Skip to main content
SpringerLink
Log in

Assessment of Therapy Response to Transarterial Radioembolization for Liver Metastases by Means of Post-treatment MRI-Based Texture Analysis

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

Abstract

Introduction

To determine whether post-treatment magnetic resonance imaging (MRI)-based texture analysis of liver metastases (LM) may be suited predicting therapy response to transarterial radioembolization (TARE) during follow-up.

Materials and Methods

Thirty-seven patients with LM treated by TARE (mean age 63.4 years) between January 2006 and December 2014 were identified in this retrospective feasibility study. They underwent dynamic contrast-enhanced and hepatocellular phase MRI after TARE (mean 2.2 days). Response was evaluated on follow-up imaging scheduled in intervals of 3 months (median follow-up, 7.3 months) based on response evaluation criteria in solid tumors 1.1 (RECIST 1.1). Results of texture analysis [mean, standard deviation, skewness (s), kurtosis (k), entropy and uniformity] were compared between patients with progressive disease (PD) and patients with stable disease (SD), partial or complete response (PR/CR). Receiver operating characteristics including the area under the curve (AUC) and cutoff values including the sensitivity and specificity were calculated.

Results

According to RECIST 1.1, 24 patients (64.9%) had PD, 8 SD (21.6%) and 5 PR (13.5%). MRI-based texture analysis showed an earlier differentiation between patients with and without PD when compared with RECIST 1.1. Median k (2.88 vs. 2.35) in arterial phase MRI and median s (0.48 vs. 0.25) and k (2.85 vs. 2.25) in venous phase MRI were significantly different (p < 0.05). The AUC for k derived from arterial phase MRI was 0.73 (cutoff = 2.55, sensitivity = 0.83, specificity = 0.62) (p < 0.05). The AUC for s and k in venous phase MRI was 0.76 (cutoff = 0.35, sensitivity = 0.71, specificity = 0.85) (p > 0.05) and 0.83 (cutoff = 2.50, sensitivity = 0.75, specificity = 0.85) (p < 0.05).

Conclusion

This study indicates the potential of MRI-based texture analysis at arterial and venous phase MRI for the early prediction of PD after TARE.

Level of Evidence

IV.

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
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Kasper HU, Drebber U, Dries V, Dienes HP. Liver metastases: incidence and histogenesis. Z Gastroenterol. 2005;43:1149–57.

    Article  PubMed  Google Scholar 

  2. Nachtnebel A, Sotti G, Vitale A, Perrini MR. Selective internal radiotherapy using yttrium-90 microspheres for primary and secondary liver malignancies. Vienna: Ludwig Boltzmann Institute for Health Technology Assessment (LBI-HTA). 2011. http://eprints.hta.lbg.ac.at/922/1/DSD_47_english.pdf. Accessed 08 May 2015.

  3. Clark ME, Smith RR. Liver-directed therapies in metastatic colorectal cancer. J Gastrointest Oncol. 2014;5:374–87.

    PubMed  PubMed Central  Google Scholar 

  4. Mahnken AH. Current status of transarterial radioembolization. World J Radiol. 2016;8:449–59.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Salem R, Lewandowski RJ, Kulik L, et al. Radioembolization results in longer time-to-progression and reduced toxicity compared with chemoembolization in patients with hepatocellular carcinoma. Gastroenterology. 2011;140(2):497–507.

    Article  PubMed  Google Scholar 

  6. Sangro B, Carpanese L, Cianni R, et al. Survival after yttrium-90 resin microsphere radioembolization of hepatocellular carcinoma across Barcelona clinic liver cancer stages: a European evaluation. Hepatology. 2011;54:868–78.

    Article  PubMed  Google Scholar 

  7. Bester L, Meteling B, Pocock N, et al. Radioembolization versus standard care of hepatic metastases: comparative retrospective cohort study of survival outcomes and adverse events in salvage patients. J Vasc Interv Radiol. 2012;23:96–105.

    Article  PubMed  Google Scholar 

  8. Jakobs TF, Hoffmann RT, Dehm K, et al. Hepatic yttrium-90 radioembolization of chemotherapy-refractory colorectal cancer liver metastases. J Vasc Interv Radiol. 2008;19:1187–95.

    Article  PubMed  Google Scholar 

  9. Memon K, Lewandowski RJ, Mulcahy MF, et al. Radioembolization for neuroendocrine liver metastases: safety, imaging, and long-term outcomes. Int J Radiat Oncol Biol Phys. 2012;83:887–94.

