Annals of Nuclear Medicine

, Volume 31, Issue 2, pp 125–134 | Cite as

Generating harmonized SUV within the EANM EARL accreditation program: software approach versus EARL-compliant reconstruction

  • Charline Lasnon
  • Thibault Salomon
  • Cédric Desmonts
  • Pascal Dô
  • Youssef Oulkhouir
  • Jeannick Madelaine
  • Nicolas AideEmail author
Original Article



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.


Positron 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


Ethics approval

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).

Supplementary material

12149_2016_1135_MOESM1_ESM.tiff (7.4 mb)
Supplemental figure 1: Effect of harmonization strategies on the liver background. For left to right, PSF and OSEM3D values, PSF7 and OSEM3D values and PSFEQ and OSEM3D values were compared using Bland-Altman plots. Upper panel (a) displays SUVmean values and lower panel (b) SUVpeak values (TIFF 7542 kb)


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Copyright information

© The Japanese Society of Nuclear Medicine 2016

Authors and Affiliations

  • Charline Lasnon
    • 1
    • 2
    • 3
  • Thibault Salomon
    • 1
  • Cédric Desmonts
    • 1
  • Pascal Dô
    • 4
  • Youssef Oulkhouir
    • 5
  • Jeannick Madelaine
    • 5
  • Nicolas Aide
    • 1
    • 2
    • 3
    Email author
  1. 1.Nuclear Medicine DepartmentCaen University HospitalCaenFrance
  2. 2.INSERM 1199, François Baclesse Cancer CentreCaenFrance
  3. 3.Normandie UniversityCaenFrance
  4. 4.Thoracic OncologyFrançois Baclesse Cancer CentreCaenFrance
  5. 5.Pulmonology DepartmentCaen University HospitalCaenFrance

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