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Prognostic value of baseline volumetric multiparametric MR imaging in neuroendocrine liver metastases treated with transarterial chemoembolization

  • Magnetic Resonance
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To determine whether baseline multiparametric MR imaging can predict overall survival (OS) and hepatic progression-free survival (HPFS) in patients with neuroendocrine liver metastases (NELMs) treated with transarterial chemoembolization (TACE).

Methods

This retrospective study included 84 NELMs patients treated with TACE. Tumor volume and volumetric measurements of arterial enhancement (AE), venous enhancement (VE), and apparent diffusion coefficient (ADC) were performed on baseline MR imaging. A maximum of one, two, and five index lesions were selected in each patient. OS was the primary endpoint and HPFS was the secondary endpoint. Prognostic values of volumetric multiparametric MR parameters for predicting OS and HPFS considering a maximum of one, two, and five index lesions were assessed.

Results

Prognostic values of volumetric multiparametric MR parameters for predicting OS and HPFS were similar regardless of the maximum number of index lesions. Multivariate survival analysis showed that baseline dominant tumor volume ≥ 73 cm3, volumetric mean AE ≥ 45%, and mean VE ≥ 73% were independent prognostic factors for OS (HR 2.73; 95% CI 1.45, 5.15; HR 0.32; 95% CI 0.17, 0.63; HR 0.35; 95% CI 0.17, 0.72, respectively) and HPFS (HR 2.30, 95% CI 1.38, 3.84; HR 0.46, 95% CI 0.25, 0.84; HR 0.36, 95% CI 0.19, 0.57, respectively). OS and HPFS were similar in patients with low and high volumetric mean ADC.

Conclusion

Volumetric enhancement values and tumor volume of the dominant lesion on baseline MR imaging may act as prognostic factors for OS and HPFS in NELMs patients treated with TACE.

Key Points

• High volumetric mean AE and VE, and low tumor volume of the dominant lesion on baseline MR imaging were associated with favorable OS and HPFS in NELMs patients treated with TACE.

• Evaluation of multiple lesions does not provide additional information as compared to single lesion evaluation.

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Abbreviations

ADC:

Apparent diffusion coefficient

AE:

Arterial enhancement

DWI:

Diffusion-weighted imaging

EASL:

European Association for the Study of the Liver

HPFS:

Hepatic progression-free survival

mRECIST:

Modified Response Evaluation Criteria in Solid Tumors

NELMs:

Neuroendocrine liver metastases

OS:

Overall survival

PFS:

Progression-free survival

TACE:

Transarterial chemoembolization

VE:

Venous enhancement

References

  1. Yao JC, Hassan M, Phan A et al (2008) One hundred years after “carcinoid”: epidemiology of and prognostic factors for neuroendocrine tumors in 35,825 cases in the United States. J Clin Oncol 26:3063–3072

    Article  PubMed  Google Scholar 

  2. Riihimaki M, Hemminki A, Sundquist K, Sundquist J, Hemminki K (2016) The epidemiology of metastases in neuroendocrine tumors. Int J Cancer 139:2679–2686

    Article  CAS  PubMed  Google Scholar 

  3. Vogl TJ, Naguib NN, Zangos S et al (2009) Liver metastases of neuroendocrine carcinomas: interventional treatment via transarterial embolization, chemoembolization and thermal ablation. Eur J Radiol 72:517–528

    Article  PubMed  Google Scholar 

  4. Pavel M, Baudin E, Couvelard A et al (2012) ENETS Consensus Guidelines for the management of patients with liver and other distant metastases from neuroendocrine neoplasms of foregut, midgut, hindgut, and unknown primary. Neuroendocrinology 95:157–176

    Article  CAS  PubMed  Google Scholar 

  5. Frilling A, Modlin IM, Kidd M et al (2014) Recommendations for management of patients with neuroendocrine liver metastases. Lancet Oncol 15:e8–e21

