Skip to main content
Log in

Dynamic total-body PET/CT imaging with reduced acquisition time shows acceptable performance in quantification of [18F]FDG tumor kinetic metrics

  • Original Article
  • Published:
European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Purpose

To investigate the feasibility of reducing the acquisition time for continuous dynamic positron emission tomography (PET) while retaining acceptable performance in quantifying kinetic metrics of 2-[18F]-fluoro-2-deoxy-D-glucose ([18F]FDG) in tumors.

Methods

In total, 78 oncological patients underwent total-body dynamic PET imaging for ≥ 60 min, with 8, 20, and 50 patients receiving full activity (3.7 MBq/kg), half activity (1.85 MBq/kg), and ultra-low activity (0.37 MBq/kg) of [18F]FDG, respectively. The dynamic data were divided into 21-, 30-, 45- and ≥ 60-min groups. The kinetic analysis involved model fitting to derive constant rates (VB, K1 to k3, and Ki) for both tumors and normal tissues, using both reversible and irreversible two-tissue-compartment models. One-way ANOVA with repeated measures or the Freidman test compared the kinetic metrics among groups, while the Deming regression assessed the correlation of kinetic metrics among groups.

Results

All kinetic metrics in the 30-min and 45-min groups were statistically comparable to those in the ≥ 60-min group. The relative differences between the 30-min and ≥ 60-min groups ranged from 12.3% ± 15.1% for K1 to 29.8% ± 30.0% for VB, and those between the 45-min and ≥ 60-min groups ranged from 7.5% ± 8.7% for Ki to 24.0% ± 24.3% for VB. However, this comparability was not observed between the 21-min and ≥ 60-min groups. The significance trend of these comparisons remained consistent across different models (reversible or irreversible), administrated activity levels, and partial volume corrections for lesions. Significant correlations in tumor kinetic metrics were identified between the 30-/45-min and ≥ 60-min groups, with Deming regression slopes > 0.813. In addition, the comparability of kinetic metrics between the 30-min and ≥ 60-min groups were established for normal tissues.

Conclusion

The acquisition time for dynamic PET imaging can be reduced to 30 min without compromising the ability to reveal tumor kinetic metrics of [18F]FDG, using the total-body PET/CT system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

The dataset used and/or analyzed in current study are available from the corresponding author on reasonable request.

Code availability

Not applicable.

References

  1. Strauss LG, Klippel S, Pan L, Schonleben K, Haberkorn U, Dimitrakopoulou-Strauss A. Assessment of quantitative FDG PET data in primary colorectal tumours: which parameters are important with respect to tumour detection? Eur J Nucl Med Mol Imaging. 2007;34(6):868–77.

    Article  PubMed  Google Scholar 

  2. Dimitrakopoulou-Strauss A, Strauss LG, Heichel T, Wu H, Burger C, Bernd L, et al. The role of quantitative 18F-FDG PET studies for the differentiation of malignant and benign bone lesions. J Nucl Med. 2002;43(4):510–8.

    PubMed  Google Scholar 

  3. Strauss LG, Dimitrakopoulou-Strauss A, Koczan D, Bernd L, Haberkorn U, Ewerbeck V, et al. 18F-FDG kinetics and gene expression in giant cell tumors. J Nucl Med. 2004;45(9):1528–35.

    CAS  PubMed  Google Scholar 

  4. Cochet A, Pigeonnat S, Khoury B, Vrigneaud JM, Touzery C, Berriolo-Riedinger A, et al. Evaluation of breast Tumor blood flow with dynamic first-pass 18F-FDG PET/CT: comparison with angiogenesis markers and prognostic factors. J Nucl Med. 2012;53(4):512–20.

    Article  CAS  PubMed  Google Scholar 

  5. Dimitrakopoulou-Strauss A, Strauss LG, Schwarzbach M, Burger C, Heichel T, Willeke F, et al. Dynamic PET 18F-FDG studies in patients with primary and recurrent soft-tissue sarcomas: impact on diagnosis and correlation with grading. J Nucl Med. 2001;42(5):713–20.

    CAS  PubMed  Google Scholar 

  6. Rusten E, Rodal J, Revheim ME, Skretting A, Bruland OS, Malinen E. Quantitative dynamic 18FDG-PET and tracer kinetic analysis of soft tissue sarcomas. Acta Oncol. 2013;52(6):1160–7.

    Article  CAS  PubMed  Google Scholar 

  7. Dunnwald LK, Doot RK, Specht JM, Gralow JR, Ellis GK, Livingston RB, et al. PET Tumor metabolism in locally advanced Breast cancer patients undergoing neoadjuvant chemotherapy: value of static versus kinetic measures of fluorodeoxyglucose uptake. Clin Cancer Res. 2011;17(8):2400–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Dimitrakopoulou-Strauss A, Strauss LG, Egerer G, Vasamiliette J, Mechtersheimer G, Schmitt T, et al. Impact of dynamic 18F-FDG PET on the early prediction of therapy outcome in patients with high-risk soft-tissue sarcomas after neoadjuvant chemotherapy: a feasibility study. J Nucl Med. 2010;51(4):551–8.

