Skip to main content

Accuracy of liver surface nodularity quantification on MDCT for staging hepatic fibrosis in patients with hepatitis C virus

Abstract

Purpose

To evaluate semi-automated measurement of liver surface nodularity (LSN) on MDCT in a cause-specific cohort of patients with chronic hepatitis C virus infection (HCV) for identification of hepatic fibrosis (stages F0–4).

Methods

MDCT scans in patients with known HCV were evaluated with an independently validated, semi-automated LSN measurement tool. Consecutive LSN measurements along the anterior liver surface were performed to derive mean LSN scores. Scores were compared with METAVIR fibrosis stage (F0–4). Fibrosis stages F0–3 were based on biopsy results within 1 year of CT. Most patients with cirrhosis (F4) also had biopsy within 1 year; the remaining cases had unequivocal clinical/imaging evidence of cirrhosis and biopsy was not indicated.

Results

288 patients (79F/209M; mean age, 49.7 years) with known HCV were stratified based on METAVIR fibrosis stage: F0 (n = 43), F1 (n = 29), F2 (n = 53), F3 (n = 37), and F4 (n = 126). LSN scores increased with increasing fibrosis (mean: F0 = 2.3 ± 0.2, F1 = 2.4 ± 0.3, F2 = 2.6 ± 0.5, F3 = 2.9 ± 0.6, F4 = 3.8 ± 1.0; p < 0.001). For identification of significant fibrosis (≥ F2), advanced fibrosis (≥ F3), and cirrhosis (≥ F4), the ROC AUCs were 0.88, 0.89, and 0.90, respectively. The sensitivity and specificity for significant fibrosis (≥ F2) using LSN threshold of 2.80 were 0.68 and 0.97; for advanced fibrosis (≥ F3; threshold = 2.77) were 0.83 and 0.85; and for cirrhosis (≥ F4, LSN threshold = 2.9) were 0.90 and 0.80.

Conclusion

Liver surface nodularity assessment at MDCT allows for accurate discrimination of intermediate stages of hepatic fibrosis in a cause-specific cohort of patients with HCV, particularly at more advanced levels.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  1. Freiman JM, Tran TM, Schumacher SG, et al. (2016) Hepatitis C core antigen testing for diagnosis of hepatitis C virus infection: a systematic review and meta-analysis. Ann Intern Med 165:345–355

    Article  Google Scholar 

  2. WHO (2017) Hepatitis C virus fact sheet. Accessed 17 May 2017

  3. Gower E, Estes C, Blach S, Razavi-Shearer K, Razavi H (2014) Global epidemiology and genotype distribution of the hepatitis C virus infection. J Hepatol 61:S45–S57

    Article  Google Scholar 

  4. Nuno Solinis R, Arratibel Ugarte P, Rojo A, Sanchez Gonzalez Y (2016) Value of treating all stages of chronic hepatitis C: a comprehensive review of clinical and economic evidence. Infect Dis Ther 5:491–508

    Article  Google Scholar 

  5. Friedrich-Rust M, Nierhoff J, Lupsor M, et al. (2012) Performance of acoustic radiation force impulse imaging for the staging of liver fibrosis: a pooled meta-analysis. J Viral Hepat 19:E212–E219

    CAS  Article  Google Scholar 

  6. Friedrich-Rust M, Ong M-F, Martens S, et al. (2008) Performance of transient elastography for the staging of liver fibrosis: a meta-analysis. Gastroenterology 134:960–974

    Article  Google Scholar 

  7. Singh S, Venkatesh SK, Wang Z, et al. (2015) Diagnostic performance of magnetic resonance elastography in staging liver fibrosis: a systematic review and meta-analysis of individual participant data. Clin Gastroenterol Hepatol 13:440–451

    Article  Google Scholar 

  8. Talwalkar JA, Kurtz DM, Schoenleber SJ, West CP, Montori VM (2007) Utrasound-based transient elastography for the detection of hepatic fibrosis: systematic review and meta-analysis. Clin Gastroenterol Hepatol 5:1214–1220

    Article  Google Scholar 

  9. Wang Q-B, Zhu H, Liu H-L, Zhang B (2012) Performance of magnetic resonance elastography and diffusion-weighted imaging for the staging of hepatic fibrosis: a meta-analysis. Hepatology 56:239–247

    Article  Google Scholar 

  10. Castera L, Vergniol J, Foucher J, et al. (2005) Prospective comparison of transient elastography, fibrotest, APRI, and liver biopsy for the assessment of fibrosis in chronic hepatitis C. Gastroenterology 128:343–350

    Article  Google Scholar 

  11. Foucher J, Chanteloup E, Vergniol J, et al. (2006) Diagnosis of cirrhosis by transient elastography (FibroScan): a prospective study. Gut 55:403–408

