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EJNMMI Research
Published in: EJNMMI Research 1/2018

Open Access 01-12-2018 | Original research

Multicentre analysis of PET SUV using vendor-neutral software: the Japanese Harmonization Technology (J-Hart) study

Authors: Yuji Tsutsui, Hiromitsu Daisaki, Go Akamatsu, Takuro Umeda, Matsuyoshi Ogawa, Hironori Kajiwara, Shigeto Kawase, Minoru Sakurai, Hiroyuki Nishida, Keiichi Magota, Kazuaki Mori, Masayuki Sasaki, J-Hart study group

Published in: EJNMMI Research | Issue 1/2018

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Abstract

Background

Recent developments in hardware and software for PET technologies have resulted in wide variations in basic performance. Multicentre studies require a standard imaging protocol and SUV harmonization to reduce inter- and intra-scanner variability in the SUV. The Japanese standardised uptake value (SUV) Harmonization Technology (J-Hart) study aimed to determine the applicability of vendor-neutral software on the SUV derived from positron emission tomography (PET) images. The effects of SUV harmonization were evaluated based on the reproducibility of several scanners and the repeatability of an individual scanner.
Images were acquired from 12 PET scanners at nine institutions. PET images were acquired over a period of 30 min from a National Electrical Manufacturers Association (NEMA) International Electrotechnical Commission (IEC) body phantom containing six spheres of different diameters and an 18F solution with a background activity of 2.65 kBq/mL and a sphere-to-background ratio of 4. The images were reconstructed to determine parameters for harmonization and to evaluate reproducibility. PET images with 2-min acquisition × 15 contiguous frames were reconstructed to evaluate repeatability. Various Gaussian filters (GFs) with full-width at half maximum (FWHM) values ranging from 1 to 15 mm in 1-mm increments were also applied using vendor-neutral software. The SUVmax of spheres was compared with the reference range proposed by the Japanese Society of Nuclear Medicine (JSNM) and the digital reference object (DRO) of the NEMA phantom. The coefficient of variation (CV) of the SUVmax determined using 12 PET scanners (CVrepro) was measured to evaluate reproducibility. The CV of the SUVmax determined from 15 frames (CVrepeat) per PET scanner was measured to determine repeatability.

Results

Three PET scanners did not require an additional GF for harmonization, whereas the other nine required additional FWHM values of GF ranging from 5 to 9 mm. The pre- and post-harmonization CVrepro of six spheres were (means ± SD) 9.45% ± 4.69% (range, 3.83–15.3%) and 6.05% ± 3.61% (range, 2.30–10.7%), respectively. Harmonization significantly improved reproducibility of PET SUVmax (P = 0.0055). The pre- and post-harmonization CVrepeat of nine scanners were (means ± SD) 6.59% ± 1.29% (range, 5.00–8.98%) and 4.88% ± 1.64% (range, 2.65–6.72%), respectively. Harmonization also significantly improved the repeatability of PET SUVmax (P < 0.0001).

