Skip to main content

Advertisement

Log in

The impact of iterative reconstruction protocol, signal-to-background ratio and background activity on measurement of PET spatial resolution

  • Original Article
  • Published:
Japanese Journal of Radiology Aims and scope Submit manuscript

Abstract

Objectives

The present study aims to assess the impact of acquisition time, different iterative reconstruction protocols as well as image context (including contrast levels and background activities) on the measured spatial resolution in PET images.

Methods

Discovery 690 PET/CT scanner was used to quantify spatial resolutions in terms of full width half maximum (FWHM) as derived (i) directly from capillary tubes embedded in air and (ii) indirectly from 10 mm-diameter sphere of the NEMA phantom. Different signal-to-background ratios (SBRs), background activity levels and acquisition times were applied. The emission data were reconstructed using iterative reconstruction protocols. Various combinations of iterations and subsets (it × sub) were evaluated.

Results

For capillary tubes, improved FWHM values were obtained for higher it × sub, with improved performance for PSF algorithms relative to non-PSF algorithms. For the NEMA phantom, by increasing acquisition times from 1 to 5 min, intrinsic FWHM for reconstructions with it × sub 32 (54) was improved by 15.3% (13.2%), 15.1% (13.8%), 14.5% (12.8%) and 13.7% (12.7%) for OSEM, OSEM + PSF, OSEM + TOF and OSEM + PSF + TOF, respectively. Furthermore, for all reconstruction protocols, the FWHM improved with more impact for higher it × sub.

Conclusion

Our results indicate that PET spatial resolution is greatly affected by SBR, background activity and the choice of the reconstruction protocols.

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

References

  1. Naqa IE. The role of quantitative PET in predicting cancer treatment outcomes. Clin Transl Imaging. 2014;2:305–20.

    Google Scholar 

  2. O JH, Jacene H, Luber B, Wang H, Huynh MH, Leal JP, et al. Quantitation of cancer treatment response by 18F-FDG PET/CT: multicenter assessment of measurement variability. J Nucl Med. 2017;58:1429–34.

    PubMed  PubMed Central  Google Scholar 

  3. Polycarpou I, Tsoumpas C, King AP, Marsden PK. Impact of respiratory motion correction and spatial resolution on lesion detection in PET: a simulation study based on real MR dynamic data. Phys Med Biol. 2014;59:697–713.

    PubMed  Google Scholar 

  4. National Electrical Manufacturers Association. Performance Measurements of Positron Emission Tomographs. NEMA Standards Publication NU 2-2012. Rosslyn: National Electrical Manufacturers Association; 2012. pp 9–11.

  5. DeGrado TR, Turkington TG, Williams JJ, Stearns CW, Hoffman JM, Coleman RE. Performance characteristics of a whole-body PET scanner. J Nucl Med. 1994;35:1398–406.

    PubMed  CAS  Google Scholar 

  6. Goertzen AL, Bao Q, Bergeron M, Blankemeyer E, Blinder S, Canadas M, et al. NEMA NU 4-2008 comparison of preclinical PET imaging systems. J Nucl Med. 2012;53:1300–9.

    PubMed  PubMed Central  Google Scholar 

  7. Tuna U, Peltonen S, Ruotsalainen U. Gap-filling for the high-resolution PET sinograms with a dedicated DCT-domain filter. IEEE Trans Med Imaging. 2010;29:830–9.

    PubMed  Google Scholar 

  8. Loukiala A, Tuna U, Beer S, Jahnke S, Ruotsalainen U. Gap-filling methods for 3D PlanTIS data. Phys Med Biol. 2010;55:6125–40.

    PubMed  CAS  Google Scholar 

  9. Iriarte A, Marabini R, Matej S, Sorzano CO, Lewitt RM. System models for PET statistical iterative reconstruction: a review. Comput Med Imaging Graph. 2016;48:30–48.

    PubMed  CAS  Google Scholar 

  10. Cheebsumon P, Yaqub M, van Velden FH, Hoekstra OS, Lammertsma AA, Boellaard R. Impact of [18F] FDG PET imaging parameters on automatic tumour delineation: need for improved tumour delineation methodology. Eur J Nucl Med Mol Imaging. 2011;38:2136–44.

