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Prognostic value of preoperative intratumoral FDG uptake heterogeneity in patients with epithelial ovarian cancer

  • Oncology
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Abstract

Objectives

To investigate the prognostic value of intratumoral FDG uptake heterogeneity (IFH) derived from PET/CT in patients with epithelial ovarian cancer (EOC).

Methods

We retrospectively reviewed patients with pathologically proven epithelial ovarian cancer who underwent preoperative 18F-FDG PET/CT scans. PET/CT parameters such as maximum and average standardized uptake values (SUVmax and SUVavg), sum of all metabolic tumour volume (MTV), cumulative total lesion glycolysis (TLG) and IFH were assessed. Regression analyses were used to identify clinicopathological and imaging variables associated with disease-free survival (DFS).

Results

Clinicopathological data were reviewed for 61 eligible patients. The median duration of DFS was 13 months (range, 6–26 months), and 18 (29.5 %) patients experienced recurrence. High IFH values were associated with tumour recurrence (P = 0.005, hazard ratio 4.504, 95 % CI 1.572–12.902). The Kaplan-Meier survival graphs showed that DFS significantly differed in groups categorized based on IFH (P = 0.002, log-rank test). Moreover, there were significant differences in DFS (P = 0.009) and IFH (P = 0.040) between patients with and without recurrence.

Conclusions

Preoperative IFH measured by 18F-FDG PET/CT was significantly associated with EOC recurrence. FDG-based heterogeneity could be a useful and potential predicator of EOC recurrence before treatment.

Key Points

• Preoperative IFH was significantly associated with recurrence of EOC

• Disease-free survival significantly differed in groups categorized by IFH

• FDG-based heterogeneity could be a potential predicator of EOC recurrence before treatment

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Abbreviations

18F-FDG:

18F-fluorodeoxyglucose

CT:

Computed tomography

DFS:

Disease-free survival

EOC:

Epithelial ovarian cancer

FIGO:

International Federation of Gynaecology and Obstetrics

IFH:

Intratumoral FDG uptake heterogeneity

MTV:

Metabolic tumour volume

TLG:

Total lesion glycolysis

PET:

Positron emission tomography

SD:

Standard deviation

SUV:

Standardized uptake value

References

  1. Jemal A, Siegel R, Ward E, Hao Y, Xu J, Thun MJ (2009) Cancer statistics, 2009. CA Cancer J Clin 59:225–249

    Article  PubMed  Google Scholar 

  2. Angioli R, Capriglione S, Aloisi A et al (2014) Can HE4 predict platinum response during first-line chemotherapy in ovarian cancer? Tumour Biol 35:7009–7015

    Article  CAS  PubMed  Google Scholar 

  3. Harter P, Muallem ZM, Buhrmann C et al (2011) Impact of a structured quality management program on surgical outcome in primary advanced ovarian cancer. Gynecol Oncol 121:615–619

    Article  PubMed  Google Scholar 

  4. Chang SJ, Bristow RE (2012) Evolution of surgical treatment paradigms for advanced-stage ovarian cancer: redefining 'optimal' residual disease. Gynecol Oncol 125:483–492

    Article  PubMed  Google Scholar 

  5. Braicu EI, Fotopoulou C, Van Gorp T et al (2013) Preoperative HE4 expression in plasma predicts surgical outcome in primary ovarian cancer patients: results from the OVCAD study. Gynecol Oncol 128:245–251

    Article  CAS  PubMed  Google Scholar 

  6. Chi DS, Bristow RE, Armstrong DK, Karlan BY (2011) Is the easier way ever the better way? J Clin Oncol 29:4073–4075

    Article  CAS  PubMed  Google Scholar 

  7. Pak K, Cheon GJ, Nam HY et al (2014) Prognostic value of metabolic tumor volume and total lesion glycolysis in head and neck cancer: a systematic review and meta-analysis. J Nucl Med 55:884–890

    Article  CAS  PubMed  Google Scholar 

  8. Tixier F, Le Rest CC, Hatt M et al (2011) Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer. J Nucl Med 52:369–378

    Article  PubMed  PubMed Central  Google Scholar 

  9. El Naqa I, Grigsby P, Apte A et al (2009) Exploring feature-based approaches in PET images for predicting cancer treatment outcomes. Pattern Recogn 42:1162–1171

    Article  Google Scholar 

  10. Cook GJ, Yip C, Siddique M et al (2013) Are pretreatment 18F-FDG PET tumor textural features in non-small cell lung cancer associated with response and survival after chemoradiotherapy? J Nucl Med 54:19–26

    Article  PubMed  Google Scholar 

  11. Kidd EA, Grigsby PW (2008) Intratumoral metabolic heterogeneity of cervical cancer. Clin Cancer Res 14:5236–5241

    Article  CAS  PubMed  Google Scholar 

  12. Basu S, Kwee TC, Gatenby R, Saboury B, Torigian DA, Alavi A (2011) Evolving role of molecular imaging with PET in detecting and characterizing heterogeneity of cancer tissue at the primary and metastatic sites, a plausible explanation for failed attempts to cure malignant disorders. Eur J Nucl Med Mol Imaging 38:987–991

    Article  PubMed  Google Scholar 

  13. Pugachev A, Ruan S, Carlin S et al (2005) Dependence of FDG uptake on tumor microenvironment. Int J Radiat Oncol Biol Phys 62:545–553

    Article  CAS  PubMed  Google Scholar 

  14. Francis RJ, Byrne MJ, van der Schaaf AA et al (2007) Early prediction of response to chemotherapy and survival in malignant pleural mesothelioma using a novel semiautomated 3-dimensional volume-based analysis of serial 18F-FDG PET scans. J Nucl Med 48:1449–1458

