Skip to main content
SpringerLink
Log in

Proposal of objective morphological classification system for hepatocellular carcinoma using preoperative multiphase computed tomography

  • Original Article—Liver, Pancreas, and Biliary Tract
  • Published:
Journal of Gastroenterology Aims and scope Submit manuscript

Abstract

Background

To establish a preoperative morphological classification system for hepatocellular carcinoma using multiphase computed tomography.

Methods

All consecutive patients who were diagnosed with hepatocellular carcinoma between 2004 and 2009 were enrolled, for a total of 232 patients. The concavity and convexity of each outer contour of hepatocellular carcinoma acquired from multiphase computed tomography were analyzed, and the area and depth of each indentation were quantified. The indentation area to tumor area ratio (s:S) and the s:S ratio multiplied by the indentation depth to indentation base ratio (s:S × d:t) were used as feature values reflecting the individual shapes.

Results

Using a hierarchical cluster analysis, the shapes were classified into three groups: Type I (smooth: n = 158), Type II (jagged: n = 63), and Type III (rough: n = 11). The 5-year survival rates for Types I, II, and III were 64, 53, and 0 %, respectively (I vs. II, P = 0.038; I vs. III, P = 0.001; II vs. III, P = 0.002). The 5-year disease-free survival rates for Types I, II, and III were 27, 23, and 0 %, respectively (I vs. III, P = 0.0003 and II vs. III, P = 0.008). Microscopic portal venous invasion was significantly more likely with Type III than with Type I or II (P < 0.001 and P = 0.001, respectively).

Conclusions

The newly developed semiautomatic computed tomography-based morphological classification system appears to provide a promising additional criterion for the prognostic categorization of patients with hepatocellular carcinoma.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Edmondson HA, Steiner PE. Primary carcinoma of the liver: a study of 100 cases among 48,900 necropsies. Cancer. 1954;7:462–503.

    Article  PubMed  CAS  Google Scholar 

  2. Nakashima T, Okuda K, Kojiro M, et al. Pathology of hepatocellular carcinoma in Japan. 232 consecutive cases autopsied in ten years. Cancer. 1983;51:863–77.

    Article  PubMed  CAS  Google Scholar 

  3. Okuda K, Peters RL, Simson IW. Gross anatomic features of hepatocellular carcinoma from three disparate geographic areas. Proposal of new classification. Cancer. 1984;54:2165–73.

    Article  PubMed  CAS  Google Scholar 

  4. Kanai T, Hirohashi S, Upton MP, et al. Pathology of small hepatocellular carcinoma. A proposal for a new gross classification. Cancer. 1987;60:810–9.

    Article  PubMed  CAS  Google Scholar 

  5. Takayama T, Makuuchi M, Hirohashi S, et al. Early hepatocellular carcinoma as an entity with a high rate of surgical cure. Hepatology. 1998;28:1241–6.

    Article  PubMed  CAS  Google Scholar 

  6. Japan LCSGo. General rules for the clinical and pathological study of primary liver cancer. 3rd English edition. Tokyo: Kanehara; 2010.

  7. Shimada M, Rikimaru T, Hamatsu T, et al. The role of macroscopic classification in nodular-type hepatocellular carcinoma. Am J Surg. 2001;182:177–82.

    Article  PubMed  CAS  Google Scholar 

  8. Yang JD, Kim WR, Park KW, et al. Model to estimate survival in ambulatory patients with hepatocellular carcinoma. Hepatology. 2012;56:614–21.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Takayasu K, Muramatsu Y, Mizuguchi Y, et al. CT evaluation of the progression of hypoattenuating nodular lesions in virus-related chronic liver disease. AJR Am J Roentgenol. 2006;187:454–63.

    Article  PubMed  Google Scholar 

  10. Breitenstein S, DeOliveira ML, Raptis DA, et al. Novel and simple preoperative score predicting complications after liver resection in noncirrhotic patients. Ann Surg. 2010;252:726–34.

