nach oben

Digestive Diseases and Sciences

Erschienen in:

25.02.2021 | Original Article

Computed Tomography-Measured Liver Volume Predicts the Risk of Hepatocellular Carcinoma Development in Chronic Hepatitis C Patients

verfasst von: Namkyu Kang, Jung Wha Chung, Eun Sun Jang, Sook-Hyang Jeong, Jin-Wook Kim

Erschienen in: Digestive Diseases and Sciences | Ausgabe 12/2021

Einloggen, um Zugang zu erhalten

Abstract

Aim

In this retrospective cohort study, we evaluated the significance of liver volume in the prediction of hepatocellular carcinoma (HCC) in 277 chronic hepatitis C (CHC) patients who received dynamic computed tomography (CT) during surveillance.

Methods

Liver volumes were measured on portal venous phase of CT images by using ImageJ software. Liver volume index, a ratio of the standard liver volume expected by weight and height to the measured liver volume, was calculated to adjust for normal variations. The cohort was randomly divided to derivation (n = 100) and validation sets (n = 177) for the generation of a liver volume-based Cox prediction model and validation of a liver volume-based nomogram, respectively.

Results

The liver volume index was independent of weight or height, and it predicted further development of HCC (hazard ratio [HR] 16.30, 95% CI 6.70–39.62; p < 0.001). Liver cirrhosis, gamma-glutamyl transferase, and liver volume index were independent predictors of HCC, and nomogram-based prediction score from these three parameters identified high-risk patients at the cutoff of 110 in both derivation (p < 0.001) and validation cohort (p < 0.001).

Conclusion

Liver volume-based prediction model stratifies the risk of developing HCC in CHC patients whose initial dynamic CT study gave negative results.

Nur mit Berechtigung zugänglich

Disease GBD, Injury I, Prevalence C. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1545–1602. https://doi.org/10.1016/S0140-6736(16)31678-6.CrossRef

Wang H, Naghavi M, Allen C, et al. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1459–1544. https://doi.org/10.1016/S0140-6736(16)31012-1.CrossRef

Bang CS, Song IH. Impact of antiviral therapy on hepatocellular carcinoma and mortality in patients with chronic hepatitis C: systematic review and meta-analysis. BMC Gastroenterol. 2017;17:46. https://doi.org/10.1186/s12876-017-0606-9.CrossRefPubMedPubMedCentral

Conti F, Buonfiglioli F, Scuteri A, et al. Early occurrence and recurrence of hepatocellular carcinoma in HCV-related cirrhosis treated with direct-acting antivirals. J Hepatol. 2016;65:727–733. https://doi.org/10.1016/j.jhep.2016.06.015.CrossRefPubMed

Cheung MCM, Walker AJ, Hudson BE, et al. Outcomes after successful direct-acting antiviral therapy for patients with chronic hepatitis C and decompensated cirrhosis. J Hepatol. 2016;65:741–747. https://doi.org/10.1016/j.jhep.2016.06.019.CrossRefPubMed

Lee HW. Nonzero risk of hepatocellular carcinoma even after sustained virological response. Gut Liver. 2016;10:661–662. https://doi.org/10.5009/gnl16340.CrossRefPubMedPubMedCentral

Omata M, Cheng AL, Kokudo N, et al. Asia-Pacific clinical practice guidelines on the management of hepatocellular carcinoma: a 2017 update. Hepatol Int. 2017;11:317–370. https://doi.org/10.1007/s12072-017-9799-9.CrossRefPubMed

Heimbach JK, Kulik LM, Finn RS, et al. AASLD guidelines for the treatment of hepatocellular carcinoma. Hepatology. 2018;67:358–380. https://doi.org/10.1002/hep.29086.CrossRefPubMed

Korean Liver Cancer A, National Cancer C. 2018 Korean Liver Cancer Association-National Cancer Center Korea practice guidelines for the management of hepatocellular carcinoma. Gut Liver. 2019;13:227–299. https://doi.org/10.5009/,gnl19024.CrossRef

10.

Kokudo N, Takemura N, Hasegawa K, et al. Clinical practice guidelines for hepatocellular carcinoma: the Japan Society of Hepatology 2017 (4th JSH-HCC guidelines) 2019 update. Hepatol Res. 2019;49:1109–1113. https://doi.org/10.1111/hepr.13411.CrossRefPubMed

11.

European Association for the Study of the Liver. Electronic address eee, European Association for the Study of the L. EASL clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol. 2018;69:182–236. https://doi.org/10.1016/j.jhep.2018.03.019.CrossRef

12.