    Article  PubMed  Google Scholar 

  9. Humbert O, Lasserre M, Bertaut A, Fumoleau P, Coutant C, Brunotte F, et al. Breast Cancer Blood Flow and Metabolism on Dual-Acquisition 18F-FDG PET: correlation with Tumor phenotype and neoadjuvant chemotherapy response. J Nucl Med. 2018;59(7):1035–41.

    Article  CAS  PubMed  Google Scholar 

  10. Dimitrakopoulou-Strauss A, Strauss LG, Burger C, Ruhl A, Irngartinger G, Stremmel W, et al. Prognostic aspects of 18F-FDG PET kinetics in patients with metastatic colorectal carcinoma receiving FOLFOX chemotherapy. J Nucl Med. 2004;45(9):1480–7.

    CAS  PubMed  Google Scholar 

  11. Ilan E, Sandstrom M, Velikyan I, Sundin A, Eriksson B, Lubberink M. Parametric Net Influx Rate images of 68Ga-DOTATOC and 68Ga-DOTATATE: quantitative accuracy and improved image contrast. J Nucl Med. 2017;58(5):744–9.

    Article  CAS  PubMed  Google Scholar 

  12. Pantel AR, Viswanath V, Muzi M, Doot RK, Mankoff DA. Principles of Tracer Kinetic Analysis in Oncology, Part I: principles and overview of Methodology. J Nucl Med. 2022;63(3):342–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Fujimura Y, Kimura Y, Simeon FG, Dickstein LP, Pike VW, Innis RB, et al. Biodistribution and Radiation Dosimetry in humans of a new PET Ligand, 18F-PBR06, to Image Translocator protein (18 kDa). J Nucl Med. 2010;51(1):145–9.

    Article  PubMed  Google Scholar 

  14. Mizrahi R, Rusjan PM, Vitcu I, Ng A, Wilson AA, Houle S, et al. Whole body biodistribution and radiation dosimetry in humans of a new PET ligand, [18F]-FEPPA, to image translocator protein (18 kDa). Mol Imaging Biol. 2013;15(3):353–9.

    Article  PubMed  Google Scholar 

  15. Zhu W, Li Q, Bai B, Conti PS, Leahy RM. Patlak image estimation from dual time-point list-mode PET data. IEEE Trans Med Imaging. 2014;33(4):913–24.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Karakatsanis NA, Casey ME, Lodge MA, Rahmim A, Zaidi H. Whole-body direct 4D parametric PET imaging employing nested generalized Patlak expectation-maximization reconstruction. Phys Med Biol. 2016;61(15):5456–85.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Strauss LG, Pan L, Cheng C, Haberkorn U, Dimitrakopoulou-Strauss A. Shortened acquisition protocols for the quantitative assessment of the 2-tissue-compartment model using dynamic PET/CT 18F-FDG studies. J Nucl Med. 2011;52(3):379–85.

    Article  PubMed  Google Scholar 

  18. Wu Y, Feng T, Zhao Y, Xu T, Fu F, Huang Z, et al. Whole-body Parametric Imaging of 18F-FDG PET using uEXPLORER with reduced scanning time. J Nucl Med. 2022;63(4):622–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Badawi RD, Shi H, Hu P, Chen S, Xu T, Price PM, et al. First Human Imaging Studies with the EXPLORER Total-Body PET scanner. J Nucl Med. 2019;60(3):299–303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Alberts I, Hunermund JN, Prenosil G, Mingels C, Bohn KP, Viscione M, et al. Clinical performance of long axial field of view PET/CT: a head-to-head intra-individual comparison of the Biograph Vision quadra with the Biograph Vision PET/CT. Eur J Nucl Med Mol Imaging. 2021;48(8):2395–404.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Liu G, Yu H, Shi D, Hu P, Hu Y, Tan H, et al. Short-time total-body dynamic PET imaging performance in quantifying the kinetic metrics of 18F-FDG in healthy volunteers. Eur J Nucl Med Mol Imaging. 2022;49(8):2493–503.

    Article  CAS  PubMed  Google Scholar 

  22. 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 

  23. Boudraa A, Zaidi H. Image segmentation techniques in nuclear medicine imaging. In: Zaidi H, editor. Quantitative analysis in Nuclear Medicine Imaging. New York: Springer; 2006. pp. 308–57.

    Chapter  Google Scholar 

  24. Foster B, Bagci U, Mansoor A, Xu Z, Mollura DJ. A review on segmentation of positron emission tomography images. Comput Biol Med. 2014;50:76–96.