    Article  PubMed  Google Scholar 

  11. Torzilli G, Minagawa M, Takayama T, et al. Accurate preoperative evaluation of liver mass lesions without fine-needle biopsy. Hepatology. 1999;30:889–93.

    Article  PubMed  CAS  Google Scholar 

  12. Leoni S, Piscaglia F, Golfieri R, et al. The impact of vascular and nonvascular findings on the noninvasive diagnosis of small hepatocellular carcinoma based on the EASL and AASLD criteria. Am J Gastroenterol. 2010;105:599–609.

    Article  PubMed  Google Scholar 

  13. Singal AG, Nehra M, Adams-Huet B, et al. Detection of hepatocellular carcinoma at advanced stages among patients in the HALT-C trial: where did surveillance fail? Am J Gastroenterol. 2013;108:425–32.

    Article  PubMed  Google Scholar 

  14. Ariizumi S, Kitagawa K, Kotera Y, et al. A non-smooth tumor margin in the hepatobiliary phase of gadoxetic acid disodium (Gd-EOB-DTPA)-enhanced magnetic resonance imaging predicts microscopic portal vein invasion, intrahepatic metastasis, and early recurrence after hepatectomy in patients with hepatocellular carcinoma. J Hepatobiliary Pancreat Sci. 2011;18:575–85.

    Article  PubMed  Google Scholar 

  15. Wakai T, Shirai Y, Nomura T, et al. Computed tomographic features of hepatocellular carcinoma predict long-term survival after hepatic resection. Eur J Surg Oncol. 2002;28:235–42.

    Article  PubMed  CAS  Google Scholar 

  16. Shirabe K, Aishima S, Taketomi A, et al. Prognostic importance of the gross classification of hepatocellular carcinoma in living donor-related liver transplantation. Br J Surg. 2011;98:261–7.

    Article  PubMed  CAS  Google Scholar 

  17. Bruix J, Sherman M. Management of hepatocellular carcinoma. Hepatology. 2005;42:1208–36.

    Article  PubMed  Google Scholar 

  18. Forner A, Llovet JM, Bruix J. Hepatocellular carcinoma. Lancet. 2012;379:1245–55.

    Article  PubMed  Google Scholar 

  19. Makuuchi M, Kosuge T, Takayama T, et al. Surgery for small liver cancers. Semin Surg Oncol. 1993;9:298–304.

    Article  PubMed  CAS  Google Scholar 

  20. Ward JHJ. Hierarchical grouping to optimize an objective function. J Am Stat Assoc. 1963;58:236–44.

    Article  Google Scholar 

  21. Minagawa M, Ikai I, Matsuyama Y, et al. Staging of hepatocellular carcinoma: assessment of the Japanese TNM and AJCC/UICC TNM systems in a cohort of 13,772 patients in Japan. Ann Surg. 2007;245:909–22.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Ringner M. What is principal component analysis? Nat Biotechnol. 2008;26:303–4.

    Article  PubMed  CAS  Google Scholar 

  23. LaVange LM, Koch GG, Schwartz TA. Applying sample survey methods to clinical trials data. Stat Med. 2001;20:2609–23.

    Article  PubMed  CAS  Google Scholar 

  24. Graubard BI, Korn EL. Regression analysis with clustered data. Stat Med. 1994;13:509–22.

    Article  PubMed  CAS  Google Scholar 

  25. Eguchi S, Takatsuki M, Hidaka M, et al. Predictor for histological microvascular invasion of hepatocellular carcinoma: a lesson from 229 consecutive cases of curative liver resection. World J Surg. 2010;34:1034–8.

    Article  PubMed  Google Scholar 

  26. Hui AM, Takayama T, Sano K, et al. Predictive value of gross classification of hepatocellular carcinoma on recurrence and survival after hepatectomy. J Hepatol. 2000;33:975–9.