Ozaki K, Matsui O, Kobayashi S, et al. Selective atrophy of the middle hepatic venous drainage area in hepatitis C-related cirrhotic liver: morphometric study by using multidetector CT. Radiology. 2010;257:705–714. https://doi.org/10.1148/radiol.10100468.CrossRefPubMed

13.

Ito K, Mitchell DG, Hann HW, et al. Viral-induced cirrhosis: grading of severity using MR imaging. AJR. 1999;173:591–596. https://doi.org/10.2214/ajr.173.3.10470885.CrossRefPubMed

14.

Zhou XP, Lu T, Wei YG, Chen XZ. Liver volume variation in patients with virus-induced cirrhosis: findings on MDCT. AJR. 2007;189:W153–159. https://doi.org/10.2214/AJR.07.2181.CrossRefPubMed

15.

Kubota K, Makuuchi M, Kusaka K, et al. Measurement of liver volume and hepatic functional reserve as a guide to decision-making in resectional surgery for hepatic tumors. Hepatology. 1997;26:1176–1181. https://doi.org/10.1053/jhep.1997.v26.pm0009362359.CrossRefPubMed

16.

Suzuki K, Epstein ML, Kohlbrenner R, et al. Quantitative radiology: automated CT liver volumetry compared with interactive volumetry and manual volumetry. AJR. 2011;197:W706–712. https://doi.org/10.2214/AJR.10.5958.CrossRefPubMed

17.

Lim MC, Tan CH, Cai J, Zheng J, Kow AW. CT volumetry of the liver: where does it stand in clinical practice? Clin Radiol. 2014;69:887–895. https://doi.org/10.1016/j.crad.2013.12.021.CrossRefPubMed

18.

D’Onofrio M, De Robertis R, Demozzi E, Crosara S, Canestrini S, Pozzi Mucelli R. Liver volumetry: is imaging reliable? Personal experience and review of the literature. World J Radiol. 2014;6:62–71. https://doi.org/10.4329/wjr.v6.i4.62.CrossRefPubMedPubMedCentral

19.

Higashiyama H, Yamaguchi T, Mori K, et al. Graft size assessment by preoperative computed tomography in living related partial liver transplantation. Br J Surg. 1993;80:489–492.CrossRefPubMed

20.

Bruix J, Sherman M, American Association for the Study of Liver D. Management of hepatocellular carcinoma: an update. Hepatology. 2011;53:1020–1022. https://doi.org/10.1002/hep.24199.CrossRefPubMed

21.

Korean Liver Cancer Study G, National Cancer Center K. 2014 KLCSG-NCC Korea practice guideline for the management of hepatocellular carcinoma. Gut Liver. 2015;9:267–317. https://doi.org/10.5009/gnl14460.CrossRef

22.

Kudo M, Matsui O, Izumi N, et al. JSH consensus-based clinical practice guidelines for the management of hepatocellular carcinoma: 2014 update by the Liver Cancer Study Group of Japan. Liver Cancer. 2014;3:458–468. https://doi.org/10.1159/000343875.CrossRefPubMedPubMedCentral

23.

World Medical A. World Medical Association declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA. 2013;310:2191–2194. https://doi.org/10.1001/jama.2013.281053.CrossRef

24.

Lee CS, Jung YJ, Kim SS, et al. Liver volume-based prediction model stratifies risks for hepatocellular carcinoma in chronic hepatitis B patients on surveillance. PLoS ONE. 2018;13:e0190261. https://doi.org/10.1371/journal.pone.0190261.CrossRefPubMedPubMedCentral

25.

Um EH, Hwang S, Song GW, et al. Calculation of standard liver volume in Korean adults with analysis of confounding variables. Korean J Hepatobiliary Pancreat Surg. 2015;19:133–138. https://doi.org/10.14701/kjhbps.2015.19.4.133.CrossRefPubMedPubMedCentral

26.

Du Bois D, Du Bois EF. A formula to estimate the approximate surface area if height and weight be known. 1916. Nutrition. 1989;5:303–311. (discussion 312-303).PubMed

27.

Collins GS, Reitsma JB, Altman DG, Moons KG. Transparent reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement. Ann Intern Med. 2015;162:55–63. https://doi.org/10.7326/M14-0697.CrossRefPubMed

28.

Heagerty PJ, Zheng Y. Survival model predictive accuracy and ROC curves. Biometrics. 2005;61:92–105. https://doi.org/10.1111/j.0006-341X.2005.030814.x.CrossRefPubMed

29.

Schroder MS, Culhane AC, Quackenbush J, Haibe-Kains B. Survcomp: an R/Bioconductor package for performance assessment and comparison of survival models. Bioinformatics. 2011;27:3206–3208. https://doi.org/10.1093/bioinformatics/btr511.CrossRefPubMedPubMedCentral

30.