    Article  PubMed  Google Scholar 

  10. Saxena A, Chua TC, Bester L, Kokandi A, Morris DL. Factors predicting response and survival after yttrium-90 radioembolization of unresectable neuroendocrine tumor liver metastases: a critical appraisal of 48 cases. Ann Surg. 2010;251:910–6.

    Article  PubMed  Google Scholar 

  11. Gonzalez-Guindalini FD, Botelho MP, Harmath CB, et al. Assessment of liver tumor response to therapy: role of quantitative imaging. Radiographics. 2013;33:1781–800.

    Article  PubMed  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

  14. Singh P, Anil G. Yttrium-90 radioembolization of liver tumors: what do the images tell us? Cancer Imaging. 2013;13:645–57.

    Article  Google Scholar 

  15. Davnall F, Yip CSP, Ljungvist G, et al. Assessment of tumor heterogeneity: an emerging imaging tool for clinical practice? Insights Imaging. 2012;3:573–89.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Gillies RJ, Kinahan PE, Hricak H. Radiomics: images Are More than Pictures, they are data. Radiology. 2016;278:563–77.

    Article  PubMed  Google Scholar 

  17. Alic L, Niessen WJ, Veenland JF. Quantification of heterogeneity as a biomarker in tumor imaging: a systematic review. PLoS ONE. 2014;9:e110300.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Just N. Improving tumour heterogeneity MRI assessment with histograms. Br J Cancer. 2014;111(12):2205–13.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Ganeshan B, Miles KA. Quantifying tumour heterogeneity with CT. Cancer Imaging. 2013;13:140–9.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Reiner CS, 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 Interv Radiol. 2016;39:400–8.

    Article  Google Scholar 

  21. Morsbach F, Pfammatter T, Reiner CS, 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 

  22. Morsbach F, Sah BR, Spring L, 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 

  23. Reiner CS, Morsbach F, Sah BR, 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 

  24. Garin E, Lenoir L, Rolland Y, 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  PubMed  CAS  Google Scholar 

  25. Zhu X, Sobhani F, Xu C, Pan L, Ghasebeh MA, Kamel IR. Quantitative volumetric functional MR imaging: an imaging biomarker of early treatment response in hypo-vascular liver metastasis patients after yttrium-90 transarterial radioembolization. Abdom Radiol (NY). 2016;41:1495–504.

    Article  Google Scholar 

  26. Schmeel FC, Simon B, Luetkens JA, et al. Prognostic value of pretreatment diffusion-weighted magnetic resonance imaging for outcome prediction of colorectal cancer liver metastases undergoing 90Y-microsphere radioembolization. J Cancer Res Clin Oncol. 2017;143:1531–41.

    Article  PubMed  CAS  Google Scholar 

  27. Kokabi N, Camacho JC, Xing M, et al. Apparent diffusion coefficient quantification as an early imaging biomarker of response and predictor of survival following yttrium-90 radioembolization for unresectable infiltrative hepatocellular carcinoma with portal vein thrombosis. Abdom Imaging. 2014;39:969–78.

    Article  PubMed  Google Scholar 

  28. Seale MK, Catalano OA, Saini S, Hahn PF, Sahani DV. Hepatobiliary-specific MR contrast agents: role in imaging the liver and biliary tree. Radiographics. 2009;29:1725–48.

    Article  PubMed  Google Scholar 

  29. Salem R, Thurston KG. Radioembolization with 90Yttrium microspheres: a state-of-the-art brachytherapy treatment for primary and secondary liver malignancies. Part 1: technical and methodologic considerations. J Vasc Interv Radiol. 2006;17:1251–78.

    Article  PubMed  Google Scholar 

  30. Mahnken AH, Spreafico C, Maleux G, Helmberger T, Jakobs TF. Standards of practice in transarterial radioembolization. Cardiovasc Interv Radiol. 2013;36:613–22.

    Article  Google Scholar 

  31. Lewandowski RJ, Sato KT, Atassi B, et al. Radioembolization with 90Y microspheres: angiographic and technical considerations. Cardiovasc Interv Radiol. 2007;30:571–92.

    Article  Google Scholar 

  32. Padia SA, Lewandowski RJ, Johnson GE, et al. Radioembolization of hepatic malignancies: background, quality improvement guidelines, and future directions. J Vasc Interv Radiol. 2017;28:1–15.