    Article  PubMed  Google Scholar 

  6. Kunz PL, Reidy-Lagunes D, Anthony LB et al (2013) Consensus guidelines for the management and treatment of neuroendocrine tumors. Pancreas 42:557–577

    Article  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  8. Kamel IR, Liapi E, Reyes DK et al (2009) Unresectable hepatocellular carcinoma: serial early vascular and cellular changes after transarterial chemoembolization as detected with MR imaging. Radiology 250:466–473

    Article  PubMed  Google Scholar 

  9. Liapi E, Geschwind JF, Vossen JA et al (2008) Functional MRI evaluation of tumor response in patients with neuroendocrine hepatic metastasis treated with transcatheter arterial chemoembolization. AJR Am J Roentgenol 190:67–73

    Article  PubMed  Google Scholar 

  10. Gillmore R, Stuart S, Kirkwood A et al (2011) EASL and mRECIST responses are independent prognostic factors for survival in hepatocellular cancer patients treated with transarterial embolization. J Hepatol 55:1309–1316

    Article  PubMed  Google Scholar 

  11. Kamel IR, Bluemke DA, Eng J et al (2006) The role of functional MR imaging in the assessment of tumor response after chemoembolization in patients with hepatocellular carcinoma. J Vasc Interv Radiol 17:505–512

    Article  PubMed  Google Scholar 

  12. Pandey A, Pandey P, Ghasabeh MA et al (2018) Baseline volumetric multiparametric MRI: can it be used to predict survival in patients with unresectable intrahepatic cholangiocarcinoma undergoing transcatheter arterial chemoembolization? Radiology 289:843–853

  13. Dong S, Ye XD, Yuan Z, Xu LC, Xiao XS (2012) Relationship of apparent diffusion coefficient to survival for patients with unresectable primary hepatocellular carcinoma after chemoembolization. Eur J Radiol 81:472–477

    Article  PubMed  Google Scholar 

  14. Yan DF, Zhang WB, Ke SB et al (2017) The prognostic value of pretreatment tumor apparent diffusion coefficient values in nasopharyngeal carcinoma. BMC Cancer 17:678

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Gladwish A, Milosevic M, Fyles A et al (2016) Association of apparent diffusion coefficient with disease recurrence in patients with locally advanced cervical cancer treated with radical chemotherapy and radiation therapy. Radiology 279:158–166

    Article  PubMed  Google Scholar 

  16. Pandey A, Pandey P, Ghasabeh MA et al (2018) Baseline volumetric multiparametric MRI: can it be used to predict survival in patients with unresectable intrahepatic cholangiocarcinoma undergoing transcatheter arterial chemoembolization? Radiology 180450

  17. Taniai N, Onda M, Tajiri T et al (2002) Good embolization response for colorectal liver metastases with hypervascularity. Hepatogastroenterology 49:1531–1534

    PubMed  Google Scholar 

  18. Sommer WH, Ceelen F, Garcia-Albeniz X et al (2013) Defining predictors for long progression-free survival after radioembolisation of hepatic metastases of neuroendocrine origin. Eur Radiol 23:3094–3103

    Article  PubMed  Google Scholar 

  19. Boas FE, Brody LA, Erinjeri JP et al (2016) Quantitative measurements of enhancement on preprocedure triphasic CT can predict response of colorectal liver metastases to radioembolization. AJR Am J Roentgenol 207:671–675

    Article  PubMed  PubMed Central  Google Scholar 

  20. Lambregts DM, Beets GL, Maas M et al (2011) Tumour ADC measurements in rectal cancer: effect of ROI methods on ADC values and interobserver variability. Eur Radiol 21:2567–2574

    Article  PubMed  PubMed Central  Google Scholar 

  21. Padhani AR, Liu G, Koh DM et al (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 11:102–125

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Blazic IM, Lilic GB, Gajic MM (2017) Quantitative assessment of rectal cancer response to neoadjuvant combined chemotherapy and radiation therapy: comparison of three methods of positioning region of interest for ADC measurements at diffusion-weighted MR imaging. Radiology 282:418–428