    PubMed  PubMed Central  Google Scholar 

  11. Prieto E, Dominguez-Prado I, Velloso MJ, Penuelas I, Richter JA, Climent JM. Impact of time-of-flight and point-spread-function in SUV quantification for oncological PET. Clin Nucl Med. 2013;38:103–9.

    PubMed  Google Scholar 

  12. Matheoud R, Lecchi M, Lizio D, Scabbio C, Marcassa C, Leva L, et al. Comparative analysis of iterative reconstruction algorithms with resolution recovery and time of flight modeling for 18F-FDG cardiac PET: a multi-center phantom study. J Nucl Cardiol. 2017;24:1036–45.

    PubMed  Google Scholar 

  13. Sharifpour R, Ghafarian P, Rahmim A, Ay MR. Quantification and reduction of respiratory induced artifacts in positron emission tomography/computed tomography using the time-of-flight technique. Nucl Med Commun. 2017;38:948–55.

    PubMed  Google Scholar 

  14. Akamatsu G, Ishikawa K, Mitsumoto K, Taniguchi T, Ohya N, Baba S, et al. Improvement in PET/ct image quality with a combination of point-spread function and time-of-flight in relation to reconstruction parameters. J Nucl Med. 2012;53:1716–22.

    PubMed  Google Scholar 

  15. Rahmim A, Tang J. Noise propagation in resolution modeled PET imaging and its impact on detectability. Phys Med Biol. 2013;58:6945–68.

    PubMed  Google Scholar 

  16. Sharifpour R, Ghafarian P, Bakhshayesh-Karam M, Jamaati H, Ay MR. Impact of time-of-flight and point-spread-function for respiratory artifact reduction in PET/CT imaging: focus on SUV. Tanaffos. 2017;16:127–35.

    PubMed  PubMed Central  Google Scholar 

  17. Rogasch JM, Steffen IG, Hofheinz F, Furth C, Mohnike K, Hass P, et al. The association of tumor-to-background ratios and SUVmax deviations related to point spread function and time-of-flight 18F-FDG-PET/CT reconstruction in colorectal liver metastases. EJNMMI Res. 2015;5:31.

    PubMed  PubMed Central  Google Scholar 

  18. Andersen FL, Klausen TL, Loft A, Beyer T, Holm S. Clinical evaluation of PET image reconstruction using a spatial resolution model. Eur J Radiol. 2013;82:862–9.

    PubMed  Google Scholar 

  19. Vennart NJ, Bird N, Buscombe J, Cheow HK, Nowosinska E, Heard S. Optimization of PET/CT image quality using the GE “Sharp IR” point-spread function reconstruction algorithm. Nucl Med Commun. 2017;38:471–9.

    PubMed  Google Scholar 

  20. Knausl B, Rausch IF, Bergmann H, Dudczak R, Hirtl A, Georg D. Influence of PET reconstruction parameters on the TrueX algorithm. Nuklearmedizin. 2013;52:28–35.

    PubMed  CAS  Google Scholar 

  21. Armstrong IS, Kelly MD, Williams HA, Matthews JC. Impact of point spread function modelling and time of flight on FDG uptake measurements in lung lesions using alternative filtering strategies. EJNMMI Phys. 2014;1:99–117.

    PubMed  PubMed Central  Google Scholar 

  22. Soret M, Bacharach SL, Buvat I. Partial-volume effect in PET tumor imaging. J Nucl Med. 2007;48:932–45.

    PubMed  Google Scholar 

  23. Erlandsson K, Buvat I, Pretorius PH, Thomas BA, Hutton BF. A review of partial volume correction techniques for emission tomography and their applications in neurology, cardiology and oncology. Phys Med Biol. 2012;57:R119–159.

    PubMed  Google Scholar 

  24. Kadrmas DJ, Casey ME, Conti M, Jakoby BW, Lois C, Townsend DW. Impact of time-of-flight on PET tumor detection. J Nucl Med. 2009;50:1315–23.

