Comparative assessment of methods for estimating tumor volume and standardized uptake value in18F-FDG PET

Journal of Nuclear Medicine

Volumn 51, Issue 2, 2010, Pages 268-276

  Tylski, Perrine ^a   Stute, Simon ^a   Grotus, Nicolas ^a   Doyeux, Kaya ^b   Hapdey, Sébastien ^b   Gardin, Isabelle ^b   Vanderlinden, Bruno ^c   Buvat, Ir̀ene ^a  

^a Centre National de la Recherche Scientifique   (France)

^b UNIVERSITÉ DE ROUEN   (France)

^c UNIVERSITÉ LIBRE DE BRUXELLES   (Belgium)

Author keywords

Partial volume effect correction; PET; Standardized uptake value; Tumor segmentation; Tumor volume

Indexed keywords

FLUORODEOXYGLUCOSE F 18;

ARTICLE; DIAGNOSTIC ACCURACY; PHANTOM; POSITRON EMISSION TOMOGRAPHY; PRIORITY JOURNAL; RELIABILITY; SIMULATION; TUMOR VOLUME;

EID: 75749089680     PISSN: 01615505     EISSN: None     Source Type: Journal    
DOI: 10.2967/jnumed.109.066241     Document Type: Article

References (34)

1. Erdi YE, Mawlawi O, Larson SM, et al. Segmentation of lung lesion volume by adaptive positron emission tomography image thresholding. Cancer. 1997;80(12, suppl):2505-2509.
2. 18F-FDG PET-positive tissue for target volume definition in radiotherapy of patients with non-small cell lung cancer. J Nucl Med. 2005;46:1342-1348.
3. 18F-FDG image analysis-method and preliminary results. Eur J Nucl Med Mol Imaging. 2008;35:393-406.
4. van Dalen JA, Hoffmann AL, Dicken V, et al. A novel iterative method for lesion delineation and volumetric quantification with FDG PET. Nucl Med Commun. 2007;28:485-493.
5. Jentzen W, Freudenberg L, Eising EG, Heinze M, Brandau W, Bockisch A. segmentation of PET volumes by iterative image thresholding. J Nucl Med. 2007;48:108-114.
6. Black QC, Grills IS, Kestin LL, et al. Defining a radiotherapy target with positron emission tomography. Int J Radiat Oncol Biol Phys. 2004;60:1272-1282.
7. Drever L, Roa W, McEwan A, Robinson D. Iterative threshold segmentation for PET target volume delineation. Med Phys. 2007;34:1253-1265.
8. 18F-FDG PET. J Nucl Med. 2008;49:892-898.
9. 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;34:1427-1438.
10. Drever LA, Roa W, McEwan A, Robinson D. Comparison of three image segmentation techniques for target volume delineation in positron emission tomography. J Appl Clin Med Phys. 2007;8:93-109.
11. Li H, Thorstad WL, Biehl KJ, et al. A novel PET tumor delineation method based on adaptive region-growing and dual-front active contours. Med Phys. 2008;35:3711-3721.
12. Hatt M, Lamare F, Boussion N, et al. Fuzzy hidden Markov chains segmentation for volume determination and quantitation in PET. Phys Med Biol. 2007;52: 3467-3491.
13. Montgomery DW, Amira A, Zaidi H. Fully automated segmentation of oncological PET volumes using a combined multiscale and statistical model. Med Phys. 2007;34:722-736.
14. Daisne JF, Duprez T, Weynand B, et al. Tumor volume in pharyngolaryngeal squamous cell carcinoma: comparison at CT, MR imaging, and FDG PET and validation with surgical specimen. Radiology. 2004;233:93-100.
15. Schinagl DA, Vogel WV, Hoffmann AL, van Dalen JA, Oyen WJ, Kaanders JH. Comparison of five segmentation tools for 18F-fluoro-deoxy-glucose-positron emission tomography-based target volume definition in head and neck cancer. Int J Radiat Oncol Biol Phys. 2007;69:1282-1289.
16. Jarritt PH, Carson KJ, Hounsell AR, Visvikis D. The role of PET/CT scanning in radiotherapy planning. Br J Radiol. 2006;79:S27-S35.
17. Boellaard R, Krak NC, Hoekstra OS, Lammertsma AA. Effects of noise, image resolution, and ROI definition on the accuracy of standard uptake values: a simulation study. J Nucl Med. 2004;45:1519-1527.
18. Krak NC, Boellaard R, Hoekstra OS, Twisk JW, Hoekstra CJ, Lammertsma AA. Effects of ROI definition and reconstruction method on quantitative outcome and applicability in a response monitoring trial. Eur J Nucl Med Mol Imaging. 2005; 32:294-301.
19. Tylski P, Grotus N, Giraud P, Rosenwald J, Buvat I. Experimental comparison of three methods for estimating tumor volume in FDG PET [abstract]. J Nucl Med. 2007;48(suppl):43P.
20. Ollinger JM. Model-based scatter correction for fully 3D PET. Phys Med Biol. 1996;41:153-176.
21. Jan S, Santin G, Strul D, et al. GATE: a simulation toolkit for PET and SPECT. Phys Med Biol. 2004;49:4543-4561.
22. Stute S, Tylski P, Grotus N, Buvat I. LuCaS: Efficient Monte Carlo simulations of highly realistic PET tumor images. IEEE Nucl Sci Symp Conf Rec. 2008: 4010-4012.
23. Chen CH, Muzic RF Jr, Nelson AD, Adler LP. Simultaneous recovery of size and radioactivity concentration of small spheroids with PET data. J Nucl Med. 1999;40:118-130.
24. Fritsch F, Carlson R. Monotone piecewise cubic interpolation. SIAM J Numer Anal. 1980;17:238-246.
25. Soret M, Bacharach SL, Buvat I. Partial-volume effect in PET tumor imaging. J Nucl Med. 2007;48:932-945.
26. Lunts A, Brailovskiy V. Evaluation of attributes obtained in statistical decision rules. Eng Cybern. 1967;3:982-1009.
27. Bland JM, Altman DG. Multiple significance tests: the Bonferroni method. Br Med J. 1995;310:170.
28. Zar JH. Biostatistical Analysis. 5th ed. Upper Saddle River, NJ: Pearson Education; 2009.
29. Daisne JF, Sibomana M, Bol A, Doumont T, Lonneux M, Gregoire V. Tri-dimensional automatic segmentation of PET volumes based on measured source-to-background ratios: influence of reconstruction algorithms. Radiother Oncol. 2003; 69:247-250.
30. Feuardent J, Soret M, de Dreuille O, Foehrenbach H, Buvat I. Reliability of uptake estimates in FDG PET as a function of acquisition and processing protocols using the CPET. IEEE Trans Nucl Sci. 2005;52:1447-1452.
31. Brambilla M, Matheoud R, Secco C, Loi G, Krengli M, Inglese E. Threshold segmentation for PET target volume delineation in radiation treatment planning: the role of target-to-background ratio and target size. Med Phys. 2008;35:1207-1213.
32. Geworski L, Knoop B, de Cabrejas M, Knapp W, Munz D. Recovery correction for quantitation in emission tomography: a feasibility study. Eur J Nucl Med. 2000;27:161-169.
33. Grotus N, Reader A, Stute S, Rosenwald J, Giraud P, Buvat I. Fully 4D list-mode reconstruction applied to respiratory-gated PET scans. Phys Med Biol. 2009;54: 1705-1721.
34. El Naqa I, Grigsby P, Apte A, et al. Exploring feature-based approaches in PET images for predicting cancer treatment outcomes. Pattern Recognit. 2009;42: 1162-1171.