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What Do We Measure in Oncology PET?

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Abstract

Positron emission tomography (PET) has come to the practice of oncology. It is known that 18F-fluorodeoxyglucose (FDG) PET is more sensitive for the assessment of treatment response than conventional imaging. In addition, PET has an advantage in the use of quantitative analysis of the study. Nowadays, various PET parameters are adopted in clinical settings. In addition, a wide range of factors has been known to be associated with FDG uptake. Therefore, there has been a need for standardization and harmonization of protocols and PET parameters. We will introduce PET parameters and discuss major issues in this review.

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References

  1. Frey EC, Humm JL, Ljungberg M. Accuracy and precision of radioactivity quantification in nuclear medicine images. Semin Nucl Med. 2012;42(3):208–18.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Doot RK, McDonald ES, Mankoff DA. Role of PET quantitation in the monitoring of cancer response to treatment: review of approaches and human clinical trials. Clin Transl Imaging. 2014;2(4):295–303.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Adams MC, Turkington TG, Wilson JM, Wong TZ. A systematic review of the factors affecting accuracy of SUV measurements. AJR Am J Roentgenol. 2010;195(2):310–20.

    Article  PubMed  Google Scholar 

  4. Young H, Baum R, Cremerius U, Herholz K, Hoekstra O, Lammertsma AA, et al. Measurement of clinical and subclinical tumour response using [18F]-fluorodeoxyglucose and positron emission tomography: review and 1999 EORTC recommendations. European Organization for Research and Treatment of Cancer (EORTC) PET Study Group. Eur J Cancer. 1999;35(13):1773–82.

    Article  CAS  PubMed  Google Scholar 

  5. 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  CAS  PubMed  PubMed Central  Google Scholar 

  6. RSNA RSoNA. Quantitative Imaging Biomarkers Alliance™. 2015. https://rsna.org/QIBA/. Accessed 17 November 2015.

  7. Graham MM, Wahl RL, Hoffman JM, Yap JT, Sunderland JJ, Boellaard R, et al. Summary of the UPICT protocol for 18F-FDG PET/CT imaging in oncology clinical trials. J Nucl Med. 2015;56(6):955–61.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Boellaard R, Delgado-Bolton R, Oyen WJ, Giammarile F, Tatsch K, Eschner W, et al. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0. Eur J Nucl Med Mol Imaging. 2015;42(2):328–54.

    Article  CAS  PubMed  Google Scholar 

  9. Lucignani G. SUV and segmentation: pressing challenges in tumour assessment and treatment. Eur J Nucl Med Mol Imaging. 2009;36(4):715–20.

    Article  PubMed  Google Scholar 

  10. Lodge MA, Chaudhry MA, Wahl RL. Noise considerations for PET quantification using maximum and peak standardized uptake value. J Nucl Med. 2012;53(7):1041–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Vanderhoek M, Perlman SB, Jeraj R. Impact of the definition of peak standardized uptake value on quantification of treatment response. J Nucl Med. 2012;53(1):4–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Pak K, Cheon GJ, Nam HY, Kim SJ, Kang KW, Chung JK, et al. Prognostic value of metabolic tumor volume and total lesion glycolysis in head and neck cancer: a systematic review and meta-analysis. J Nucl Med. 2014;55(6):884–90.

    Article  CAS  PubMed  Google Scholar 

  13. Rahim MK, Kim SE, So H, Kim HJ, Cheon GJ, Lee ES, et al. Recent trends in PET image interpretations using volumetric and texture-based quantification methods in nuclear oncology. Nucl Med Mol Imaging. 2014;48(1):1–15.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Daisne JF, Duprez T, Weynand B, Lonneux M, Hamoir M, Reychler H, et al. Tumor volume in pharyngolaryngeal squamous cell carcinoma: comparison at CT, MR imaging, and FDG PET and validation with surgical specimen. Radiology. 2004;233(1):93–100.

    Article  PubMed  Google Scholar 

  15. de Jong PA, van Ufford HM, Baarslag HJ, de Haas MJ, Wittebol SH, Quekel LG, et al. CT and 18F-FDG PET for noninvasive detection of splenic involvement in patients with malignant lymphoma. AJR Am J Roentgenol. 2009;192(3):745–53.

    Article  PubMed  Google Scholar 

  16. Zheng Y, Syh J, Yao M, Wessels B. An automatic method for PET target segmentation using a lookup table based on volume and concentration ratio. Technol Cancer Res Treat. 2010;9(3):243–52.

    Article  PubMed  Google Scholar 

  17. Arens AI, Troost EG, Hoeben BA, Grootjans W, Lee JA, Gregoire V, et al. Semiautomatic methods for segmentation of the proliferative tumour volume on sequential FLT PET/CT images in head and neck carcinomas and their relation to clinical outcome. Eur J Nucl Med Mol Imaging. 2014;41(5):915–24.

