, respectively, as shown in Table 3.

Univariate regression analysis revealed that ARFI elatography and TE as well as fibrosis scores (FIB-4, API, and AST/ALT ratio) were significantly dependent variables in the prediction of HCC; however, hepatic ARFI has the highest odd ratio in the prediction of HCC as shown in Table 4.

Table 4 Univariate logistic regression model with non-invasive methods in the prediction of HCC among patients with advanced hepatic fibrosis (≥ F3) and cirrhosis (F4)
Full size table

Discussion

HCC is a common malignancy worldwide [19] with more than 700,000 new cases annually and ranking third as a cause of cancer-related death [20]. HCV is the leading cause of advanced liver fibrosis and cirrhosis, with an increased risk of developing HCC [21]. The early diagnosis and prediction of HCC are highly essential to implement curable management to reduce HCC-related deaths. Egypt has the highest burden of HCV infection in the world [22]. HCV is a major contributor to liver cirrhosis and cancer in Egypt [23].

The risk factors for HCC in chronic HCV patients have been widely studied and the degree of liver fibrosis is known to be the strongest one [24].

In this study, we investigated the clinical use of hepatic SWV measured with ARFI imaging in a large cohort of CHC patients with advanced hepatic fibrosis (≥ F3) and cirrhosis (F4) to set cutoff value for predicting HCC and early therapeutic decisions are made.

It was well known that serum albumin, bilirubin, and international normalized ratio (INR) reflecting the synthetic function of hepatocytes while AST and ALT correlated with both necroinflammation and hepatic fibrosis stage as well as platelets count reflect the severity of hepatic fibrosis. In addition, high AST and low platelets count were related to a higher stage of hepatic fibrosis and portal hypertension denoting severe hepatic fibrosis which favors progression to HCC [25].

These parameters were used to calculate non-invasive markers such as FIB-4, APRI, AAR ratio, and AP index which were previously studied and evaluated in predicting the risk of developing HCC [26,27,28,29,30,31].

Among these non-invasive markers, FIB-4 has been validated with regard to its longitudinal perspective to predict the development of HCC and other prognostic outcomes in viral hepatitis [26,27,28]. Our study was able to predict the development of HCC at a cutoff value of 3.2 in agreement with Ito et al. (2015) and Tamaki et al. (2014) who concluded that FIB-4 index >2.0 and ≤4.0, as well as FIB-4 index >3.25, could predict HCC development, respectively [29, 30]. Moreover, the present study showed APRI, AAR ratio, and AP index could predict HCC at a cutoff of 1, 1.4, and 8, respectively, and this was in agreement with Tseng et al. (2013) who showed APRI, AAR, and AP index at cutoff >1.4, ≥1, and ≥8, respectively, could predict the highest risk for HCC development in HCV patients [31].

In addition, LSM by TE was significantly higher among HCC patients in comparison to patients with advanced hepatic fibrosis (≥F3) and cirrhosis (F4) (non-HCC patients) and this was in accordance with previous studies which stated LS is significantly higher in patients with HCC than in patients without HCC [32, 33].

Furthermore, TE and fibrosis scores predict not only the hepatic fibrosis stage in CHC patients but they also seem to be a non-invasive alternative in predicting complications of cirrhosis including large esophageal varices, variceal bleeding, and HCC [34,35,36,37]. However, the presence of ascites in cirrhotic patients limits TE performance because of its inability to generate valid measurements [13].

Our study showed also that the AUROC curve of TE for prediction of HCC was 0.76 with a cutoff value of 28.8 kPa (sensitivity 65%, specificity 80.23%). This cutoff value is very similar to those reported by Masuzaki et al. [35] and Yosry et al. [38].

Several studies have confirmed that ARFI elatography is a more reliable method than TE in analyzing the progression of CLD toward cirrhosis [39] and demonstrated its usefulness in the evaluation of hepatic focal lesions because ARFI allows the dynamic visualization of the liver parenchyma and the placement of the ROI directly on the liver tissue; thus, ARFI elastography showed a satisfactory specificity for discriminating malignant lesions from benign lesions [40, 41].

