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18F-FDG-PET/CT based total metabolic tumor volume change during neoadjuvant chemotherapy predicts outcome in advanced epithelial ovarian cancer

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European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Objective

To evaluate the predictive potential of total metabolic tumor volume (MTV) reduction during neoadjuvant chemotherapy (NACT) with 18F–FDG-PET/CT in an advanced FIGO stage III/IV epithelial ovarian cancer (EOC) patient cohort.

Methods

Twenty-nine primarily inoperable EOC patients underwent 18F–FDG-PET/CT before and after NACT. The pre- and post-NACT total MTV, in addition to the percentage MTV reduction during NACT, were compared with primary therapy outcome and progression-free survival (PFS). ROC-analysis determined an optimal threshold for MTV reduction identifying patients with progressive or stable disease (PD/SD) at the end of primary therapy. A multivariate analysis with residual tumor (0/>0), FIGO stage (III/IV) and MTV reduction compared to PFS was performed. The association between MTV reduction and overall survival (OS) was evaluated.

Results

The median pre- and post-NACT total MTV were 352 cm3 (range 150 to 1322 cm3) and 51 cm3 (range 0 to 417 cm3), respectively. The median MTV reduction during NACT was 89% (range 24% to 100%). Post-NACT MTV and MTV reduction associated with primary therapy outcome (MTV post-NACT p = 0.007, MTV reduction p = 0.001) and PFS (MTV post-NACT p = 0.005, MTV reduction p = 0.005). MTV reduction <85% identified the PD/SD patients (sensitivity 70%, specificity 78%, AUC 0.79). In a multivariate analysis, MTV reduction (p = 0.002) and FIGO stage (p = 0.003) were statistically significant variables associated with PFS. MTV reduction during NACT corresponded to OS (p = 0.05).

Conclusion

18F–FDG-PET/CT is helpful in NACT response evaluation. Patients with total MTV reduction <85% during NACT might be candidates for second-line chemotherapy and clinical trials, instead of interval debulking surgery.

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References

  1. Benedet JL, Bender H, Jones HI, Ngan HY, Pecorelli S. FIGO staging classifications and clinical practice guidelines in the management of gynecologic cancers. Int J Gynecol Obstet. 2000;70:209–62.

    Article  CAS  Google Scholar 

  2. Vergote I, Tropé CG, Amant F, Kristensen GB, Ehlen T, Johnson N, et al. Neoadjuvant chemotherapy or primary surgery in stage IIIC or IV ovarian cancer. N Engl J Med. 2010;363:943–53.

    Article  PubMed  CAS  Google Scholar 

  3. du Bois A, Reuss A, Pujade-Lauraine E, Harter P, Ray-Coquard I, Pfisterer J. Role of surgical outcome as prognostic factor in advanced epithelial ovarian cancer: a combined exploratory analysis of 3 prospectively randomized phase 3 multicenter trials: by the Arbeitsgemeinschaft Gynaekologische Onkologie Studiengruppe Ovarialkarzin. Cancer. 2009;115:1234–44.

    Article  PubMed  CAS  Google Scholar 

  4. Ledermann JA, Raja FA, Fotopoulou C, Colombo N, Sessa C. Clinical practice guidelines newly diagnosed and relapsed epithelial ovarian carcinoma: ESMO clinical practice guidelines clinical practice guidelines. Ann Oncol. 2013;24:24–32.

    Article  Google Scholar 

  5. Wright AA, Bohlke K, Armstrong DK, Bookman MA, Cliby WA, Coleman RL, et al. Neoadjuvant chemotherapy for newly diagnosed, advanced ovarian Cancer: Society of Gynecologic Oncology and American Society of clinical oncology clinical practice guideline. J Clin Oncol. 2016;143:3–15.

    Google Scholar 

  6. Petrillo M, Vizzielli G, Fanfani F, Gallotta V, Cosentino F, Chiantera V, et al. Definition of a dynamic laparoscopic model for the prediction of incomplete cytoreduction in advanced epithelial ovarian cancer: proof of a concept. Gynecol Oncol. 2015;139:5–9.