    Article  PubMed  Google Scholar 

  18. Schaefer A, Kim YJ, Kremp S, Mai S, Fleckenstein J, Bohnenberger H, et al. PET-based delineation of tumour volumes in lung cancer: comparison with pathological findings. Eur J Nucl Med Mol Imaging. 2013;40(8):1233–44.

    Article  CAS  PubMed  Google Scholar 

  19. Ott K, Fink U, Becker K, Stahl A, Dittler HJ, Busch R, et al. Prediction of response to preoperative chemotherapy in gastric carcinoma by metabolic imaging: results of a prospective trial. J Clin Oncol. 2003;21(24):4604–10.

    Article  CAS  PubMed  Google Scholar 

  20. Paquet N, Albert A, Foidart J, Hustinx R. Within-patient variability of (18)F-FDG: standardized uptake values in normal tissues. J Nucl Med. 2004;45(5):784–8.

    CAS  PubMed  Google Scholar 

  21. van den Hoff J, Oehme L, Schramm G, Maus J, Lougovski A, Petr J, et al. The PET-derived tumor-to-blood standard uptake ratio (SUR) is superior to tumor SUV as a surrogate parameter of the metabolic rate of FDG. EJNMMI Res. 2013;3(1):77.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Mawlawi O, Erasmus JJ, Munden RF, Pan T, Knight AE, Macapinlac HA, et al. Quantifying the effect of IV contrast media on integrated PET/CT: clinical evaluation. AJR Am J Roentgenol. 2006;186(2):308–19.

    Article  PubMed  Google Scholar 

  23. 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(11):1760–9.

    Article  PubMed  Google Scholar 

  24. Sugawara Y, Zasadny KR, Neuhoff AW, Wahl RL. Reevaluation of the standardized uptake value for FDG: variations with body weight and methods for correction. Radiology. 1999;213(2):521–5.

    Article  CAS  PubMed  Google Scholar 

  25. James WPT. Research on obesity1976. Report No.: 0-11-4500347.

  26. Boer P. Estimated lean body mass as an index for normalization of body fluid volumes in humans. Am J Physiol. 1984;247(4 Pt 2):F632–6.

    CAS  PubMed  Google Scholar 

  27. Hume R. Prediction of lean body mass from height and weight. J Clin Pathol. 1966;19(4):389–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Wang Y, Moss J, Thisted R. Predictors of body surface area. J Clin Anesth. 1992;4(1):4–10.

    Article  CAS  PubMed  Google Scholar 

  29. Mosteller RD. Simplified calculation of body-surface area. N Engl J Med. 1987;317(17):1098.

    CAS  PubMed  Google Scholar 

  30. Haycock GB, Schwartz GJ, Wisotsky DH. Geometric method for measuring body surface area: a height-weight formula validated in infants, children, and adults. J Pediatr. 1978;93(1):62–6.

    Article  CAS  PubMed  Google Scholar 

  31. Assen S. Kirov LMF. Pathology-validated PET image data sets and their role in PET segmentation. Clin Translational Imaging.2(3):253-67.

  32. Hatt M, Cheze-le Rest C, van Baardwijk A, Lambin P, Pradier O, Visvikis D. Impact of tumor size and tracer uptake heterogeneity in (18)F-FDG PET and CT non-small cell lung cancer tumor delineation. J Nucl Med. 2011;52(11):1690–7.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Yu J, Li X, Xing L, Mu D, Fu Z, Sun X, et al. Comparison of tumor volumes as determined by pathologic examination and FDG-PET/CT images of non-small-cell lung cancer: a pilot study. Int J Radiat Oncol Biol Phys. 2009;75(5):1468–74.

    Article  PubMed  Google Scholar 

  34. Benz MR, Evilevitch V, Allen-Auerbach MS, Eilber FC, Phelps ME, Czernin J, et al. Treatment monitoring by 18F-FDG PET/CT in patients with sarcomas: interobserver variability of quantitative parameters in treatment-induced changes in histopathologically responding and nonresponding tumors. J Nucl Med. 2008;49(7):1038–46.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgement

This study was supported by a grant from the National R&D Program for Cancer Control, Ministry for Health and Welfare, Republic of Korea (0920050).

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Correspondence to Seong-Jang Kim.

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Kyoungjune Pak and Seong-Jang Kim declare that they have no conflict of interest.

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No research interventions were done in this review (no ethics approval needed).

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Pak, K., Kim, SJ. What Do We Measure in Oncology PET?. Nucl Med Mol Imaging 51, 212–216 (2017). https://doi.org/10.1007/s13139-016-0416-y

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  • DOI: https://doi.org/10.1007/s13139-016-0416-y

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