    Article  PubMed  Google Scholar 

  15. Veit-Haibach P, Schaefer NG, Steinert HC, Soyka JD, Seifert B, Stahel RA (2010) Combined FDG-PET/CT in response evaluation of malignant pleural mesothelioma. Lung Cancer 67:311–317

  16. Bundschuh RA, Dinges J, Neumann L et al (2014) Textural parameters of tumor heterogeneity in 18F-FDG PET/CT for therapy response assessment and prognosis in patients with locally advanced rectal cancer. J Nucl Med 55:891–897

    Article  CAS  PubMed  Google Scholar 

  17. Metz CE (1978) Basic principles of ROC analysis. Semin Nuc Med 8:283–298

    Article  CAS  Google Scholar 

  18. Hanley JA, McNeil BJ (1982) The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143:29–36

    Article  CAS  PubMed  Google Scholar 

  19. Harries M, Gore M (2002) Part I: chemotherapy for epithelial ovarian cancer-treatment at first diagnosis. Lancet Oncol 3:529–536

    Article  CAS  PubMed  Google Scholar 

  20. Sorensen M, Horsman MR, Cumming P, Munk OL, Keiding S (2005) Effect of intratumoral heterogeneity in oxygenation status on FMISO PET, autoradiography, and electrode Po2 measurements in murine tumors. Int J Radiat Oncol Biol Phys 62:854–861

    Article  PubMed  Google Scholar 

  21. Avril N, Menzel M, Dose J et al (2001) Glucose metabolism of breast cancer assessed by 18F-FDG PET: histologic and immunohistochemical tissue analysis. J Nucl Med 42:9–16

    CAS  PubMed  Google Scholar 

  22. Zasadny KR, Tatsumi M, Wahl RL (2003) FDG metabolism and uptake versus blood flow in women with untreated primary breast cancers. Eur J Nucl Med Mol Imaging 30:274–280

    Article  CAS  PubMed  Google Scholar 

  23. Tateishi U, Nishihara H, Tsukamoto E, Morikawa T, Tamaki N, Miyasaka K (2002) Lung tumors evaluated with FDG-PET and dynamic CT: the relationship between vascular density and glucose metabolism. J Comput Assist Tomogr 26:185–190

    Article  PubMed  Google Scholar 

  24. Zhao S, Kuge Y, Mochizuki T et al (2005) Biologic correlates of intratumoral heterogeneity in 18F-FDG distribution with regional expression of glucose transporters and hexokinase-II in experimental tumor. J Nucl Med 46:675–682

    CAS  PubMed  Google Scholar 

  25. van Baardwijk A, Bosmans G, van Suylen RJ et al (2008) Correlation of intra-tumour heterogeneity on 18F-FDG PET with pathologic features in non-small cell lung cancer: a feasibility study. Radiother Oncol 87:55–58

    Article  PubMed  Google Scholar 

  26. Arriagada R, Le Chevalier T, Quoix E et al (1991) ASTRO (American Society for Therapeutic Radiology and Oncology) plenary: effect of chemotherapy on locally advanced non-small cell lung carcinoma: a randomized study of 353 patients. GETCB (Groupe d'Etude et Traitement des Cancers Bronchiques), FNCLCC (Federation Nationale des Centres de Lutte contre le Cancer) and the CEBI trialists. Int J Radiat Oncol Biol Phys 20:1183–1190

    Article  CAS  PubMed  Google Scholar 

  27. Le Chevalier T, Brisgand D, Douillard JY et al (1994) Randomized study of vinorelbine and cisplatin versus vindesine and cisplatin versus vinorelbine alone in advanced non-small-cell lung cancer: results of a European multicenter trial including 612 patients. J Clin Oncol 12:360–367

    PubMed  Google Scholar 

  28. Bradley J, Thorstad WL, Mutic S et al (2004) Impact of FDG-PET on radiation therapy volume delineation in non-small-cell lung cancer. Int J Radiat Oncol Biol Phys 59:78–86

    Article  PubMed  Google Scholar 

  29. Paulino AC, Johnstone PA (2004) FDG-PET in radiotherapy treatment planning: Pandora's box? Int J Radiat Oncol Biol Phys 59:4–5

    Article  PubMed  Google Scholar 

  30. Yang Z, Sun Y, Zhang Y et al (2013) Can fluorine-18 fluoroestradiol positron emission tomography-computed tomography demonstrate the heterogeneity of breast cancer in vivo? Clin Breast Cancer 13:359–363

    Article  CAS  PubMed  Google Scholar 

  31. Tateishi U, Terauchi T, Akashi-Tanaka S et al (2012) Comparative study of the value of dual tracer PET/CT in evaluating breast cancer. Cancer Sci 103:1701–1707

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

The scientific guarantor of this publication is Gi Jeong Cheon. 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. This work was supported by the Research Resettlement Fund for new faculty of Seoul National University, and by grant no. 3420130200 (2013-0362) from the SK Telecom Research Fund and grant no. 0320140270 (2014-1040) from the Seoul National University Hospital Research Fund. No complex statistical methods were necessary for this paper. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. Methodology: retrospective, diagnostic or prognostic study, performed at one institution.

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Correspondence to Hyun Hoon Chung.

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Lee, M., Lee, H., Cheon, G.J. et al. Prognostic value of preoperative intratumoral FDG uptake heterogeneity in patients with epithelial ovarian cancer. Eur Radiol 27, 16–23 (2017). https://doi.org/10.1007/s00330-016-4368-5

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  • DOI: https://doi.org/10.1007/s00330-016-4368-5

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