Log in

Histogram Analysis of CT Perfusion of Hepatocellular Carcinoma for Predicting Response to Transarterial Radioembolization: Value of Tumor Heterogeneity Assessment

  • Clinical Investigation
  • Published:
CardioVascular and Interventional Radiology Aims and scope Submit manuscript

Abstract

Purpose

To evaluate in patients with hepatocellular carcinoma (HCC), whether assessment of tumor heterogeneity by histogram analysis of computed tomography (CT) perfusion helps predicting response to transarterial radioembolization (TARE).

Materials and Methods

Sixteen patients (15 male; mean age 65 years; age range 47–80 years) with HCC underwent CT liver perfusion for treatment planning prior to TARE with Yttrium-90 microspheres. Arterial perfusion (AP) derived from CT perfusion was measured in the entire tumor volume, and heterogeneity was analyzed voxel-wise by histogram analysis. Response to TARE was evaluated on follow-up imaging (median follow-up, 129 days) based on modified Response Evaluation Criteria in Solid Tumors (mRECIST). Results of histogram analysis and mean AP values of the tumor were compared between responders and non-responders. Receiver operating characteristics were calculated to determine the parameters’ ability to discriminate responders from non-responders.

Results

According to mRECIST, 8 patients (50 %) were responders and 8 (50 %) non-responders. Comparing responders and non-responders, the 50th and 75th percentile of AP derived from histogram analysis was significantly different [AP 43.8/54.3 vs. 27.6/34.3 mL min−1 100 mL−1); p < 0.05], while the mean AP of HCCs (43.5 vs. 27.9 mL min−1 100 mL−1; p > 0.05) was not. Further heterogeneity parameters from histogram analysis (skewness, coefficient of variation, and 25th percentile) did not differ between responders and non-responders (p > 0.05). If the cut-off for the 75th percentile was set to an AP of 37.5 mL min−1 100 mL−1, therapy response could be predicted with a sensitivity of 88 % (7/8) and specificity of 75 % (6/8).

Conclusion

Voxel-wise histogram analysis of pretreatment CT perfusion indicating tumor heterogeneity of HCC improves the pretreatment prediction of response to TARE.

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

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Germany)

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Hilgard P, Hamami M, Fouly AE, Scherag A, Muller S, Ertle J, et al. Radioembolization with yttrium-90 glass microspheres in hepatocellular carcinoma: European experience on safety and long-term survival. Hepatology. 2010;52:1741–9.

    Article  CAS  PubMed  Google Scholar 

  2. Inarrairaegui M, Martinez-Cuesta A, Rodriguez M, Bilbao JI, Arbizu J, Benito A, et al. Analysis of prognostic factors after yttrium-90 radioembolization of advanced hepatocellular carcinoma. Int J Radiat Oncol Biol Phys. 2010;77:1441–8.

    Article  PubMed  Google Scholar 

  3. Dancey JE, Shepherd FA, Paul K, Sniderman KW, Houle S, Gabrys J, et al. Treatment of nonresectable hepatocellular carcinoma with intrahepatic 90Y-microspheres. J Nucl Med. 2000;41:1673–81.

    CAS  PubMed  Google Scholar 

  4. Jain RK. Normalization of tumor vasculature: an emerging concept in antiangiogenic therapy. Science. 2005;307:58–62.

    Article  CAS  PubMed  Google Scholar 

  5. Simpson-Herren L, Noker PE, Wagoner SD. Variability of tumor response to chemotherapy. II. Contribution of tumor heterogeneity. Cancer Chemother Pharmacol. 1988;22:131–6.

    Article  CAS  PubMed  Google Scholar 

  6. Eccles SA, Welch DR. Metastasis: recent discoveries and novel treatment strategies. Lancet. 2007;369:1742–57.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  7. Thng CH, Koh TS, Collins DJ, Koh DM. Perfusion magnetic resonance imaging of the liver. World J Gastroenterol. 2010;16:1598–609.

    Article  PubMed Central  PubMed  Google Scholar 

  8. Sahani DV, Holalkere NS, Mueller PR, Zhu AX. Advanced hepatocellular carcinoma: CT perfusion of liver and tumor tissue–initial experience. Radiology. 2007;243:736–43.

    Article  PubMed  Google Scholar 

  9. Morsbach F, Pfammatter T, Reiner CS, Fischer MA, Sah BR, Winklhofer S, et al. Computed tomographic perfusion imaging for the prediction of response and survival to transarterial radioembolization of liver metastases. Invest Radiol. 2013;48:787–94.

    Article  PubMed  Google Scholar 

  10. Reiner CS, Morsbach F, Sah BR, Puippe G, Schaefer N, Pfammatter T, et al. Early treatment response evaluation after yttrium-90 radioembolization of liver malignancy with CT perfusion. J Vasc Interv Radiol. 2014;25:747–59.

    Article  PubMed  Google Scholar 

  11. Mayr NA, Yuh WT, Arnholt JC, Ehrhardt JC, Sorosky JI, Magnotta VA, et al. Pixel analysis of MR perfusion imaging in predicting radiation therapy outcome in cervical cancer. J Magn Reson Imaging. 2000;12:1027–33.