    Article  PubMed  Google Scholar 

  25. Liu G, Xu H, Hu P, Tan H, Zhang Y, Yu H, et al. Kinetic metrics of 18F-FDG in normal human organs identified by systematic dynamic total-body positron emission tomography. Eur J Nucl Med Mol Imaging. 2021;48(8):2363–72.

    Article  CAS  PubMed  Google Scholar 

  26. Liu G, Hu P, Yu H, Tan H, Zhang Y, Yin H, et al. Ultra-low-activity total-body dynamic PET imaging allows equal performance to full-activity PET imaging for investigating kinetic metrics of 18F-FDG in healthy volunteers. Eur J Nucl Med Mol Imaging. 2021;48(8):2373–83.

    Article  PubMed  Google Scholar 

  27. Wahl LM, Asselin MC, Nahmias C. Regions of interest in the venous sinuses as input functions for quantitative PET. J Nucl Med. 1999;40(10):1666–75.

    CAS  PubMed  Google Scholar 

  28. Tseng J, Dunnwald LK, Schubert EK, Link JM, Minoshima S, Muzi M, et al. 18F-FDG kinetics in locally advanced Breast cancer: correlation with Tumor blood flow and changes in response to neoadjuvant chemotherapy. J Nucl Med. 2004;45(11):1829–37.

    CAS  PubMed  Google Scholar 

  29. Srinivas SM, Dhurairaj T, Basu S, Bural G, Surti S, Alavi A. A recovery coefficient method for partial volume correction of PET images. Ann Nucl Med. 2009;23(4):341–8.

    Article  PubMed  Google Scholar 

  30. Torizuka T, Nobezawa S, Momiki S, Kasamatsu N, Kanno T, Yoshikawa E, et al. Short dynamic FDG-PET imaging protocol for patients with Lung cancer. Eur J Nucl Med. 2000;27(10):1538–42.

    Article  CAS  PubMed  Google Scholar 

  31. Dimitrakopoulou-Strauss A, Strauss LG, Egerer G, Vasamiliette J, Schmitt T, Haberkorn U, et al. Prediction of chemotherapy outcome in patients with metastatic soft tissue sarcomas based on dynamic FDG PET (dPET) and a multiparameter analysis. Eur J Nucl Med Mol Imaging. 2010;37(8):1481–9.

    Article  CAS  PubMed  Google Scholar 

  32. Feng T, Zhao Y, Shi H, Li H, Zhang X, Wang G, et al. Total-body quantitative Parametric Imaging of Early Kinetics of 18F-FDG. J Nucl Med. 2021;62(5):738–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Wang Z, Wu Y, Li X, Bai Y, Chen H, Ding J, et al. Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging. EJNMMI Phys. 2022;9(1):63.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Wu Y, Feng T, Shen Y, Fu F, Meng N, Li X, et al. Total-body parametric imaging using the Patlak model: feasibility of reduced scan time. Med Phys. 2022;49(7):4529–39.

    Article  PubMed  Google Scholar 

  35. Sari H, Eriksson L, Mingels C, Alberts I, Casey ME, Afshar-Oromieh A, et al. Feasibility of using abbreviated scan protocols with population-based input functions for accurate kinetic modeling of [18F]-FDG datasets from a long axial FOV PET scanner. Eur J Nucl Med Mol Imaging. 2023;50(2):257–65.

    Article  CAS  PubMed  Google Scholar 

Download references

Funding

This study was funded by the Shanghai Municipal Key Clinical Specialty Project (grant number: SHSLCZDZK03401), the Major Science and Technology Projects for Major New Drug Creation (grant number: 2019ZX09302001), the Shanghai Science and Technology Committee program (grant number: 20DZ2201800), and the Three-year Action Plan of Clinical Skills and Innovation of Shanghai Hospital Development Center (grant number: SHDC2020CR3079B).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hongcheng Shi.

Ethics declarations

Conflict of interest

The authors declare that there is not any conflict of interest regarding this study.

Ethics approval

This study was approved by the Ethics Committee of Zhongshan Hospital of Fudan University (approval number: B2019-160).

Consent to participate

Written informed consents were obtained from included subjects for participation of this study.

Consent for publication

The authors affirm that human research participants provided informed consent for publication of the studied data.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Guobing Liu, Yimeng Shi and Xiaoguang Hou contributed equally to this article.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, G., Shi, Y., Hou, X. et al. Dynamic total-body PET/CT imaging with reduced acquisition time shows acceptable performance in quantification of [18F]FDG tumor kinetic metrics. Eur J Nucl Med Mol Imaging 51, 1371–1382 (2024). https://doi.org/10.1007/s00259-023-06526-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00259-023-06526-4

Keywords

Navigation