Kanwal F, Kramer JR, Asch SM, Cao Y, Li L, El-Serag HB. Long-term risk of hepatocellular carcinoma in HCV patients treated with direct acting antiviral agents. Hepatology. 2019;. https://doi.org/10.1002/hep.30823.CrossRefPubMed

31.

Nahon P, Layese R, Bourcier V, et al. Incidence of hepatocellular carcinoma after direct antiviral therapy for HCV in patients with cirrhosis included in surveillance programs. Gastroenterology. 2018;155:1436–1450e1436. https://doi.org/10.1053/j.gastro.2018.07.015.CrossRef

32.

Ganne-Carrie N, Layese R, Bourcier V, et al. Nomogram for individualized prediction of hepatocellular carcinoma occurrence in hepatitis C virus cirrhosis (ANRS CO12 CirVir). Hepatology. 2016;64:1136–1147. https://doi.org/10.1002/hep.28702.CrossRefPubMed

33.

van der Meer AJ, Hansen BE, Fattovich G, et al. Reliable prediction of clinical outcome in patients with chronic HCV infection and compensated advanced hepatic fibrosis: a validated model using objective and readily available clinical parameters. Gut. 2015;64:322–331. https://doi.org/10.1136/gutjnl-2013-305357.CrossRefPubMed

34.

Lee MH, Lu SN, Yuan Y, et al. Development and validation of a clinical scoring system for predicting risk of HCC in asymptomatic individuals seropositive for anti-HCV antibodies. PLoS ONE. 2014;9:e94760. https://doi.org/10.1371/journal.pone.0094760.CrossRefPubMedPubMedCentral

35.

Chang KC, Hung CH, Lu SN, et al. A novel predictive score for hepatocellular carcinoma development in patients with chronic hepatitis C after sustained response to pegylated interferon and ribavirin combination therapy. J Antimicrob Chemother. 2012;67:2766–2772. https://doi.org/10.1093/jac/dks269.CrossRefPubMed

36.

Chang KC, Wu YY, Hung CH, et al. Clinical-guide risk prediction of hepatocellular carcinoma development in chronic hepatitis C patients after interferon-based therapy. Br J Cancer. 2013;109:2481–2488. https://doi.org/10.1038/bjc.2013.564.CrossRefPubMedPubMedCentral

37.

El-Serag HB, Kanwal F, Davila JA, Kramer J, Richardson P. A new laboratory-based algorithm to predict development of hepatocellular carcinoma in patients with hepatitis C and cirrhosis. Gastroenterology. 2014;146:1249–1255e1241. https://doi.org/10.1053/j.gastro.2014.01.045.CrossRef

38.

Ikeda K, Arase Y, Saitoh S, et al. Prediction model of hepatocarcinogenesis for patients with hepatitis C virus-related cirrhosis. Validation with internal and external cohorts. J Hepatol. 2006;44:1089–1097. https://doi.org/10.1016/j.jhep.2006.02.008.CrossRefPubMed

39.

Yoshida H, Shiratori Y, Moriyama M, et al. 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. 1999;131:174–181.CrossRefPubMed

40.

Regev A, Berho M, Jeffers LJ, et al. Sampling error and intraobserver variation in liver biopsy in patients with chronic HCV infection. Am J Gastroenterol. 2002;97:2614–2618. https://doi.org/10.1111/j.1572-0241.2002.06038.x.CrossRefPubMed

41.

Bedossa P, Carrat F. Liver biopsy: the best, not the gold standard. J Hepatol. 2009;50:1–3. https://doi.org/10.1016/j.jhep.2008.10.014.CrossRefPubMed

42.

Masuzaki R, Tateishi R, Yoshida H, et al. Prospective risk assessment for hepatocellular carcinoma development in patients with chronic hepatitis C by transient elastography. Hepatology. 2009;49:1954–1961. https://doi.org/10.1002/hep.22870.CrossRefPubMed

43.

Wang JH, Yen YH, Yao CC, et al. Liver stiffness-based score in hepatoma risk assessment for chronic hepatitis C patients after successful antiviral therapy. Liver Int. 2016;36:1793–1799. https://doi.org/10.1111/liv.13179.CrossRefPubMed

44.

Sultanik P, Kramer L, Soudan D, et al. The relationship between liver stiffness measurement and outcome in patients with chronic hepatitis C and cirrhosis: a retrospective longitudinal hospital study. Aliment Pharmacol Therap. 2016;44:505–513. https://doi.org/10.1111/apt.13722.CrossRef

45.