Conclusions

Harmonizing SUV using vendor-neutral software produced SUVmax for 12 scanners that fell within the JSNM reference range of a NEMA body phantom and improved SUVmax reproducibility and repeatability.
Literature
1.
Fletcher JW, Djulbegovic B, Soares HP, Siegel BA, Lowe VJ, Lyman GH, et al. Recommendations on the use of 18F-FDG PET in oncology. J Nucl Med. 2008;49:480–508.CrossRefPubMed
2.
Ben-Haim S, Ell P. 18F-FDG PET and PET/CT in the evaluation of cancer treatment response. J Nucl Med. 2009;50:88–99.CrossRefPubMed
3.
Gupta T, Master Z, Kannan S, Agarwal JP, Ghsoh-Laskar S, Rangarajan V, et al. Diagnostic performance of post-treatment FDG PET or FDG PET/CT imaging in head and neck cancer: a systematic review and meta-analysis. Eur J Nucl Med Mol Imaging. 2011;38:2083–95.CrossRefPubMed
4.
Bengtsson T, Hicks RJ, Peterson A, Port RE. 18F-FDG PET as a surrogate biomarker in non-small cell lung cancer treated with erlotinib: newly identified lesions are more informative than standardized uptake value. J Nucl Med. 2012;53:530–7.CrossRefPubMed
5.
Hicks RJ. Role of 18F-FDG PET in assessment of response in non-small cell lung cancer. J Nucl Med. 2009;50(Suppl 1):31S–42S.CrossRefPubMed
6.
Hellwig D, Graeter TP, Ukena D, Groeschel A, Sybrecht GW, Schaefers HJ, et al. 18F-FDG PET for mediastinal staging of lung cancer: which SUV threshold makes sense? J Nucl Med. 2007;48:1761–6.CrossRefPubMed
7.
Dijkman BG, Schuurbiers OCJ, Vriens D, Looijen-Salamon M, Bussink J, Timmer-Bonte JNH, et al. The role of (18)F-FDG PET in the differentiation between lung metastases and synchronous second primary lung tumours. Eur J Nucl Med Mol Imaging. 2010;37:2037–47.CrossRefPubMedPubMedCentral
8.
Agarwal M, Brahmanday G, Bajaj SK, Ravikrishnan KP, Wong C-YO. Revisiting the prognostic value of preoperative (18)F-fluoro-2-deoxyglucose ( (18)F-FDG) positron emission tomography (PET) in early-stage (I & II) non-small cell lung cancers (NSCLC). Eur J Nucl Med Mol Imaging. 2010;37:691–8.CrossRefPubMed
9.
Liao S, Penney BC, Wroblewski K, Zhang H, Simon CA, Kampalath R, et al. Prognostic value of metabolic tumor burden on 18F-FDG PET in nonsurgical patients with non-small cell lung cancer. Eur J Nucl Med Mol Imaging. 2012;39:27–38.CrossRefPubMed
10.
Sullivan DC, Obuchowski NA, Kessler LG, Raunig DL, Gatsonis C, Huang EP, et al. Metrology standards for quantitative imaging biomarkers. Radiology. 2015;277:813–25.CrossRefPubMedPubMedCentral
11.
O’Connor JPB, Aboagye EO, Adams JE, Aerts HJWL, Barrington SF, Beer AJ, et al. Imaging biomarker roadmap for cancer studies. Nat Rev Clin Oncol. 2017;14:169–86. Nature Publishing GroupCrossRefPubMed
12.
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;45:1519–27.PubMed
13.
Westerterp M, Pruim J, Oyen W, Hoekstra O, Paans A, Visser E, et al. Quantification of FDG PET studies using standardised uptake values in multi-centre trials: effects of image reconstruction, resolution and ROI definition parameters. Eur J Nucl Med Mol Imaging. 2007;34:392–404.CrossRefPubMed
14.
Sunderland JJ, Christian PE. Quantitative PET/CT scanner performance characterization based upon the Society of Nuclear Medicine and Molecular Imaging Clinical Trials Network oncology clinical simulator phantom. J Nucl Med. 2015;56:145–52.CrossRefPubMed
15.
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.CrossRefPubMedPubMedCentral
16.
Rahmim A, Qi J, Sossi V. Resolution modeling in PET imaging: theory, practice, benefits, and pitfalls. Med Phys. 2013;40:64301.CrossRef
17.