    Article  PubMed  Google Scholar 

  23. Bonekamp S, Halappa VG, Geschwind JF et al (2013) Unresectable hepatocellular carcinoma: MR imaging after intraarterial therapy. Part II. Response stratification using volumetric functional criteria after intraarterial therapy. Radiology 268:431–439

    Article  PubMed  Google Scholar 

  24. Gowdra HV, Corona-Villalobos CP, Bonekamp S et al (2013) Neuroendocrine liver metastasis treated by using intraarterial therapy: volumetric functional imaging biomarkers of early tumor response and survival. Radiology 266:502–513

    Article  Google Scholar 

  25. Li Z, Bonekamp S, Halappa VG et al (2012) Islet cell liver metastases: assessment of volumetric early response with functional MR imaging after transarterial chemoembolization. Radiology 264:97–109

    Article  PubMed  Google Scholar 

  26. de Baere T, Deschamps F, Tselikas L et al (2015) GEP-NETS update: interventional radiology: role in the treatment of liver metastases from GEP-NETs. Eur J Endocrinol 172:R151–R166

    Article  CAS  PubMed  Google Scholar 

  27. Gupta S (2013) Intra-arterial liver-directed therapies for neuroendocrine hepatic metastases. Semin Interv Radiol 30:28–38

    Article  Google Scholar 

  28. Kim BK, Kim SU, Kim MJ et al (2013) Number of target lesions for EASL and modified RECIST to predict survivals in hepatocellular carcinoma treated with chemoembolization. Clin Cancer Res 19:1503–1511

    Article  PubMed  Google Scholar 

  29. Newson R (2010) Comparing the predictive powers of survival models using Harrell’s C or Somers’ D. Stata J 10:339–358

    Article  Google Scholar 

  30. Kwan SW, Fidelman N, Ma E, Kerlan RJ, Yao FY (2012) Imaging predictors of the response to transarterial chemoembolization in patients with hepatocellular carcinoma: a radiological-pathological correlation. Liver Transpl 18:727–736

    Article  PubMed  PubMed Central  Google Scholar 

  31. Marrache F, Vullierme MP, Roy C et al (2007) Arterial phase enhancement and body mass index are predictors of response to chemoembolisation for liver metastases of endocrine tumours. Br J Cancer 96:49–55

    Article  CAS  PubMed  Google Scholar 

  32. Denecke T, Baur AD, Ihm C et al (2013) Evaluation of radiological prognostic factors of hepatic metastases in patients with non-functional pancreatic neuroendocrine tumors. Eur J Radiol 82:e550–e555

    Article  PubMed  Google Scholar 

  33. Pope WB, Lai A, Mehta R et al (2011) Apparent diffusion coefficient histogram analysis stratifies progression-free survival in newly diagnosed bevacizumab-treated glioblastoma. AJNR Am J Neuroradiol 32:882–889

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Pope WB, Kim HJ, Huo J et al (2009) Recurrent glioblastoma multiforme: ADC histogram analysis predicts response to bevacizumab treatment. Radiology 252:182–189

    Article  PubMed  Google Scholar 

  35. Mannelli L, Kim S, Hajdu CH, Babb JS, Taouli B (2013) Serial diffusion-weighted MRI in patients with hepatocellular carcinoma: prediction and assessment of response to transarterial chemoembolization. Preliminary experience. Eur J Radiol 82:577–582

    Article  PubMed  Google Scholar 

  36. Min JH, Kang TW, Kim YK et al (2018) Hepatic neuroendocrine tumour: apparent diffusion coefficient as a potential marker of prognosis associated with tumour grade and overall survival. Eur Radiol 28:2561–2571