Based on this fact, our study showed that the mean hepatic SWV measured with ARFI within HCC were significantly lower than hepatic parenchyma adjunct to HCC in HCC patients. This could be explained by the fact that HCC had a lower amount of collagen deposition, resulting in much softer than the surrounding hepatic parenchyma with very low elastometric values as was stated in previous studies [40,41,42,43], and another important finding was that ARFI values of HCC seemed to be similar to hepatic parenchyma in non-HCC in patients with advanced hepatic fibrosis ≥F3.

Similar to TE and fibrosis scores, ARFI was also studied for predicting complications of liver cirrhosis, especially portal hypertension and HCC [44, 45].

The present study reported that the AUROC curve of hepatic ARFI for predicting HCC was 0.79 with a cutoff of 2.28 m/s (sensitivity 95.6% and specificity 54.23%). This AUROC curve differed from the one obtained by Vermehren et al. [45] being higher this might be attributed to the patient numbers were consistently low in the study.

The limitations of the study are as follows: First, the diagnosis of HCC was based on imaging modalities [triphasic computed tomography (CT) or magnetic resonance imaging (MRI)], not on histological examination. Second, the size of the ROI did not cover the entire HCC; therefore, it might not reflect the heterogeneity of the entire HCC and stiffness measurement in the HCC ROI may not be representative of the full extent of stiffness variation within a tumor. Third, the number of HCC patients was relatively small. Therefore, further studies with larger numbers of HCC patients are warranted to determine the usefulness of ARFI elastography in this special patient population.

Conclusion

In conclusion, ARFI elastography can reflect changes in the stiffness of malignant focal liver lesions accurately and can be used in the prediction of HCC among patients with advanced hepatic fibrosis and cirrhosis in contrast to TE which cannot asses the focal lesion elasticity itself and also cannot be performed in decompensated cirrhotic patients (i.e., ascites).

Availability of data and materials

The data supporting the results are available from the corresponding author upon reasonable request.

Abbreviations

AAR:

AST/ALT ratio

ALT:

Alanine transaminase

API:

Age platelets index

APRI:

AST to Platelet Ratio Index

ARFI:

Acoustic radiation force impulse elastography

AST:

Aspartate transaminase

AUROC:

Receiver operating characteristic curve

CHC:

Chronic hepatitis C

CI:

Confidence interval

CLD:

Chronic liver disease

EASL:

European Association for the Study of the Liver

ElastPQ:

Elastography point quantification

FIB-4:

Fibrosis-4 score

HBV:

Hepatitis B virus

HCC:

Hepatocellular carcinoma

HCV:

Hepatitis C virus

INR:

International normalized ratio

IQR:

Interquartile range

kPa:

Kilopascal

LB:

Liver biopsy

LS:

Liver stiffness

LSM:

Liver stiffness measurement LSM

MRE:

Magnetic resonance elastography

NAFLD:

Non-alcoholic fatty liver disease

PCR:

Polymerase chain reaction

PEI:

Percutaneous ethanol injection

RFA:

Radiofrequency ablation

RNA:

Ribonucleic acid

ROI:

Region of Interest

SSI:

Supersonic shear imaging

SWV:

Shear wave velocity

TE:

Transient elastography

VTTQ:

Virtual touch tissue quantification

References

  1. Lavanchy D (2011) Evolving epidemiology of hepatitis C virus. Clin Microbiol Infection 17:107–115

    Article  CAS  Google Scholar 

  2. El-Serag HB (2011) Hepatocellular carcinoma. N Engl J Med 365:1118–1127

    Article  CAS  PubMed  Google Scholar 

  3. Singal AG, Volk ML, Jensen D et al (2010) A sustained viral response is associated with reduced liver-related morbidity and mortality in patients with hepatitis C virus. Clin Gastroenterol Hepatol 8:280–288

    Article  PubMed  Google Scholar 

  4. National Institutes of H (2002) National Institutes of Health consensus development conference statement: management of hepatitis C. Hepatology 36:S3-20

    Google Scholar 

  5. Saadeh S, Cammelli G, Carey WD et al (2001) The role of liver biopsy in chronic hepatitis C. Hepatology 33:196–200

    Article  CAS  PubMed  Google Scholar 

  6. Piccinino F, Sagnelli E, Pasquale G et al (1986) Complications following percutaneous liver biopsy. A multicentre retrospective study on 68,276 biopsies. Journal of Hepatology 2:165–73