Kidera D, Kihara K, Akamatsu G, Mikasa S, Taniguchi T, Tsutsui Y, et al. The edge artifact in the point-spread function-based PET reconstruction at different sphere-to-background ratios of radioactivity. Ann Nucl Med. 2016;30:97–103.CrossRefPubMed
18.
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;56:955–61.CrossRefPubMedPubMedCentral
19.
Boellaard R, Delgado-Bolton R, Oyen WJG, 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;42:328–54.
20.
Fukukita H, Suzuki K, Matsumoto K, Terauchi T, Daisaki H, Ikari Y, et al. Japanese guideline for the oncology FDG-PET/CT data acquisition protocol: synopsis of version 2.0. Ann. Nucl Med. 2014;28:693–705.CrossRefPubMedPubMedCentral
21.
22.
23.
Quak E, Le Roux P-Y, 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;42:2072–82.CrossRefPubMedPubMedCentral
24.
Makris NE, Huisman MC, Kinahan PE, Lammertsma AA, Boellaard R. Evaluation of strategies towards harmonization of FDG PET/CT studies in multicentre trials: comparison of scanner validation phantoms and data analysis procedures. Eur J Nucl Med Mol Imaging. 2013;40:1507–15.CrossRefPubMed
25.
Quak E, Le Roux P-Y, Lasnon C, Robin P, Hofman MS, Bourhis D, et al. Does PET SUV harmonization affect PERCIST response classification? J Nucl Med. 2016;57:1699–706.CrossRefPubMed
26.
Raunig DL, McShane LM, Pennello G, Gatsonis C, Carson PL, Voyvodic JT, et al. Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment. Stat Methods Med Res. 2015;24:27–67.CrossRefPubMed
27.
Pierce LA, Elston BF, Clunie DA, Nelson D, Kinahan PE. A digital reference object to analyze calculation accuracy of PET standardized uptake value. Radiology. 2015;277:538–45.CrossRefPubMedPubMedCentral
28.
29.
Nakahara T, Daisaki H, Yamamoto Y, Iimori T, Miyagawa K, Okamoto T, et al. Use of a digital phantom developed by QIBA for harmonizing SUVs obtained from the state-of-the-art SPECT/CT systems: a multicenter study. EJNMMI Res. 2017;7:53.CrossRefPubMedPubMedCentral
30.
Boellaard R. Standards for PET image acquisition and quantitative data analysis. J Nucl Med. 2009;50(Suppl 1):11S–20S.CrossRefPubMed
31.
32.
Takahashi Y, Oriuchi N, Otake H, Endo K, Murase K. Variability of lesion detectability and standardized uptake value according to the acquisition procedure and reconstruction among five PET scanners. Ann Nucl Med. 2008;22:543–8.CrossRefPubMed
33.
Velasquez LM, Boellaard R, Kollia G, Hayes W, Hoekstra OS, Lammertsma AA, et al. Repeatability of 18F-FDG PET in a multicenter phase I study of patients with advanced gastrointestinal malignancies. J Nucl Med. 2009;50:1646–54.CrossRefPubMed
34.
Doot RK, Scheuermann JS, Christian PE, Karp JS, Kinahan PE. Instrumentation factors affecting variance and bias of quantifying tracer uptake with PET/CT. Med Phys. 2010;37:6035–46.CrossRefPubMedPubMedCentral
35.
36.
Lim R, Eaton A, Lee NY, Setton J, Ohri N, Rao S, et al. 18F-FDG PET/CT metabolic tumor volume and total lesion glycolysis predict outcome in oropharyngeal squamous cell carcinoma. J Nucl Med. 2012;53:1506–13.CrossRefPubMed
Metadata
Title
Multicentre analysis of PET SUV using vendor-neutral software: the Japanese Harmonization Technology (J-Hart) study
Authors
Yuji Tsutsui
Hiromitsu Daisaki
Go Akamatsu
Takuro Umeda
Matsuyoshi Ogawa
Hironori Kajiwara
Shigeto Kawase
Minoru Sakurai
Hiroyuki Nishida
Keiichi Magota
Kazuaki Mori
Masayuki Sasaki
J-Hart study group
Publication date
01-12-2018
Publisher
Springer Berlin Heidelberg
Published in
EJNMMI Research / Issue 1/2018
Electronic ISSN: 2191-219X
DOI
https://doi.org/10.1186/s13550-018-0438-9

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