    PubMed  PubMed Central  Google Scholar 

  25. Bettinardi V, Castiglioni I, De Bernardi E, Gilardi MC. PET quantification: strategies for partial volume correction. Clin Transl Imaging. 2014;2:199–21818.

    Google Scholar 

  26. Yan J, Shern JL, Loi HY, Khor LK, Sinha AK, Quek ST, et al. Impact of image reconstruction settings on texture features in 18F-FDG PET. J Nucl Med. 2015;56:1667–733.

    PubMed  CAS  Google Scholar 

  27. Kueng R, Driscoll B, Manser P, Fix MK, Stampanoni M, Keller H. Quantification of local image noise variation in PET images for standardization of noise-dependent analysis metrics. Biomed Phys Eng Express. 2017;3:025007.

    Google Scholar 

  28. Carlier T, Ferrer L, Necib H, Bodet-Milin C, Rousseau C, Kraeber-Bodéré F. Clinical NECR in 18F-FDG PET scans: optimization of injected activity and variable acquisition time. Relationship with SNR. Phys Med Biol. 2014;59:6417–30.

    PubMed  CAS  Google Scholar 

  29. Zeimpekis KG, Barbosa F, Hüllner M, ter Voert E, Davison H, Veit-Haibach P, et al. Clinical evaluation of PET Image quality as a function of acquisition time in a new TOF-PET/MRI compared to TOF-PET/CT-initial results. Mol Imaging Biol. 2015;17:735–44.

    PubMed  CAS  Google Scholar 

  30. Lütje S, Blex S, Gomez B, Schaarschmidt BM, Umutlu L, Forsting M, et al. Optimization of acquisition time of 68Ga-PSMA-ligand PET/MRI in patients with local and metastatic prostate cancer. PLoS ONE ONE. 2016;11:e0164392.

    Google Scholar 

  31. Umeda T, Miwa K, Murata T, Miyaji N, Wagatsuma K, Motegi K, et al. Optimization of a shorter variable-acquisition time for legs to achieve true whole-body PET/CT images. Australas Phys Eng Sci Med. 2017;40:861–8.

    PubMed  Google Scholar 

  32. Lodge MA, Leal JP, Rahmim A, Sunderland JJ, Frey EC. Measuring PET spatial resolution using a cylinder phantom positioned at an oblique angle. J Nucl Med. 2018;59:1768–75.

    PubMed  PubMed Central  CAS  Google Scholar 

  33. Hofheinz F, Dittrich S, Pötzsch C, van den Hoff J. Effects of cold sphere walls in PET phantom measurements on the volume reproducing threshold. Phys Med Biol. 2010;55:1099–113.

    PubMed  CAS  Google Scholar 

  34. Ketabi A, Ghafarian P, Mosleh-Shirazi MA, Mahdavi SR, Rahmim A, Ay MR. Impact of image reconstruction methods on quantitative accuracy and variability of FDG-PET volumetric and textural measures in solid tumors. Eur Radiol. 2019;29:2146–56.

    PubMed  Google Scholar 

  35. Ketabi A, Ghafarian P, Mosleh-Shirazi M, Mahdavi S, Ay M. The influence of using different reconstruction algorithms on sensitivity of quantitative 18F-FDG-PET volumetric measures to background activity variation. Iran J Nucl Med. 2018;26:87–97.

    CAS  Google Scholar 

  36. Suljic A, Tomse P, Jensterle L, Skrk D. The impact of reconstruction algorithms and time of flight information on PET/CT image quality. Radiol Oncol. 2015;49:227–33.

    PubMed  PubMed Central  CAS  Google Scholar 

  37. Taniguchi T, Akamatsu G, Kasahara Y, Mitsumoto K, Baba S, Tsutsui Y, et al. Improvement in PET/CT image quality in overweight patients with PSF and TOF. Ann Nucl Med. 2015;29:71–7.

