Correlation of (18F) FDG PET/CT Parameters with Haematological Parameters in Esophageal Cancers and the Effect of These Parameters on Survival

Objective: In the present study, we aimed to investigate the relationship between metabolic (SUVmax) and volume-based (18F)FDG PET/CT parameters (metabolic tumour volume (MTV) and total lesion glycolysis (TLG)) and haematological parameters (neutrophil, lymphocyte, platelet,mean platelet volume(MPV) , neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (TLR)) with survival, and whether haematological parameters are correlated with metabolic and volume-based PET parameters. Method: We included a total of 55 patients who underwent (18F)FDG PET/CT in our nuclear medicine clinic between January 2017 and December 2018 with a diagnosis of esophageal squamous cell carcinoma, had no distant metastasis, either had or did not have regional lymph node metastasis, whose imaging and laboratory data could be retrospectively accessed, who did not undergo an operation before imaging, did not receive chemo-radiotherapy. Results: In multivariate regression analysis, we found esophageal MTV (OR 2.6; 95% CI 1.04–6.57, p: 0.041) and esophageal TLG (OR 2.7; 95% CI 1.2–6.2, p: 0.022) values to be independent variables in terms of survival. While we observed a negative correlation between PLR and esophageal MTV and TLG (p values were respectively p: 0.021, p: 0.03), we observed a positive correlation between lymphocyte counts and esophageal MTV and TLG (p values were p: 0.004, p: 0.001, respectively). We detected a positive correlation between the size and SUVmax of lymph node metastasis, on the one hand, and both neutrophil counts and NLR on the other. Conclusion: We determined MTV and TLG values, which are volume-based metabolic PET parameters, to be independent prognostic factors for survival. MTV and TLG had a negative correlation with PLR and a positive correlation with lymphocyte counts.

Özefagus Kanserlerinde (18F) FDG PET/BT Parametrelerinin Hematolojik Parametreler İle Korelasyonu ve Bu Parametrelerin Sağkalım Üzerine Etkisi

Amaç: Metabolik ve volüm tabanlı 18F-FDG pozitron emisyon tomografisi/bilgisayarlı tomografi (PET/BT) parametreleri (metabolik tümör volümü (MTV), total lezyon glikolizi (TLG), maksimum standardize tutulum değerleri (maksSTD)) ve hematolojik parametrelerin (nötrofil, lenfosit, trombosit, ortalama trombosit hacmi (OTH), nötrofil lenfosit oranı (NLO) ve trombosit-lenfosit oranı (TLO)) sağkalım ile ilişkisini ve ayrıca hematolojik parametreler ile metabolik volüm tabanlı PET parametreleri arasında korelasyon olup olmadığını incelemeyi amaçladık. Yöntemler: Ocak 2017 ile Aralık 2018 tarihleri arasında özefagus skuamöz hücreli karsinom tanısı ile Nükleer Tıp Kliniğimizde PET/BT çekilen uzak metastazı olmayan, bölgesel lenf nodu metastazı olan veya olmayan retrospektif olarak görüntüleme ve laboratuar verilerine ulaşılabilen görüntüleme öncesi opere edilmemiş, kemo-radioterapi almamış, (18F)FDG PET/BT çekimi ile eş zamanlı tam kan parametrelerine ulaşılabilen 55 hasta dahil edildi. Bulgular: Çok değişkenli regresyon analizinde özefagus MTV (OR 2.6; 95% CI 1,04-6,57, p:0,041) ve özefagus TLG (OR 2.7; 95% CI 1.2- 6.2, p:0,022) değerleri sağkalım açısından bağımsız değişkenler olarak bulundu. TLO ile özefagus MTV ve TLG si arasında negatif korelasyon izlenirken (p değerleri sırasıyla p:0,021, p:0,03) lenfosit sayısı ile özefagus MTV ve TLG arasında pozitif korelasyon izlendi (p değerleri sırasıyla p:0,004, p:0,001). Lenf nodu metastazının boyutu ve maksSTD değeri ile hem nötrofil sayısı hem de NLO arasında pozitif korelasyon saptandı. Sonuç: Volüm tabanlı metabolik PET parametreleri olan MTV ve TLG değerleri sağkalım için bağımsız prognostik faktörler olarak bulundu. MTV ve TLG ile TLO arasında negatif korelasyon izlenirken lenfosit sayısı ile pozitif korelasyon izlendi.