    Article  CAS  PubMed  Google Scholar 

  7. Lucca Schiavon LD, Schiavon JL, Carvalho-Filho RJD (2014) Non-invasive diagnosis of liver fibrosis in chronic hepatitis C. World J Gastroenterol 20(11):2854e66

    Google Scholar 

  8. Ferraioli G, Parekh P, Levitov AB et al (2014) Shear wave elastography for evaluation of liver fibrosis. J Ultrasound Med 33:197203

    Article  Google Scholar 

  9. Asrani SK, Incorporation of noninvasive measures of liver fibrosis into clinical practice (2015) Diagnosis and prognosis. Clin Gastroenterol Hepatol 13(12):2190e204

    Article  Google Scholar 

  10. Fierbinteanu Braticevici C, Sporea I, Panaitescu E et al (2013) Value of acoustic radiation force impulse imaging elastography for non-invasive evaluation of patients with nonalcoholic fatty liver disease. Ultrasound Med Biol 39:1942–50

    Article  PubMed  Google Scholar 

  11. Bota S, Herkner H, Sporea I et al (2013) Meta-analysis: ARFI elastography versus transient elastography for the evaluation of liver fibrosis. Liver Int 33:1138–47

    Article  PubMed  Google Scholar 

  12. Galle PR, Forner A, Llovet JM, Mazzaferro V, Piscaglia F, Raoul JL et al (2018) EASL clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol 69(1):182–236

    Article  Google Scholar 

  13. Sandrin L, Fourquet B, Hasquenoph JM, Yon S et al (2003) Transient elastography: a new noninvasive method for assessment of hepatic fibrosis. Ultrasound Med Biol. 29:1705–1713

    Article  PubMed  Google Scholar 

  14. Friedrich-Rust M, Wunder K, Kriener S, Sotoudeh F, Richter S, Bojunga J et al (2009) Liver fibrosis in viral hepatitis: noninvasive assessment with acoustic radiation force impulse imaging versus transient elastography. Radiology 252:595–604

    Article  PubMed  Google Scholar 

  15. Wai CT, Greenson JK, Fontana RJ et al (2003) A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C. Hepatology 38:518–26

    Article  PubMed  Google Scholar 

  16. Sterling RK, Lissen E, Clumeck N et al (2006) Development of a simple noninvasive index to predict significant fibrosis inpatients with HIV/HCV co-infection. Hepatology 43:1317–25

    Article  CAS  PubMed  Google Scholar 

  17. Poynard T, Bedossa P (1997) Age and platelet count: a simple index for predicting the presence of histological lesions in patients with antibodies to hepatitis C virus. METAVIR and CLINIVIR Cooperative Study Groups. J Viral Hepatitis 4:199–208

    Article  CAS  Google Scholar 

  18. Williams AL, Hoofnagle JH (1988) Ratio of serum aspartate to alanine aminotransferase in chronic hepatitis Relationship to cirrhosis. Gastroenterology 95:734–739

    Article  CAS  PubMed  Google Scholar 

  19. Parkin DM, Bray F, Ferlay J, Pisani P (2005) Global cancer statistics, 2002. CA Cancer J Clin 55:74–108

    Article  PubMed  Google Scholar 

  20. Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M et al (2015) Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 136(5):E359-86. https://doi.org/10.1002/ijc.29210. (PMID: 25220842)

    Article  CAS  PubMed  Google Scholar 

  21. Llovet JM, Beaugrand M (2003) Hepatocellular carcinoma: present status and future prospects. J Hepatol 38(Suppl1):S136-49

    Article  PubMed  Google Scholar 

  22. El-Zanaty F, Way A (2009) Egypt Demographic and Health Survey 2008. Ministry of Health/Egypt, El-Zanaty and Associates/Egypt, and Macro International, Cairo. Available at http://dhsprogram.com/pubs/pdf/FR220/FR220.pdf

  23. Pybus OG, Drummond AJ, Nakano T et al (2003) The epidemiology and iatrogenic transmission of hepatitis C virus in Egypt: a Bayesian coalescent approach. Mol Biol Evol 20:381–387. https://doi.org/10.1093/molbev/msg043