    CAS  Article  Google Scholar 

  12. Yin M, Glaser KJ, Talwalkar JA, et al. (2016) Hepatic MR elastography: clinical performance in a series of 1377 consecutive examinations. Radiology 278:114–124

    Article  Google Scholar 

  13. Tang A, Cloutier G, Szeverenyi NM, Sirlin CB (2015) Ultrasound elastography and MR elastography for assessing liver fibrosis: part 2, diagnostic performance, confounders, and future directions. Am J Roentgenol 205:33–40

    Article  Google Scholar 

  14. Wagner M, Corcuera-Solano I, Lo G, et al. (2017) Technical failure of MR elastography examinations of the liver: experience from a large single-center study. Radiology. https://doi.org/10.1148/radiol.2016160863:160863

    Article  PubMed  PubMed Central  Google Scholar 

  15. Petitclerc L, Sebastiani G, Gilbert G, Cloutier G, Tang A (2016) Liver fibrosis: review of current imaging and MRI quantification techniques. J Magn Reson Imaging. https://doi.org/10.1002/jmri.25550

    Article  PubMed  Google Scholar 

  16. Furusato Hunt OM, Lubner MG, Ziemlewicz TJ, Munoz Del Rio A, Pickhardt PJ (2016) The liver segmental volume ratio for noninvasive detection of cirrhosis: comparison with established linear and volumetric measures. J Comput Assist Tomogr 40:478–484

    Article  Google Scholar 

  17. Honda H, Onitsuka H, Masuda K, et al. (1990) Chronic liver disease: value of volumetry of liver and spleen with computed tomography. Radiat Med 8:222–226

    CAS  PubMed  Google Scholar 

  18. Smith AD, Branch CR, Zand K, et al. (2016) Liver surface nodularity quantification from routine CT images as a biomarker for detection and evaluation of cirrhosis. Radiology 280:771–781

    Article  Google Scholar 

  19. Zhou X, Lu T, Wei Y, Chen X (2007) Liver volume variation in patients with virus-induced cirrhosis: findings on MDCT. AJR 189:W153–W159

    Article  Google Scholar 

  20. Smith AD, Zand KA, Florez E, et al. (2016) Liver surface nodularity score allows prediction of cirrhosis decompensation and death. Radiology. https://doi.org/10.1148/radiol.2016160799:160799

    Article  PubMed  Google Scholar 

  21. Pickhardt PJ, Malecki K, Hunt OF, et al. (2017) Hepatosplenic volumetric assessment at MDCT for staging liver fibrosis. Eur Radiol 27:3060–3068

    Article  Google Scholar 

  22. Pickhardt PJ, Malecki K, Kloke J, Lubner MG (2016) Accuracy of liver surface nodularity quantification on MDCT as a noninvasive biomarker for staging hepatic fibrosis. AJR 207:1194–1199

    Article  Google Scholar 

  23. Lo GC, Besa C, King MJ, et al. (2017) Feasibility and reproducibility of liver surface nodularity quantification for the assessment of liver cirrhosis using CT and MRI. Eur J Radiol Open 4:95–100

    Article  Google Scholar 

  24. Smith AD, Branch CR, Zand K, et al. (2016) Liver surface nodularity quantification from routine computed tomography images as a biomarker for detection and evaluation of cirrhosis. Radiology 280:771–781

    Article  Google Scholar 

  25. Bedossa P, Poynard T (1996) An algorithm for the grading of activity in chronic hepatitis C. The METAVIR cooperative study group. Hepatology 24:289–293

    CAS  Article  Google Scholar 

  26. Martinez SM, Crespo G, Navasa M, Forns X (2011) Noninvasive assessment of liver fibrosis. Hepatology 53:325–335

    Article  Google Scholar 

  27. Daginawala N, Li B, Buch K, et al. (2016) Using texture analyses of contrast enhanced CT to assess hepatic fibrosis. Eur J Radiol 85:511–517

    Article  Google Scholar 

  28. Lubner MG, Malecki K, Kloke J, Ganeshan B, Pickhardt PJ (2017) Texture analysis of the liver at MDCT for assessing hepatic fibrosis. Abdom Radiol 42:2069–2078

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Meghan G. Lubner.

Ethics declarations

Funding

No funding supported this work.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The need for informed consent was waived.

Disclosures

MGL: Grant funding—Philips, Ethicon. PJP: Co-founder, VirtuoCTC, Advisor to Check-Cap, Shareholder in Cellectar, Elucent, SHINE and for other authors there are no relevant disclosures.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lubner, M.G., Jones, D., Said, A. et al. Accuracy of liver surface nodularity quantification on MDCT for staging hepatic fibrosis in patients with hepatitis C virus. Abdom Radiol 43, 2980–2986 (2018). https://doi.org/10.1007/s00261-018-1572-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-018-1572-6

Keywords

  • Computed tomography
  • Liver surface nodularity
  • Hepatitis C virus
  • Liver fibrosis