    Article  PubMed  Google Scholar 

  37. Tam HH, Collins DJ, Brown G et al (2013) The role of pre-treatment diffusion-weighted MRI in predicting long-term outcome of colorectal liver metastasis. Br J Radiol 86:20130281

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Gupta S, Johnson MM, Murthy R et al (2005) Hepatic arterial embolization and chemoembolization for the treatment of patients with metastatic neuroendocrine tumors: variables affecting response rates and survival. Cancer Am Cancer Soc 104:1590–1602

    Google Scholar 

  39. Kress O, Wagner HJ, Wied M et al (2003) Transarterial chemoembolization of advanced liver metastases of neuroendocrine tumors--a retrospective single-center analysis. Digestion 68:94–101

    Article  CAS  PubMed  Google Scholar 

  40. Hur S, Chung JW, Kim HC et al (2013) Survival outcomes and prognostic factors of transcatheter arterial chemoembolization for hepatic neuroendocrine metastases. J Vasc Interv Radiol 24:947–956, 957

    Article  PubMed  Google Scholar 

  41. Zappa M, Hentic O, Vullierme MP et al (2017) Is visual radiological evaluation of liver tumour burden in patients with neuroendocrine tumours reproducible? Endocr Connect 6:33–38

    Article  PubMed  PubMed Central  Google Scholar 

  42. Sahu S, Schernthaner R, Ardon R et al (2017) Imaging biomarkers of tumor response in neuroendocrine liver metastases treated with transarterial chemoembolization: can enhancing tumor burden of the whole liver help predict patient survival? Radiology 283:883–894

    Article  PubMed  Google Scholar 

  43. Fleckenstein FN, Schernthaner RE, Duran R et al (2016) 3D quantitative tumour burden analysis in patients with hepatocellular carcinoma before TACE: comparing single-lesion vs. multi-lesion imaging biomarkers as predictors of patient survival. Eur Radiol 26:3243–3252

    Article  PubMed  PubMed Central  Google Scholar 

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Funding

The authors state that this work has not received any funding.

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Authors and Affiliations

  1. Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China

    Yan Luo, Zhen Li & Daoyu Hu

  2. Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Nelson 143, Central Radiology, MRI, 600 North Wolfe Street, Room 143, Baltimore, MD, 21287, USA

    Yan Luo, Ankur Pandey, Mounes Aliyari Ghasabeh, Pallavi Pandey, Farnaz Najmi Varzaneh, Manijeh Zarghampour, Pegah Khoshpouri, Sanaz Ameli & Ihab R. Kamel

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  1. Yan Luo
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  3. Mounes Aliyari Ghasabeh
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  9. Zhen Li
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  11. Ihab R. Kamel
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Corresponding author

Correspondence to Ihab R. Kamel.

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Guarantor

The scientific guarantor of this publication is Ihab R Kamel.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Study subjects or cohorts overlap

Some study subjects or cohorts have been previously reported in a previously published paper (Gowdra HV et al Neuroendocrine liver metastasis treated by using intra-arterial therapy: volumetric functional imaging biomarkers of early tumor response and survival. Radiology 2013; 266:502–513). We have reported on 55 out of 84 patients included in the current study. However, the prior report focused on the prognostic value of pre- and post-TACE changes in volumetric multiparametric MR imaging of the dominant lesion for predicting overall survival. The current study included a larger sample size and evaluated whether baseline volumetric MR imaging only can predict overall survival and hepatic progression-free survival. Also, the prognostic values of baseline volumetric MR metrics using three different numbers of index lesions (one, two, and five) were compared in the current study.

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

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Luo, Y., Pandey, A., Ghasabeh, M.A. et al. Prognostic value of baseline volumetric multiparametric MR imaging in neuroendocrine liver metastases treated with transarterial chemoembolization. Eur Radiol 29, 5160–5171 (2019). https://doi.org/10.1007/s00330-019-06100-3

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  • DOI: https://doi.org/10.1007/s00330-019-06100-3

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