    Article  CAS  PubMed  Google Scholar 

  24. Yoshida H, Shiratori Y, Moriyama M, Arakawa Y, Ide T, Sata M et al (1999) Interferon therapy reduces the risk for hepatocellular carcinoma: national surveillance program of cirrhotic and noncirrhotic patients with chronic hepatitis C in Japan. IHIT Study Group. Inhibition of Hepatocarcinogenesis by Interferon Therapy. Ann Intern Med 131:174–181

    Article  CAS  PubMed  Google Scholar 

  25. Nagamine T, Ohtuka T, Takehara K, Arai T, Takagi H, Mori M (1996) Thrombocytopenia associated with hepatitis C viral infection. J Hepatol 24(2):135–40

    Article  CAS  PubMed  Google Scholar 

  26. Suh B, Park S, Shin DW et al (2015) High liver fibrosis index FIB-4 is highly predictive of hepatocellular carcinoma in chronic hepatitis B carriers. Hepatology 61:1261–1268

    Article  CAS  PubMed  Google Scholar 

  27. Toyoda H, Kumada T, Tada T et al (2015) A laboratory marker, FIB-4 index, as a predictor for long-term outcomes of hepatocellular carcinoma patients after curative hepatic resection. Surgery 157:699–707

    Article  PubMed  Google Scholar 

  28. Berenguer J, Zamora FX, Aldamiz-Echevarria T et al (2015) Comparison of the prognostic value of liver biopsy and FIB-4 index in patients coinfected with HIV and hepatitis C virus. Clin Infect Dis. 60:950–958

    Article  CAS  PubMed  Google Scholar 

  29. Ito T, Kumada T, Toyoda H, Tada T, Kiriyama S et al (2015) Utility of the FIB-4 Index for hepatocarcinogenesis in hepatitis C virus carriers with normal alanine aminotransferase levels. J Viral Hepatitis 22:777–783

    Article  CAS  Google Scholar 

  30. Tamaki N, Kurosaki M, Matsuda S, Muraoka M, Yasui Y, Suzuki S, Hosokawa T, Ueda K, Tsuchiya K, Nakanishi H, Itakura J, Takahashi Y, Asahina Y, Izumi N (2014) Non-invasive prediction of hepatocellular carcinoma development using serum fibrosis marker in chronic hepatitis C patients. J Gastroenterol 49:1495–1503

    Article  CAS  PubMed  Google Scholar 

  31. Tseng PL, Wang JH, Hung CH, Tung HD, Chen TM et al (2013) Comparisons of noninvasive indices based on daily practice parameters for predicting liver cirrhosis in chronic hepatitis B and hepatitis C patients in hospital and community populations. Kaohsiung J Med Sci 29:385–395

    Article  PubMed  Google Scholar 

  32. Feier D, Lupsor Platon M, Stefanescu H, Badea R (2013) Transient elastography for the detection of hepatocellular carcinoma in viral C liver cirrhosis. Is there something else than increased liver stiffness? J Gastrointestin Liver Dis 22:283–289

    PubMed  Google Scholar 

  33. Wong GL (2013) Transient elastography: kill two birds with one stone? World J Hepatol 5:264–274

    Article  PubMed  PubMed Central  Google Scholar 

  34. Castera L, Le Bail B, Roudot-Thoraval F et al (2009) Early detection in routine clinical practice of cirrhosis and oesophageal varices in chronic hepatitis C: comparison of transient elastography (FibroScan) with standard laboratory tests and non-invasive scores. J Hepatol 50:59–68

    Article  PubMed  Google Scholar 

  35. Masuzaki R, Tateishi R, Yoshida H et al (2010) Prospective risk assessment for hepatocellular carcinoma development in patients with chronic hepatitis C by transient elastography. Hepatology 49:1954–61

    Article  Google Scholar 

  36. Foucher J, Chanteloup E, Vergniol J et al (2006) Diagnosis of cirrhosis by transient elastography (FibroScan): a prospective study. Gut 55:403–8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Vergniol J, Foucher J, Terrebonne E, Bernard PH, le Bail B, Merrouche W, Couzigon P, de Ledinghen V (2011) Noninvasive tests for fibrosis and liver stiffness predict 5-year outcomes of patients with chronic hepatitis C. Gastroenterology 140:1970-9-1979.e1–3