    Article  PubMed  CAS  Google Scholar 

  27. Kawamura Y, Ikeda K, Hirakawa M, et al. New classification of dynamic computed tomography images predictive of malignant characteristics of hepatocellular carcinoma. Hepatol Res. 2010;40:1006–14.

    Article  PubMed  Google Scholar 

  28. Tanaka H, Iijima H, Higashiura A, et al. New malignant grading system for hepatocellular carcinoma using the Sonazoid contrast agent for ultrasonography. J Gastroenterol (Epub ahead of print).

  29. Yang LY, Fang F, Ou DP, et al. Solitary large hepatocellular carcinoma: a specific subtype of hepatocellular carcinoma with good outcome after hepatic resection. Ann Surg. 2009;249:118–23.

    Article  PubMed  Google Scholar 

  30. Choi GH, Han DH, Kim DH, et al. Outcome after curative resection for a huge (> or = 10 cm) hepatocellular carcinoma and prognostic significance of gross tumor classification. Am J Surg. 2009;198:693–701.

    Article  PubMed  Google Scholar 

  31. Shiina S, Tateishi R, Arano T, et al. Radiofrequency ablation for hepatocellular carcinoma: 10-year outcome and prognostic factors. Am J Gastroenterol. 2012;107:569–77.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  32. Torzilli G, Belghiti J, Kokudo N, et al. A snapshot of the effective indications and results of surgery for hepatocellular carcinoma in tertiary referral centers: is it adherent to the EASL/AASLD recommendations? An observational study of the HCC East-West Study Group. Ann Surg. 2013;257:929–37.

    Article  PubMed  Google Scholar 

  33. Hasegawa K, Kokudo N, Imamura H, et al. Prognostic impact of anatomic resection for hepatocellular carcinoma. Ann Surg. 2005;242:252–9.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Takayama T, Sekine T, Makuuchi M, et al. Adoptive immunotherapy to lower postsurgical recurrence rates of hepatocellular carcinoma: a randomised trial. Lancet. 2000;356:802–7.

    Article  PubMed  CAS  Google Scholar 

  35. Saito S, Yamanaka J, Miura K, et al. A novel 3D hepatectomy simulation based on liver circulation: application to liver resection and transplantation. Hepatology. 2005;41:1297–304.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

We thank Dr. Kousuke Ihara, Department of Electronics and Computer Science, Nihon University School of Science and Technology; Mr. Katsuhiko Sakurai; and Dr. Makiyo Ishiguro, Nihon University School of Medicine, for their technical support. This work was supported by a Nihon University Multidisciplinary Research Grant for 2011–2012 and by a Grant-in-Aid for Scientific Research (A) 24249068, Research (C) 25350856 from the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan.

Conflict of interest

The authors declare that they have no conflict of interest.

Author information

Authors and Affiliations

  1. Department of Digestive Surgery, Nihon University School of Medicine, 30-1 Oyaguchikami-machi, Itabashi-ku, Tokyo, 173-8610, Japan

    Hisashi Nakayama, Tadatoshi Takayama, Takao Okubo, Tokio Higaki, Yutaka Midorikawa & Masamichi Moriguchi

  2. Department of Electronics and Computer Science, Nihon University School of Science and Technology, 7-24-1 Narashinodai, Funabashi, Chiba, 274-8501, Japan

    Akiyoshi Itoh

Authors
  1. Hisashi Nakayama
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tadatoshi Takayama
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Takao Okubo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tokio Higaki
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yutaka Midorikawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Masamichi Moriguchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Akiyoshi Itoh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tadatoshi Takayama.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nakayama, H., Takayama, T., Okubo, T. et al. Proposal of objective morphological classification system for hepatocellular carcinoma using preoperative multiphase computed tomography. J Gastroenterol 49, 1430–1437 (2014). https://doi.org/10.1007/s00535-013-0908-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00535-013-0908-9

Keywords

Search

Navigation