    Article  PubMed  CAS  Google Scholar 

  7. Vergote I, Amant F, Leunen K, du Bois A, Heitz F, Harter P. Neoadjuvant chemotherapy in advanced ovarian cancer: on what do we agree and disagree ? Gynecol Oncol. 2013;128:6–11.

    Article  PubMed  Google Scholar 

  8. Axtell AE, Lee MH, Bristow RE, Dowdy SC, Cliby WA, Raman S, et al. Multi-institutional reciprocal validation study of computed tomography predictors of suboptimal primary cytoreduction in patients with advanced ovarian cancer. J Clin Oncol. 2007;25:384–9.

    Article  PubMed  Google Scholar 

  9. Menczer J, Usviatzov I, Ben-Shem E, Golan A, Levy T. Neoadjuvant chemotherapy in ovarian, primary peritoneal and tubal carcinoma: can imaging results prior to interval debulking predict survival? J Gynecol Oncol. 2011;22:183–7.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Juweid ME, Cheson BD. Positron-emission tomography and assessment of cancer therapy. N Engl J Med. 2006;354:496–507.

    Article  PubMed  CAS  Google Scholar 

  11. Vallius T, Peter A, Auranen A, Carpén O, Kemppainen J, Matomäki J, et al. (18)F-FDG-PET/CT can identify histopathological non-responders to platinum-based neoadjuvant chemotherapy in advanced epithelial ovarian cancer. Gynecol Oncol. 2016;140:29–35.

    Article  PubMed  Google Scholar 

  12. McPherson A, Roth A, Laks E, Masud T, Bashashati A, Zhang AW, et al. Divergent modes of clonal spread and intraperitoneal mixing in high-grade serous ovarian cancer. Nat Genet. 2016;48:758–67.

    Article  PubMed  CAS  Google Scholar 

  13. Lee JW, Cho A, Lee J-H, Yun M, Lee JD, Kim YT, et al. The role of metabolic tumor volume and total lesion glycolysis on 18F-FDG PET/CT in the prognosis of epithelial ovarian cancer. Eur J Nucl Med Mol Imaging. 2014;41:1898–906.

    Article  PubMed  Google Scholar 

  14. Chung HH, Kwon HW, Kang KW, Park N-H, Song Y-S, Chung J-K, et al. Prognostic value of preoperative metabolic tumor volume and total lesion glycolysis in patients with epithelial ovarian cancer. Ann Surg Oncol. 2012;19:1966–72.

    Article  PubMed  Google Scholar 

  15. Vallius T, Hynninen J, Auranen A, Carpén O, Matomäki J, Oksa S, et al. Serum HE4 and CA125 as predictors of response and outcome during neoadjuvant chemotherapy of advanced high-grade serous ovarian cancer. Tumour Biol. 2014;35:12389–95.

    Article  PubMed  CAS  Google Scholar 

  16. Fagotti A, Ferrandina G, Fanfani F, Garganese G, Vizzielli G, Carone V, et al. Prospective validation of a laparoscopic predictive model for optimal cytoreduction in advanced ovarian carcinoma. Am J Obstet Gynecol. 2008;199:642.e1–6.

    Article  Google Scholar 

  17. 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  PubMed  CAS  Google Scholar 

  18. Rustin GJS, Vergote I, Eisenhauer EA, Pujade-Lauraine E, Quinn M, Thigpen T, et al. Definitions for response and progression in ovarian cancer clinical trials incorporating RECIST 1.1 and CA 125 agreed by the gynecological cancer intergroup (GCIG). Int J Gynecol Cancer. 2011;21:419–23.

    Article  PubMed  Google Scholar 

  19. Wahl RL, Jacene H, Kasamon Y, Lodge MA. From RECIST to PERCIST: evolving considerations for PET response criteria in solid tumors. J Nucl Med. 2009;50(Suppl 1):122S–50S.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3–900051–07-0, http://www.R-project.org/.

