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Intra-reader reliability of FDG PET volumetric tumor parameters: effects of primary tumor size and segmentation methods

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Abstract

Objective

To establish the effects of size and segmentation methods on intra-reader reliability of primary tumor metabolic tumor volume (MTV) and total glycolytic activity (TGA) in human solid tumors.

Methods

This is a retrospective study of 121 patients who had a baseline FDG PET/CT scan for oncologic staging. Volumetric parameter readings were performed in random order on two separate occasions, 12 weeks apart, by the same reader. The MTV and TGA were segmented using gradient and fixed maximum standardized uptake value (SUVmax) threshold methods. Intra-reader reliability was established by the intraclass correlation coefficient (ICC) and Bland–Altman analysis.

Results

The biases for MTV were 2.95, 14.76 and 11.13 % for gradient segmentation, 38 and 50 % SUVmax fixed threshold segmentations, respectively (p < 0.0001). For TGA, the corresponding biases were 0.76, 10.36 and 7.46 % (p < 0.0001). There were no statistically significant differences in the biases between the first and second reads for MTV segmented for small and large volume tumors by the gradient method (p < 0.34) or 50 % SUVmax threshold segmentation (p < 0.08). However, there were statistically significant differences in the corresponding biases for the 38 % SUVmax threshold segmentation (p < 0.04). There were no statistically significant differences in the biases between the first and second reads for TGA segmented for small and large volume tumors (p < 0.98).

Conclusion

Intra-reader reliability for primary tumor FDG MTV and TGA is affected by the tumor size and segmentation methods. The segmentation bias was smaller for gradient method than percentage fixed threshold method for MTV. The segmentation biases were smaller for TGA than MTV.

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References

  1. Sullivan DC, Gatsonis C. Response to treatment series: part 1 and introduction, measuring tumor response–challenges in the era of molecular medicine. AJR Am J Roentgenol. 2011;197:15–7.

    Article  PubMed  Google Scholar 

  2. Subramaniam RM, Truong M, Peller P, Sakai O, Mercier G. Fluorodeoxyglucose-positron-emission tomography imaging of head and neck squamous cell cancer. AJNR Am J Neuroradiol. 2010;31:598–604.

    Article  PubMed  CAS  Google Scholar 

  3. Davison JM, Ozonoff A, Imsande HM, Grillone GA, Subramaniam RM. Squamous cell carcinoma of the palatine tonsils: FDG standardized uptake value ratio as a biomarker to differentiate tonsillar carcinoma from physiologic uptake. Radiology. 2010;255:578–85.

    Article  PubMed  Google Scholar 

  4. Karantanis D, Bogsrud TV, Wiseman GA, Mullan BP, Subramaniam RM, Nathan MA, et al. Clinical significance of diffusely increased 18F-FDG uptake in the thyroid gland. J Nucl Med. 2007;48:896–901.

    Article  PubMed  CAS  Google Scholar 

  5. Karantanis D, Subramaniam RM, Witte RJ, Mullan BP, Nathan MA, et al. 18F-FDG PET/CT in primary central nervous system lymphoma in HIV-negative patients. Nucl Med Commun. 2007;28:834–41.

    Article  PubMed  Google Scholar 

  6. Karantanis D, Subramaniam RM, Peller PJ, Lowe VJ, Durski JM, Collins DA, et al. The value of [(18)F]fluorodeoxyglucose positron emission tomography/computed tomography in extranodal natural killer/T-cell lymphoma. Clin Lymphoma Myeloma. 2008;8:94–9.

    Article  PubMed  Google Scholar 

  7. Imsande HM, Davison JM, Truong MT, Devaiah AK, Mercier G, Ozonoff Al, et al. Use of 18F-FDG PET/CT as a predictive biomarker of outcome in patients with head-and-neck non-squamous cell carcinoma. AJR Am J Roentgenol. 2011;197(4):976–80.

    Article  PubMed  Google Scholar 

  8. Seol YM, Kwon BR, Song MK, Choi YJ, Shin HJ, Chung JS, et al. Measurement of tumor volume by PET to evaluate prognosis in patients with head and neck cancer treated by chemo-radiation therapy. Acta Oncol. 2010;49:201–8.

    Article  PubMed  CAS  Google Scholar 

  9. Lee HY, Hyun SH, Lee KS, Kim BT, Kim J, Shim YM, et al. Volume-based parameter of 18F-FDG PET/CT in malignant pleural mesothelioma: prediction of therapeutic response and prognostic implications. Ann Surg Oncol. 2010;17:2787–94.

    Article  PubMed  Google Scholar 

  10. Hatt M, Cheze Le Rest C, Albarghach N, Pradier O, Visvikis D. PET functional volume delineation: a robustness and repeatability study. Eur J Nucl Med Mol Imaging. 2011;38:663–72.

