Generating harmonized SUV within the EANM EARL accreditation program: software approach versus EARL-compliant reconstruction
Evolutions in hardware and software PET technology, such as point spread function (PSF) reconstruction, have been shown to improve diagnostic performance, but can also lead to important device-dependent and reconstruction-dependent variations in standardized uptake values (SUVs). This may preclude the multicentre use of SUVs as a prognostic or diagnostic tool or as a biomarker of the early response to antineoplastic treatments. This study compared two SUV harmonization strategies using a newer reconstruction algorithm that improves lesion detection while maintaining comparability with older systems: (1) the use of a second reconstruction compliant with harmonization standards and (2) the use of a proprietary software tool (EQ.PET).
PET data from 50 consecutive non-small cell lung cancer patients were reconstructed with PSF reconstruction for optimal tumor detection and an ordered subset expectation maximization (OSEM3D) reconstruction to mimic a former generation PET. An additional PSF reconstruction was performed with a 7 mm Gaussian filter (PSF7, first method), and, post-reconstruction, the EQ filter (same Gaussian filter) was applied to the PSF data (PSFEQ, second method) for harmonization purposes. The 7 mm kernel filter was chosen to comply with the European Association of Nuclear Medicine (EANM) standards. SUVs for all reconstructions were compared with regression analyses and/or Bland–Altman plots.
Overall, 171 lesions were analyzed: 55 lung lesions (32.2%), 87 lymph nodes (50.9%), and 29 metastases (16.9%). In these lesions, the mean PSF7/OSEM3D ratios for SUVmax and SUVpeak were 1.02 (95% CI: 0.93–1.11) and 1.04 (95% CI: 0.95–1.14), respectively. The mean PSFEQ/OSEM3D ratios for SUVmax and SUVpeak were 1.01 (95% CI: 0.91–1.11) and 1.04 (95% CI: 0.94–1.14), respectively. When comparing PSF7 and PSFEQ, Bland–Altman analysis showed that the mean PSF7/PSFEQ ratios for SUVmax and SUVpeak were 1.01 (95% CI: 0.96–1.06) and 1.01 (95% CI: 0.97–1.04), respectively.
The issue of reconstruction dependency in SUV values that hampers the comparison of data between different PET systems can be overcome using two reconstructions for harmonized quantification and optimal diagnosis or using the EQ.PET technology. Both technologies produce similar results, EQ.PET sparing reconstruction and interpretation time. Other manufacturers are encouraged to either emulate this solution or to produce a vendor-neutral approach.
KeywordsPositron emission tomography 18F-Fluorodeoxyglucose Quantitation Standardized uptake value Harmonization
Dr. Alison Johnson, François Baclesse cancer Centre, France, is thanked for her critical review of the manuscript.
Compliance with ethical standards
Conflict of interest disclosure
Informed consent was waived for this type of study by the local ethics committee (Ref A12-D24-VOL13, Comité de protection des personnes Nord-Ouest III).
- 2.Konings R, van Gool MH, Bard MP, Zwijnenburg A, Titulaer BM, Aukema TS, et al. Prognostic value of pre-operative glucose-corrected maximum standardized uptake value in patients with non-small cell lung cancer after complete surgical resection and 5-year follow-up. Ann Nucl Med. 2016;30:362–8. doi: 10.1007/s12149-016-1070-2.CrossRefPubMedGoogle Scholar
- 4.Shigemoto Y, Suga K, Matsunaga N. F-18-FDG-avid lymph node metastasis along preferential lymphatic drainage pathways from the tumor-bearing lung lobe on F-18-FDG PET/CT in patients with non-small-cell lung cancer. Ann Nucl Med. 2016;30:287–97. doi: 10.1007/s12149-016-1063-1.CrossRefPubMedGoogle Scholar
- 5.Yamamoto T, Kadoya N, Shirata Y, Kaneta T, Koto M, Umezawa R, et al. Formula corrected maximal standardized uptake value in FDG-PET for partial volume effect and motion artifact is not a prognostic factor in stage I non-small cell lung cancer treated with stereotactic body radiotherapy. Ann Nucl Med. 2015;29:666–73. doi: 10.1007/s12149-015-0991-5.CrossRefPubMedGoogle Scholar
- 9.Tong S, Alessio AM, Kinahan PE. Evaluation of noise properties in PSF-based PET image reconstruction. IEEE Nucl Sci Symp Conf Rec. 1997;2009(2009):3042–7.Google Scholar
- 11.Bellevre D, Blanc Fournier C, Switsers O, Dugue AE, Levy C, Allouache D, et al. Staging the axilla in breast cancer patients with (1)(8)F-FDG PET: how small are the metastases that we can detect with new generation clinical PET systems? Eur J Nucl Med Mol Imaging. 2014;41:1103–12. doi: 10.1007/s00259-014-2689-7.CrossRefPubMedPubMedCentralGoogle Scholar
- 13.Rogasch JM, Steffen IG, Hofheinz F, Grosser OS, Furth C, Mohnike K, et al. The association of tumor-to-background ratios and SUVmax deviations related to point spread function and time-of-flight F18-FDG-PET/CT reconstruction in colorectal liver metastases. EJNMMI Res. 2015;5:31. doi: 10.1186/s13550-015-0111-5.CrossRefPubMedPubMedCentralGoogle Scholar
- 21.Lasnon C, Desmonts C, Quak E, Gervais R, Do P, Dubos-Arvis C, et al. Harmonizing SUVs in multicentre trials when using different generation PET systems: prospective validation in non-small cell lung cancer patients. Eur J Nucl Med Mol Imaging. 2013;40:985–96. doi: 10.1007/s00259-013-2391-1.CrossRefPubMedPubMedCentralGoogle Scholar
- 23.Quak E, Le Roux PY, Hofman MS, Robin P, Bourhis D, Callahan J, et al. Harmonizing FDG PET quantification while maintaining optimal lesion detection: prospective multicentre validation in 517 oncology patients. Eur J Nucl Med Mol Imaging. 2015;42:2072. doi: 10.1007/s00259-015-3128-0.CrossRefPubMedPubMedCentralGoogle Scholar