  21. Jacquet P, Jelinek JS, Steves MA, Sugarbaker PH. Evaluation of computed tomography in patients with peritoneal carcinomatosis. Cancer. 1993;72:1631–6.

    Article  PubMed  CAS  Google Scholar 

  22. Shankar LK, Van Den Abbeele A, Yap J, Benjamin R, Scheutze S, FitzGerald TJ. Considerations for the use of imaging tools for phase II treatment trials in oncology. Clin Cancer Res. 2009;15:1891–7.

    Article  PubMed  CAS  Google Scholar 

  23. Muraji M, Sudo T, Iwasaki S, Ueno S, Wakahashi S, Yamaguchi S, et al. Histopathology predicts clinical outcome in advanced epithelial ovarian cancer patients treated with neoadjuvant chemotherapy and debulking surgery. Gynecol Oncol. 2013;131:531–4.

    Article  PubMed  Google Scholar 

  24. Kitajima K, Murakami K, Yamasaki E, Kaji Y, Fukasawa I, Inaba N, et al. Diagnostic accuracy of integrated FDG-PET/contrast-enhanced CT in staging ovarian cancer: comparison with enhanced CT. Eur J Nucl Med Mol Imaging. 2008;35:1912–20.

    Article  PubMed  Google Scholar 

  25. Shim S-H, Lee SJ, Kim S-O, Kim S-N, Kim D-Y, Lee JJ, et al. Nomogram for predicting incomplete cytoreduction in advanced ovarian cancer patients. Gynecol Oncol. 2015;136:30–6.

    Article  PubMed  Google Scholar 

  26. Hynninen J, Auranen A, Carpén O, Dean K, Seppänen M, Kemppainen J, et al. FDG PET/CT in staging of advanced epithelial ovarian cancer: frequency of supradiaphragmatic lymph node metastasis challenges the traditional pattern of disease spread. Gynecol Oncol. 2012;126:64–8.

    Article  PubMed  Google Scholar 

  27. Nam EJ, Yun MJ, Oh YT, Kim JW, Kim JH, Kim S, et al. Diagnosis and staging of primary ovarian cancer: correlation between PET/CT, Doppler US, and CT or MRI. Gynecol Oncol. 2010;116:389–94.

    Article  PubMed  Google Scholar 

  28. Weber WA, Ziegler SI, Thödtmann R, Hanauske AR, Schwaiger M. Reproducibility of metabolic measurements in malignant tumors using FDG PET. J Nucl Med. 1999;40:1771–7.

    PubMed  CAS  Google Scholar 

  29. Rockall AG, Avril N, Lam R, Iannone R, Mozley PD, Parkinson C, et al. Repeatability of quantitative FDG-PET/CT and contrast-enhanced CT in recurrent ovarian carcinoma: test-retest measurements for tumor FDG uptake, diameter, and volume. Clin Cancer Res. 2014;20:2751–60.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. Schmidt S, Meuli RA, Achtari C, Prior JO. Peritoneal carcinomatosis in primary ovarian cancer staging: comparison between MDCT, MRI, and 18F-FDG PET/CT. Clin Nucl Med. 2015;40:371–7.

    Article  PubMed  Google Scholar 

  31. Senft A, De Bree R, Golding RP, Comans EFI, Van Waesberghe JHTM, Kuik JD, et al. Interobserver variability in chest CT and whole body FDG-PET screening for distant metastases in head and neck cancer patients. Mol Imaging Biol. 2011;13:385–90.

    Article  PubMed  Google Scholar 

  32. Jacene HA, Leboulleux S, Baba S, Chatzifotiadis D, Goudarzi B, Teytelbaum O, et al. Assessment of interobserver reproducibility in quantitative 18F-FDG PET and CT measurements of tumor response to therapy. J Nucl Med. 2009;50:1760–9.