    PubMed  Google Scholar 

  38. Gong K, Cherry SR, Qi J. On the assessment of spatial resolution of PET systems with iterative image reconstruction. Phys Med Biol. 2016;61:N193–N202.

    PubMed  PubMed Central  CAS  Google Scholar 

  39. Rahmim A, Qi J, Sossi V. Resolution modeling in PET imaging: theory, practice, benefits, and pitfalls. Med Phys. 2013;40:064301.

    PubMed  PubMed Central  Google Scholar 

  40. Lodge MA, Rahmim A, Wahl RL. Simultaneous measurement of noise and spatial resolution in PET phantom images. Phys Med Biol. 2010;55:1069–81.

    PubMed  PubMed Central  Google Scholar 

  41. Skretting A. A method for on-site measurements of the effective spatial resolution in PET image volumes reconstructed with OSEM and gaussian post-filters. Radiat Prot Dosimetry. 2010;139:195–8.

    PubMed  Google Scholar 

  42. Lodge MA, Rahmim A, Wahl RL. A practical, automated quality assurance method for measuring spatial resolution in PET. J Nucl Med. 2009;50:1307–14.

    PubMed  PubMed Central  Google Scholar 

  43. Yao R, Seidel J, Johnson CA, -Witherspoon ME, Green MV, Carson RE. Performance characteristics of the 3-D OSEM algorithm in the reconstruction of small animal PET images. Ordered-subsets expectation-maximization. IEEE Trans Med Imaging. 2000;19:798–804.

    PubMed  CAS  Google Scholar 

  44. Yang Y, Tai YC, Siegel S, Newport DF, Bai B, Li Q, et al. Optimization and performance evaluation of the microPET II scanner for in vivo small-animal imaging. Phys Med Biol. 2004;49:2527–46.

    PubMed  Google Scholar 

  45. Rogasch JMM, Hofheinz F, Lougovski A, Furth C, Ruf J, Großer OS, et al. The influence of different signal-to-background ratios on spatial resolution and 18F-FDG-PET quantification using point spread function and time-of-flight reconstruction. EJNMMI Phys. 2014;1:12.

    PubMed  PubMed Central  Google Scholar 

  46. Noto B, Büther F, Auf der Springe K, Avramovic N, Heindel W, Schafers M, et al. Impact of PET acquisition durations on image quality and lesion detectability in whole-body 68Ga-PSMA PET-MRI. EJNMMI Res 2017;7(1):12.

  47. Schaefferkoetter J, Casey M, Townsend D, Fakhri GE. Clinical impact of time-of-flight and point response modeling in PET reconstructions: a lesion detection study. Phys Med Biol. 2013;58:1465–78.

    PubMed  PubMed Central  Google Scholar 

  48. Akamatsu G, Mitsumoto K, Ishikawa K, Taniguchi T, Ohya N, Baba S, et al. Benefits of point-spread function and time of flight for PET/CT image quality in relation to the body mass index and injected dose. Clin Nucl Med. 2013;38:407–12.

    PubMed  Google Scholar 

  49. Bal H, Guerin L, Casey ME, Conti M, Eriksson L, Michel C, et al. Improving PET spatial resolution and detectability for prostate cancer imaging. Phys Med Biol. 2014;59:4411–26.

    PubMed  CAS  Google Scholar 

  50. Shekari M, Ghafarian P, Ahangari S, Ay MR. Quantification of the impact of TOF and PSF on PET images using the noise-matching concept: Clinical and phantom study. Nucl Sci Tech. 2017;28:167.

    Google Scholar 

Download references

Funding

This work was supported under grant number 33381, Tehran University of Medical Sciences, as well as Masih Daneshvari Hospital and Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pardis Ghafarian.

Ethics declarations

Conflicts of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

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

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rezaei, S., Ghafarian, P., Bakhshayesh-Karam, M. et al. The impact of iterative reconstruction protocol, signal-to-background ratio and background activity on measurement of PET spatial resolution. Jpn J Radiol 38, 231–239 (2020). https://doi.org/10.1007/s11604-019-00914-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11604-019-00914-3

Keywords

Navigation