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1. Bray F, Ferlay J, Soerjomataram I, et al. Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2018; 68: 394– 424.

2. Blot WJ TR. Cancer Epidemiology and Prevention. 4th ed. Thun MJ, Linet MS, Cerhan JR, Haiman CA SD (eds). New york, Oxford University Press, 2018; 579–92.

3. Baquet CR, Commiskey P, Mack K, et al. Esophageal cancer epidemiology in blacks and whites: Racial and gender disparities in incidence, mortality, survival rates and histology. J Natl Med Assoc. 2005; 97: 1471–8.

4. Enzinger PC, Mayer RJ. Esophageal cancer. N Engl J Med. 2003; 349: 2241–52.

5. Shapiro J, van Lanschot JJB, Hulshof MCCM, et al. Neoadjuvant chemoradiotherapy plus surgery versus surgery alone for oesophageal or junctional cancer (CROSS): Long-term results of a randomised controlled trial. Lancet Oncol. 2015; 16: 1090–8.

6. Stavrou EP, McElroy HJ, Baker DF, et al. Adenocarcinoma of the oesophagus: incidence and survival rates in New South Wales, 1972–2005. Med J. 2009; 191: 310–4.

7. Mantovani A, Allavena P, Sica A, et al. Cancerrelated inflammation. Nature. 2008; 454: 436–44.

8. Matthews LM, Noble F, Tod J, et al. Systematic review and meta-analysis of immunohistochemical prognostic biomarkers in resected oesophageal adenocarcinoma. Br J Cancer. 2015; 113: 1746.

9. Templeton AJ, McNamara MG, Šeruga B, et al. Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: a systematic review and metaanalysis. J Natl Cancer Inst. 2014; 106: dju124.

10. Yang X, Huang Y, Feng JF LJ. Prognostic significance of neutrophil-to-lymphocyte ratio in esophageal cancer: a meta- analysis. Onco Targets Ther. 2015; 10: 789–94.

11. Liao S, Penney BC, Wroblewski K, et al. Prognostic value of metabolic tumor burden on 18FFDG PET in nonsurgical patients with non- small cell lung cancer. Eur J Nucl Med Mol Imaging. 2012; 39: 27–38.

12. Dibble EH, Alvarez AC, Truong MT, et al. 18F-FDG metabolic tumor volume and total glycolytic activity of oral cavity and oropharyngeal squamous cell cancer: adding value to clinical staging. J Nucl Med. 2012; 53: 709–15.

13. Lin J, Kligerman S, Goel R, et al. State-of-the-art molecular imaging in esophageal cancer management: implications for diagnosis, prognosis, and treatment. J Gastrointest Oncol. 2015; 6: 3–19.

14. Hyun SH, Choi JY, Shim YM, et al. Prognostic value of metabolic tumor volume measured by 18Ffluorodeoxyglucose positron emission tomography in patients with esophageal carcinoma. Ann Surg Oncol. 2010; 17: 115–22.

15. Atsumi K, Nakamura K, Abe K, et al. Prediction of outcome with FDG-PET in definitive chemoradiotherapy for esophageal cancer. J Radiat Res. 2013; 54: 890–8.

16. Alie O, Michel P, Ménard JF, et al. The predictive value of treatment response using FDG PET performed on day 21 of chemoradiotherapy in patients with oesophageal squamous cell carcinoma. A prospective, multicentre study (RTEP3). Eur J Nucl Med Mol Imaging. 2013; 40: 1345–55.