    Article  PubMed  Google Scholar 

  11. Hatt M, Cheze-Le Rest C, Aboagye EO, Kenny LM, Rosso L, Turkheimer FE, et al. Reproducibility of 18F-FDG and 3′-deoxy-3′-18F-fluorothymidine PET tumor volume measurements. J Nucl Med. 2010;51:1368–76.

    Article  PubMed  CAS  Google Scholar 

  12. Hyun SH, Choi JY, Shim YM, Kim K, Lee SJ, Cho YS, et al. Prognostic value of metabolic tumor volume measured by 18F-fluorodeoxyglucose positron emission tomography in patients with esophageal carcinoma. Ann Surg Oncol. 2010;17(1):115–22.

    Article  PubMed  Google Scholar 

  13. La TH, Filion EJ, Turnbull BB, Chu JN, Lee P, Nguyen K, et al. Metabolic tumor volume predicts for recurrence and death in head-and-neck cancer. Int J Radiat Oncol Biol Phys. 2009;74:1335–41.

    Article  PubMed  Google Scholar 

  14. Hadiprodjo D, Ryan T, Truong M, Mercier G, Subramaniam R. Parotid gland tumors: preliminary data for the value of FDG PET/CT diagnostic parameters. AJR (in press). 2011.

  15. Dibble E, Lara Alvarez A, Truong M, Mercier G, Cook E, Subramaniam RM. FDG metabolic tumor volume and total glycolytic activity: prognostic imaging biomarkers of oral and oropharyngeal squamous cell cancers. J Nucl Med. 2012;53:709–15.

    Article  PubMed  CAS  Google Scholar 

  16. Werner-Wasik M, Nelson AD, Choi W, Arai Y, Faulhaber PF, Kang P, et al. What is the best way to contour lung tumors on PET Scans? multiobserver validation of a gradient-based method using a NSCLC digital PET phantom. Int J Radiat Oncol Biol Phys. 2012;82:1164–71.

    Article  PubMed  Google Scholar 

  17. Cheebsumon P, van Velden FH, Yaqub M, Frings V, de Langen AJ, Hoekstra OS, et al. Effects of image characteristics on performance of tumor delineation methods: a test–retest assessment. J Nucl Med. 2011;52:1550–8.

    Article  PubMed  CAS  Google Scholar 

  18. Hatt M, Visvikis D, Le Rest CC. Autocontouring versus manual contouring. J Nucl Med. 2011;52:658.

    Article  PubMed  Google Scholar 

  19. MacManus M, Nestle U, Rosenzweig KE, Carrio I, Messa C, Belohlavek O, et al. Use of PET and PET/CT for radiation therapy planning: IAEA expert report 2006–2007. Radiother Oncol. 2009;91:85–94.

    Article  PubMed  Google Scholar 

  20. Geets X, Lee JA, Bol A, Lonneux M, Gregoire V. A gradient-based method for segmenting FDG-PET images: methodology and validation. Eur J Nucl Med Mol Imaging. 2007;34:1427–38.

    Article  PubMed  Google Scholar 

  21. Wanet M, Lee JA, Weynand B, De Bast M, Poncelet A, Lacroix V, et al. Gradient-based delineation of the primary GTV on FDG-PET in non-small cell lung cancer: a comparison with threshold-based approaches. CT and surgical specimens. Radiother Oncol. 2011;98:117–25.

    Article  PubMed  Google Scholar 

  22. Murphy JD, Chisholm KM, Daly ME, Wiegner EA, Truong D, Iagaru A, et al. Correlation between metabolic tumor volume and pathologic tumor volume in squamous cell carcinoma of the oral cavity. Radiother Oncol. 2011;101:356–61.

    Article  PubMed  Google Scholar 

  23. Dewalle-Vignion AS, Yeni N, Petyt G, Verscheure L, Huglo D, Beron A, et al. Evaluation of PET volume segmentation methods: comparisons with expert manual delineations. Nucl Med Commun. 2012;33:34–42.

    Article  PubMed  Google Scholar 

  24. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159–74.

    Article  PubMed  CAS  Google Scholar 

  25. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1:307–10.

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  Google Scholar 

  27. Jackson T, Chung M, Ozonoff A, Mercier G, Subramaniam RM. FDG PET/CT inter-observer agreement in head and neck cancer: FDG and CT measurements of the primary tumor site. Nucl Med Commun. 2012;33:305–12.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

Rathan Subramaniam was supported by a GE-AUR Research fellowship and received Siemens molecular imaging and MJ Fox foundation research grants.

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Correspondence to R. M. Subramaniam.

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Shah, B., Srivastava, N., Hirsch, A.E. et al. Intra-reader reliability of FDG PET volumetric tumor parameters: effects of primary tumor size and segmentation methods. Ann Nucl Med 26, 707–714 (2012). https://doi.org/10.1007/s12149-012-0630-3

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  • DOI: https://doi.org/10.1007/s12149-012-0630-3

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