    Article  PubMed  Google Scholar 

  38. Yosry A, Fouad R, Abdel Hafez H, Ezz Al Arab M, Gohar M, Esmat G et al (2013) Transient elastography can predict the risk of hepatocellular carcinoma in egyptian patients with chronic hepatitis C. J Gastroenterol Hepatol Res 2(7):687–691

    CAS  Google Scholar 

  39. Rizzo L, Calvaruso V, Cacopardo B, Alessi N, Attanasio M, Petta S, Fatuzzo F et al (2011) Comparison of transient elastography and acoustic radiation force impulse for non-invasive staging of liver fibrosis in patients with chronic hepatitis C. Am J Gastroenterol 106:2112–2120

    Article  CAS  PubMed  Google Scholar 

  40. Frulio N, Laumonier H, Carteret T, Laurent C et al (2013) Evaluation of liver tumors using acoustic radiation force impulse elastography and correlation with histologic data. J Ultrasound Med 32:121–130

    Article  PubMed  Google Scholar 

  41. Bj Fahey, Rc Nelson, Dp Bradway, Sj Hsu, Dm Dumont, Ge Trahey et al (2008) In vivo visualization of abdominal malignancies with acoustic radiation force elastography. Phys Med Biol 53:279–293

    Article  Google Scholar 

  42. Cho SH, Lee JY, Han JK, Choi BI (2010) Acoustic radiation force impulse elastography for the evaluation of focal solid hepatic lesions: preliminary findings. Ultrasound Med Biol 36:202–208

    Article  PubMed  Google Scholar 

  43. Gallotti A, D’Onofrio M, Romanini L, Cantisani V, Pozzi Mucelli R et al (2012) Acoustic radiation force impulse (ARFI) ultrasound imaging of solid focal liver lesions. Eur J Radiol 81:451–455

    Article  CAS  PubMed  Google Scholar 

  44. Şirli R, Sporea I, Bota S et al (2010) Can acoustic radiation force impulse elastography (ARFI) predict the complications of liver cirrhosis? Rom J Intern Med 7:15–20

    Google Scholar 

  45. Vermehren J, Polta A, Zimmermann O et al (2012) Comparison of acoustic radiation force impulse imaging with transient elastography for the detection of complications in patients with cirrhosis. Liver Int 32:852–858

    Article  PubMed  Google Scholar 

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Acknowledgements

Very special thanks to Cairo University Center of Hepatic Fibrosis (CUC-HF) funded through Scientific Technology and Development Fund (STDF fund: project ID 5274) where this work was accomplished.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Endemic Medicine and Hepatology Department, Faculty of Medicine, Cairo University, Cairo, 11562, Egypt

    Shereen Abdel Alem, Heba omar, Naglaa Zayed, Mahasen Mabrouk & Ayman Yosry

Authors
  1. Shereen Abdel Alem
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  2. Heba omar
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  3. Naglaa Zayed
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  4. Mahasen Mabrouk
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  5. Ayman Yosry
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Contributions

All authors have substantially contributed to the conception and design, acquisition of the data, data analysis, and interpretation. All authors have agreed on the content of the manuscript. SAA: ARFI and Fibroscan operator, data analysis and interpretation, manuscript writing; HO: data collection, acquisition, and statistical analysis; NZ: conception and study design, interpretation of the results, and manuscript revision; MM: interpretation of the results and manuscript revision; AY: study design, conception, and manuscript revision. The authors read and approved the final manuscript.

Corresponding author

Correspondence to Shereen Abdel Alem.

Ethics declarations

Ethics approval and consent to participate

The study was conducted according to the principles of the Declaration of Helsinki and was approved by Institutional Review Board (IRB) of Faculty of Medicine (approval code; N-53-2014), Cairo University. Written informed consent was obtained from each patient prior to the TE and ARFI examinations.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Alem, S.A., omar, H., Zayed, N. et al. Clinical value of acoustic radiation force impulse elastography in the prediction of hepatocellular carcinoma in chronic hepatitis C patients. Egypt Liver Journal 13, 22 (2023). https://doi.org/10.1186/s43066-023-00258-8

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  • DOI: https://doi.org/10.1186/s43066-023-00258-8

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