17. Hatt M, Tixier F, Cheze Le Rest C, et al. Robustness of intratumour 18F-FDG PET uptake heterogeneity quantification for therapy response prediction in oesophageal carcinoma. Eur J Nucl Med Mol Imaging. 2013; 40: 1662–71.

18. Van Westreenen HL, Plukker JT, Cobben DC, et al. Prognostic value of the standardized uptake value in esophageal cancer. AJR Am J Roentgenol. 2005; 185: 436–40.

19. Omloo JM, Sloof GW, Boellaard R, et al. Importance of fluorodeoxyglucose-positron emission tomography (FDG-PET) and endoscopic ultrasonography parameters in predicting survival following surgery for esophageal cancer. Endoscopy. 2008; 40: 464–71.

20. Song SY, Kim JH, Ryu JS, et al. FDG-PET in the prediction of pathologic response after neoadjuvant chemoradiotherapy in locally advanced, resectable esophageal cancer. Int J Radiat Oncol Biol Phys. 2005; 63: 1053–9.

21. Kitajima K, Doi H, Kuribayashi K, et al. Prognostic value of pretreatment volume-based quantitative 18F-FDG PET/CT parameters in patients with malignant pleural mesothelioma. Eur J Radiol. 26: 2287-96.

22. Choi ES, Ha SG, Kim HS, et al. Total lesion glycolysis by 18F-FDG PET/CT is a reliable predictor of prognosis in soft-tissue sarcoma. Eur J Nucl Med Mol Imaging. 2013; 40: 1836–42.

23. Hong JH, Kim HH, Han E J, et al. Total lesion glycolysis using 18F-FDG PET/CT as a prognostic factor for locally advanced esophageal cancer. J Korean Med Sci. 2016; 31: 39–46.

24. Yildirim BA, Torun N, Guler OC, et al. Prognostic value of metabolic tumor volume and total lesion glycolysis in esophageal carcinoma patients treated with definitive chemoradiotherapy. Nucl Med Commun. 2018; 39: 553–63.

25. Rice TW, Apperson-Hansen C, DiPaola LM, et al. Worldwide Esophageal Cancer Collaboration: clinical staging data. Dis Esophagus. 2016; 29: 707– 14.

26. Mariette C, Piessen G, Briez N et al. The number of metastatic lymph nodes and the ratio between metastatic and examined lymph nodes are independent prognostic factors in esophageal cancer regardless of neoadjuvant chemoradiation or lymphadenectomy extent. Ann Surg. 2008; 247: 365–71.

27. Ogino I, Watanabe S, Misumi T, et al. Lymph Node Metastases Diagnosed by 18F-FDG-PET/CT in Esophageal Squamous Cell Cancer Treated With Concurrent Chemoradiotherapy. Anticancer Res. 2019; 39: 4977-85.

28. Sun Y, Zhang L. The clinical use of pretreatment NLR, PLR, and LMR in patients with esophageal squamous cell carcinoma: Evidence from a metaanalysis. Cancer Manag Res. 2018; 10: 6167–79.

29. Yodying H, Matsuda A, Miyashita M, et al. Prognostic Significance of Neutrophil-to- Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio in Oncologic Outcomes of Esophageal Cancer: A Systematic Review and Meta-analysis. Ann Surg Oncol. 2016; 23: 646–54.

30. Pirozzolo G, Gisbertz SS, Castoro C, et al. Neutrophil-to-lymphocyte ratio as prognostic marker in esophageal cancer: A systematic review and meta-analysis. J Thorac Dis. 2019; 11: 3136–45.

31. Sürücü E, Demir Y, Şengöz T. The correlation between the metabolic tumor volume and haematological parameters in patients with esophageal cancer. Ann Nucl Med. 2015; 29: 906–10.
Dicle Tıp Dergisi-Cover
  • ISSN: 1300-2945
  • Yayın Aralığı: Yılda 4 Sayı
  • Başlangıç: 1963
  • Yayıncı: Cahfer GÜLOĞLU
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