    Article  PubMed  Google Scholar 

  33. Avril N, Sassen S, Schmalfeldt B, Naehrig J, Rutke S, Weber WA, et al. Prediction of response to neoadjuvant chemotherapy by sequential F-18-fluorodeoxyglucose positron emission tomography in patients with advanced-stage ovarian cancer. J Clin Oncol. 2005;23:7445–53.

    Article  PubMed  Google Scholar 

  34. Yamamoto M, Tujikawa T, Fujita Y, Chino Y, Kurokawa T, Kiyono Y, et al. Metabolic tumor burden predicts prognosis of ovarian cancer patients who receive platinum-based adjuvant chemotherapy. Cancer Sci. 2016;107:478–85.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Mikhaeel NG, Smith D, Dunn JT, Phillips M, Møller H, Fields PA, et al. Combination of baseline metabolic tumour volume and early response on PET/CT improves progression-free survival prediction in DLBCL. Eur J Nucl Med Mol Imaging. 2016;43:1209–19.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Roedl JB, Colen RR, Holalkere NS, Fischman AJ, Choi NC, Blake MA. Adenocarcinomas of the esophagus: response to chemoradiotherapy is associated with decrease of metabolic tumor volume as measured on PET-CT. Comparison to histopathologic and clinical response evaluation. Radiother Oncol. 2008;89:278–86.

    Article  PubMed  CAS  Google Scholar 

  37. Nakamura K, Hongo A, Kodama J, Hiramatsu Y. The pretreatment of maximum standardized uptake values (SUVmax) of the primary tumor is predictor for poor prognosis for patients with epithelial ovarian cancer. Acta Med Okayama. 2012;66:53–60.

    PubMed  Google Scholar 

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Acknowledgements

This study was financially supported by the Clinical Research (EVO) fund of the Turku University Hospital and grants from the Turku University Foundation, the Medical Faculty of University of Turku, the Finnish Cultural Foundation and Ida Montini Foundation.

Funding

This study was financially supported by the Clinical Research (EVO) fund of the Turku University Hospital and grants from the Turku University Foundation, the Medical Faculty of University of Turku, the Finnish Cultural Foundation and Ida Montini Foundation.

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Authors and Affiliations

  1. Department of Obstetrics and Gynecology, University of Turku and Turku University Hospital, PL 52, 20521, Turku, Finland

    Tuulia Vallius, Johanna Hynninen & Seija Grénman

  2. Department of Clinical Physiology and Nuclear Medicine, Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland

    Jukka Kemppainen & Marko Seppänen

  3. Department of Nuclear Medicine, Sao Joao Hospital Centre, Oporto, Portugal

    Victor Alves

  4. Center of Statistics and Department of Clinical Medicine, University of Turku, Turku, Finland

    Kari Auranen

  5. Turku University Hospital, Clinical Research Centre, Turku, Finland

    Jaakko Matomäki

  6. Department of Obstetrics and Gynecology, Satakunta Central Hospital, Pori, Finland

    Sinikka Oksa

  7. Medical Imaging centre of Southwest Finland, University of Turku and Turku University Hospital, Turku, Finland

    Johanna Virtanen

  8. Department of Obstetrics and Gynecology, University of Tampere and Tampere University Hospital, Tampere, Finland

    Annika Auranen

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  1. Tuulia Vallius
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Correspondence to Tuulia Vallius.

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Conflict of interest

Dr. Tuulia Vallius has received research grants from the Clinical Research (EVO) fund of the Turku University Hospital, the Turku University Foundation, the Medical Faculty of University of Turku, the Finnish Cultural Foundation and Ida Montini Foundation. All the other co-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.

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Informed consent was obtained from all individual participants included in the study.

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Vallius, T., Hynninen, J., Kemppainen, J. et al. 18F-FDG-PET/CT based total metabolic tumor volume change during neoadjuvant chemotherapy predicts outcome in advanced epithelial ovarian cancer. Eur J Nucl Med Mol Imaging 45, 1224–1232 (2018). https://doi.org/10.1007/s00259-018-3961-z

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