    Article  CAS  PubMed  Google Scholar 

  12. Ng F, Ganeshan B, Kozarski R, Miles KA, Goh V. Assessment of primary colorectal cancer heterogeneity by using whole-tumor texture analysis: contrast-enhanced CT texture as a biomarker of 5-year survival. Radiology. 2013;266:177–84.

    Article  PubMed  Google Scholar 

  13. Patankar TF, Haroon HA, Mills SJ, Baleriaux D, Buckley DL, Parker GJ, et al. Is volume transfer coefficient (K(trans)) related to histologic grade in human gliomas? Am J Neuroradiol. 2005;26:2455–65.

    PubMed  Google Scholar 

  14. Ng F, Kozarski R, Ganeshan B, Goh V. Assessment of tumor heterogeneity by CT texture analysis: can the largest cross-sectional area be used as an alternative to whole tumor analysis? Eur J Radiol. 2013;82:342–8.

    Article  PubMed  Google Scholar 

  15. Chapiro J, Duran R, Lin M, Schernthaner RE, Wang Z, Gorodetski B, et al. Identifying staging markers for hepatocellular carcinoma before transarterial chemoembolization: comparison of three-dimensional quantitative versus non-three-dimensional Imaging markers. Radiology. 2015;275:438–47.

    Article  PubMed Central  PubMed  Google Scholar 

  16. European Association For The Study of The L, European Organisation For R, Treatment Of C. EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol. 2012;56:908–43.

    Article  Google Scholar 

  17. Reiner CS, Morsbach F, Sah BR, Puippe G, Schaefer N, Pfammatter T, et al. Early treatment response evaluation after yttrium-90 radioembolization of liver malignancy with CT perfusion. J Vasc Interv Radiol. 2014;25:747–59.

    Article  PubMed  Google Scholar 

  18. Goetti R, Leschka S, Desbiolles L, Klotz E, Samaras P, von Boehmer L, et al. Quantitative computed tomography liver perfusion imaging using dynamic spiral scanning with variable pitch: feasibility and initial results in patients with cancer metastases. Invest Radiol. 2010;45:419–26.

    PubMed  Google Scholar 

  19. Denys A, Pracht M, Duran R, Guiu B, Adib S, Boubaker A, et al. How to prepare a patient for transarterial radioembolization? A practical guide. Cardiovasc Intervent Radiol. 2015;38(2):372–80.

    Article  Google Scholar 

  20. Lau WY, Kennedy AS, Kim YH, Lai HK, Lee RC, Leung TW, et al. Patient selection and activity planning guide for selective internal radiotherapy with yttrium-90 resin microspheres. Int J Radiat Oncol Biol Phys. 2012;82:401–7.

    Article  PubMed  Google Scholar 

  21. Cosimelli M, Mancini R, Carpanese L, Sciuto R, Pizzi G, Pattaro G, et al. Integration of radioembolisation into multimodal treatment of liver-dominant metastatic colorectal cancer. Expert Opin Ther Targets. 2012;16(Suppl 2):S11–6.

    Article  CAS  PubMed  Google Scholar 

  22. Saddi KA, Chefd’hotel C, Cheriet F. Large deformation registration of contrast-enhanced images with volume-preserving constraint. In: Pluim JPW, Reinhard JM, editors. Proceedings of The International Society for Optical Engineering (SPIE). Washington: Bellingham; 2007.

    Google Scholar 

  23. Miles KA, Hayball MP, Dixon AK. Functional images of hepatic perfusion obtained with dynamic CT. Radiology. 1993;188:405–11.

    Article  CAS  PubMed  Google Scholar 

  24. Blomley MJ, Coulden R, Dawson P, Kormano M, Donlan P, Bufkin C, et al. Liver perfusion studied with ultrafast CT. J Comput Assist Tomogr. 1995;19:424–33.

    Article  CAS  PubMed  Google Scholar 

  25. Tsushima Y, Funabasama S, Aoki J, Sanada S, Endo K. Quantitative perfusion map of malignant liver tumors, created from dynamic computed tomography data. Acad Radiol. 2004;11:215–23.

    Article  PubMed  Google Scholar 

  26. Lencioni R, Llovet JM. Modified RECIST (mRECIST) assessment for hepatocellular carcinoma. Semin Liver Dis. 2010;30:52–60.

    Article  CAS  PubMed  Google Scholar 

  27. Eisenhauer EA, Therasse P, Bogaerts J, Schwartz LH, Sargent D, Ford R, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45:228–47.

    Article  CAS  PubMed  Google Scholar 

  28. Bonekamp S, Halappa VG, Geschwind JF, Li Z, Corona-Villalobos CP, Reyes D, et al. Unresectable hepatocellular carcinoma: MR imaging after intraarterial therapy. Part II. Response stratification using volumetric functional criteria after intraarterial therapy. Radiology. 2013;268:431–9.