Adler M, Larocca L, Trovato FM, Marcinkowski H, Pasha Y, Taylor-Robinson SD. Evaluating the risk of hepatocellular carcinoma in patients with prominently elevated liver stiffness measurements by FibroScan: a multicentre study. HPB (Oxford). 2016;18:678–683. https://doi.org/10.1016/j.hpb.2016.05.005.CrossRef

46.

De Mitri MS, Poussin K, Baccarini P, et al. HCV-associated liver cancer without cirrhosis. Lancet. 1995;345:413–415.CrossRefPubMed

47.

el-Refaie A, Savage K, Bhattacharya S, et al. HCV-associated hepatocellular carcinoma without cirrhosis. J Hepatol. 1996;24:277–285.CrossRefPubMed

48.

Suzuki K, Kohlbrenner R, Epstein ML, Obajuluwa AM, Xu J, Hori M. Computer-aided measurement of liver volumes in CT by means of geodesic active contour segmentation coupled with level-set algorithms. Med Phys. 2010;37:2159–2166. https://doi.org/10.1118/1.3395579.CrossRefPubMedPubMedCentral

49.

Everhart JE, Wright EC. Association of gamma-glutamyl transferase (GGT) activity with treatment and clinical outcomes in chronic hepatitis C (HCV). Hepatology. 2013;57:1725–1733. https://doi.org/10.1002/hep.26203.CrossRefPubMed

50.

Rodgers SK, Fetzer DT, Gabriel H, et al. Role of US LI-RADS in the LI-RADS algorithm. Radiographics. 2019;39:690–708. https://doi.org/10.1148/rg.2019180158.CrossRefPubMed

Titel: Computed Tomography-Measured Liver Volume Predicts the Risk of Hepatocellular Carcinoma Development in Chronic Hepatitis C Patients
verfasst von: Namkyu Kang
Jung Wha Chung
Eun Sun Jang
Sook-Hyang Jeong
Jin-Wook Kim
Publikationsdatum: 25.02.2021
Verlag: Springer US
Erschienen in: Digestive Diseases and Sciences / Ausgabe 12/2021
Print ISSN: 0163-2116
Elektronische ISSN: 1573-2568
DOI: https://doi.org/10.1007/s10620-020-06762-w

Leitlinien kompakt für die Innere Medizin

Mit medbee Pocketcards sicher entscheiden.

^{Seit 2022 gehört die medbee GmbH zum Springer Medizin Verlag}

Kostenlos registrieren

Neu im Fachgebiet Innere Medizin

24.04.2024 | DGIM 2024 | Kongressbericht | Nachrichten

Update Innere Medizin

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.

Newsletter bestellen

Springer Medizin

Computed Tomography-Measured Liver Volume Predicts the Risk of Hepatocellular Carcinoma Development in Chronic Hepatitis C Patients

Abstract

Aim

Methods

Results

Conclusion

Leitlinien kompakt für die Innere Medizin

Neu im Fachgebiet Innere Medizin

Metformin rückt in den Hintergrund

Myokarditis nach Infekt – richtig schwierig wird es bei Profisportlern

Thrombophiliescreening – Wenn, dann richtig und nur bei therapeutischer Konsequenz

Bei Senioren mit Prostatakarzinom auf Anämie achten!

Update Innere Medizin

Springer Medizin

Abstract

Aim

Methods

Results

Conclusion

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 12/2021

Regional Gastrointestinal Transit and Contractility Patterns Vary in Postural Orthostatic Tachycardia Syndrome (POTS)

Price Is Right: Exploring Prescription Drug Coverage Barriers for Irritable Bowel Syndrome Using Threshold Pricing Analysis

Recurrence of Clostridium Difficile and Cytomegalovirus Infections in Patients with Ulcerative Colitis Who Undergo Ileal Pouch-Anal Anastomosis

Circular RNA circZFR Promotes Hepatocellular Carcinoma Progression by Regulating miR-375/HMGA2 Axis

Liver Biopsy in Pregnancy: Two Case Reports and Review of the Literature

Mesenteric Lymph Duct Ligation Alleviates Acute Lung Injury Caused by Severe Acute Pancreatitis Through Inhibition of High Mobility Group Box 1-Induced Inflammation in Rats

Leitlinien kompakt für die Innere Medizin

Neu im Fachgebiet Innere Medizin

Metformin rückt in den Hintergrund

Myokarditis nach Infekt – richtig schwierig wird es bei Profisportlern

Thrombophiliescreening – Wenn, dann richtig und nur bei therapeutischer Konsequenz

Bei Senioren mit Prostatakarzinom auf Anämie achten!

Update Innere Medizin