    Article  PubMed  Google Scholar 

  33. Mann HB, Whitney DR. On a test of whether one of 2 random variables is stochastically larger than the other. Annals Math Stat. 1947;18:50–60.

    Article  Google Scholar 

  34. Bewick V, Cheek L, Ball J. Statistics review 13: receiver operating characteristic curves. Crit Care. 2004;8:508–12.

    Article  PubMed  PubMed Central  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  36. 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  PubMed  CAS  Google Scholar 

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

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Ganeshan B, Panayiotou E, Burnand K, Dizdarevic S, Miles K. Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival. Eur Radiol. 2012;22:796–802.

    Article  PubMed  Google Scholar 

  39. De Cecco CN, Ganeshan B, Ciolina M, et al. Texture analysis as imaging biomarker of tumoral response to neoadjuvant chemoradiotherapy in rectal Cancer patients studied with 3-T magnetic resonance. Invest Radiol. 2015;50(4):239–45.

    Article  PubMed  CAS  Google Scholar 

  40. Chen BB, Shih TT. DCE-MRI in hepatocellular carcinoma-clinical and therapeutic image biomarker. World J Gastroenterol. 2014;20:3125–34.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Chandarana H, Rosenkrantz AB, Mussi TC, et al. Histogram analysis of whole-lesion enhancement in differentiating clear cell from papillary subtype of renal cell cancer. Radiology. 2012;265:790–8.

    Article  PubMed  Google Scholar 

  42. Downey K, Riches SF, Morgan VA, et al. Relationship between imaging biomarkers of stage I cervical cancer and poor-prognosis histologic features: quantitative histogram analysis of diffusion-weighted MR images. AJR Am J Roentgenol. 2013;200:314–20.

    Article  PubMed  Google Scholar 

  43. O’Connor JP, Rose CJ, Waterton JC, Carano RA, Parker GJ, Jackson A. Imaging intratumor heterogeneity: role in therapy response, resistance, and clinical outcome. Clin Cancer Res. 2015;21:249–57.

    Article  PubMed  CAS  Google Scholar 

  44. Chapiro J, Duran R, Lin M, et al. Early survival prediction after intra-arterial therapies: a 3D quantitative MRI assessment of tumour response after TACE or radioembolization of colorectal cancer metastases to the liver. Eur Radiol. 2015;25:1993–2003.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Tacher V, Lin M, Duran R, et al. Comparison of existing response Criteria in patients with hepatocellular carcinoma treated with transarterial chemoembolization Using a 3D quantitative approach. Radiology. 2016;278:275–84.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank Prof. Dr. Nina Timmesfeld (Philipps-University, Marburg, Germany) for statistical advice, Dr. Matthias Baumhauer (Mint Medical GmbH, Dossenheim, Germany) for technical support and Dr. Andrew McIntyre (Städtisches Klinikum Karlsruhe, Germany) for language editing. Our special thanks go to the liver tumor board at Klinikum Karlsruhe and the interventional section of the Institute of Diagnostic and Interventional Radiology.

Author information

Authors and Affiliations

  1. Department of Radiology, University of Cologne, Kerpener Straße 62, 50937, Cologne, Germany

    Robert P. Reimer

  2. Department of Diagnostic and Interventional Radiology, Marburg University Hospital, Philipps-University, Baldingerstrasse, 35043, Marburg, Germany

    Robert P. Reimer & Andreas H. Mahnken

  3. Institute of Diagnostic and Interventional Radiology, Klinikum Karlsruhe, Academic Teaching Hospital of the University of Freiburg, 76133, Karlsruhe, Germany

    Peter Reimer

Authors
  1. Robert P. Reimer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Peter Reimer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andreas H. Mahnken
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Robert P. Reimer.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

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.

Informed Consent

The requirement to obtain an additional informed consent was waived by the ethics committee of Philipps-University, Marburg, Germany.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Reimer, R.P., Reimer, P. & Mahnken, A.H. Assessment of Therapy Response to Transarterial Radioembolization for Liver Metastases by Means of Post-treatment MRI-Based Texture Analysis. Cardiovasc Intervent Radiol 41, 1545–1556 (2018). https://doi.org/10.1007/s00270-018-2004-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00270-018-2004-2

Keywords

Search

Navigation