    Article  PubMed  Google Scholar 

  29. Cicchetti DV. Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychol Assess. 1994;6:284–90.

    Article  Google Scholar 

  30. Flamen P, Vanderlinden B, Delatte P, Ghanem G, Ameye L, Van Den Eynde M, et al. Multimodality imaging can predict the metabolic response of unresectable colorectal liver metastases to radioembolization therapy with Yttrium-90 labeled resin microspheres. Phys Med Biol. 2008;53:6591–603.

    Article  PubMed  Google Scholar 

  31. Morsbach F, Sah BR, Spring L, Puippe G, Gordic S, Seifert B, et al. Perfusion CT best predicts outcome after radioembolization of liver metastases: a comparison of radionuclide and CT imaging techniques. Eur Radiol. 2014;24:1455–65.

    Article  PubMed  Google Scholar 

  32. Sato KT, Omary RA, Takehana C, Ibrahim S, Lewandowski RJ, Ryu RK, et al. The role of tumor vascularity in predicting survival after yttrium-90 radioembolization for liver metastases. J Vasc Interv Radiol. 2009;20:1564–9.

    Article  PubMed  Google Scholar 

  33. Garin E, Lenoir L, Rolland Y, Edeline J, Mesbah H, Laffont S, et al. Dosimetry based on 99mTc-macroaggregated albumin SPECT/CT accurately predicts tumor response and survival in hepatocellular carcinoma patients treated with 90Y-loaded glass microspheres: preliminary results. J Nucl Med. 2012;53:255–63.

    Article  CAS  PubMed  Google Scholar 

  34. Reiner CS, Goetti R, Burger IA, Fischer MA, Frauenfelder T, Knuth A, et al. Liver perfusion imaging in patients with primary and metastatic liver malignancy: prospective comparison between 99mTc-MAA spect and dynamic CT perfusion. Acad Radiol. 2012;19:613–21.

    Article  PubMed  Google Scholar 

  35. Kucuk ON, Soydal C, Araz M, Bilgic S, Ibis E. Prognostic importance of 18F-FDG uptake pattern of hepatocellular cancer patients who received SIRT. Clin Nucl Med. 2013;38:e283–9.

    Article  PubMed  Google Scholar 

  36. Katyal S, Oliver JH, Peterson MS, Chang PJ, Baron RL, Carr BI. Prognostic significance of arterial phase CT for prediction of response to transcatheter arterial chemoembolization in unresectable hepatocellular carcinoma: a retrospective analysis. Am J Roentgenol. 2000;175:1665–72.

    Article  CAS  Google Scholar 

  37. Yu MH, Kim JH, Yoon JH, Kim HC, Chung JW, Han JK, et al. Role of C-arm CT for transcatheter arterial chemoembolization of hepatocellular carcinoma: diagnostic performance and predictive value for therapeutic response compared with gadoxetic acid-enhanced MRI. Am J Roentgenol. 2013;201:675–83.

    Article  Google Scholar 

  38. Campbell AM, Bailey IH, Burton MA. Analysis of the distribution of intra-arterial microspheres in human liver following hepatic yttrium-90 microsphere therapy. Phys Med Biol. 2000;45:1023–33.

    Article  CAS  PubMed  Google Scholar 

  39. Nelson DA, Tan TT, Rabson AB, Anderson D, Degenhardt K, White E. Hypoxia and defective apoptosis drive genomic instability and tumorigenesis. Genes Dev. 2004;18:2095–107.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  40. Britten RA, Evans AJ, Allalunis-Turner MJ, Franko AJ, Pearcey RG. Intratumoral heterogeneity as a confounding factor in clonogenic assays for tumour radioresponsiveness. Radiother Oncol. 1996;39:145–53.

    Article  CAS  PubMed  Google Scholar 

  41. Yang X, Knopp MV. Quantifying tumor vascular heterogeneity with dynamic contrast-enhanced magnetic resonance imaging: a review. J Biomed Biotechnol. 2011;2011:732848.

    PubMed Central  PubMed  Google Scholar 

  42. Ulrych TJ, Velis DR, Woodbury AD, Sacchi MD. L-moments and C-moments. Stoch Env Res Risk Assess. 2000;14:50–68.

    Article  Google Scholar 

  43. Chalian H, Tochetto SM, Tore HG, Rezai P, Yaghmai V. Hepatic tumors: region-of-interest versus volumetric analysis for quantification of attenuation at CT. Radiology. 2012;262:853–61.

    Article  PubMed  Google Scholar 

  44. Rose CJ, Mills SJ, O’Connor JP, Buonaccorsi GA, Roberts C, Watson Y, et al. Quantifying spatial heterogeneity in dynamic contrast-enhanced MRI parameter maps. Magn Reson Med. 2009;62:488–99.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Caecilia S. Reiner.

Ethics declarations

Conflict of interest

All authors declare that they have no conflicts of interest regarding this study.

Research Involving Human Participants

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.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Reiner, C.S., Gordic, S., Puippe, G. et al. Histogram Analysis of CT Perfusion of Hepatocellular Carcinoma for Predicting Response to Transarterial Radioembolization: Value of Tumor Heterogeneity Assessment. Cardiovasc Intervent Radiol 39, 400–408 (2016). https://doi.org/10.1007/s00270-015-1185-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00270-015-1185-1

Keywords

Navigation