Cited by 107Medical Imaging Techniques and ApplicationsCardiac Imaging and DiagnosticsLung Cancer Diagnosis and Treatment

Harmonizing FDG PET quantification while maintaining optimal lesion detection: prospective multicentre validation in 517 oncology patients

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Quak, Elske, Le Roux, Pierre-Yves, Hofman, Michael S., Robin, Philippe, Bourhis, David, Callahan, Jason, Binns, David, Desmonts, Cédric +3 more·2015·European Journal of Nuclear Medicine and Molecular Imaging

Abstract

PURPOSE: Point-spread function (PSF) or PSF + time-of-flight (TOF) reconstruction may improve lesion detection in oncologic PET, but can alter quantitation resulting in variable standardized uptake values (SUVs) between different PET systems. This study aims to validate a proprietary software tool (EQ.PET) to harmonize SUVs across different PET systems independent of the reconstruction algorithm used. METHODS: NEMA NU2 phantom data were used to calculate the appropriate filter for each PSF or PSF+TOF reconstruction from three different PET systems, in order to obtain EANM compliant recovery coefficients. PET data from 517 oncology patients were reconstructed with a PSF or PSF+TOF reconstruction for optimal tumour detection and an ordered subset expectation maximization (OSEM3D) reconstruction known to fulfil EANM guidelines. Post-reconstruction, the proprietary filter was applied to the PSF or PSF+TOF data (PSFEQ or PSF+TOFEQ). SUVs for PSF or PSF+TOF and PSFEQ or PSF+TOFEQ were compared to SUVs for the OSEM3D reconstruction. The impact of potential confounders on the EQ.PET methodology including lesion and patient characteristics was studied, as was the adherence to imaging guidelines. RESULTS: For the 1380 tumour lesions studied, Bland-Altman analysis showed a mean ratio between PSF or PSF+TOF and OSEM3D of 1.46 (95%CI: 0.86-2.06) and 1.23 (95%CI: 0.95-1.51) for SUVmax and SUVpeak, respectively. Application of the proprietary filter improved these ratios to 1.02 (95%CI: 0.88-1.16) and 1.04 (95%CI: 0.92-1.17) for SUVmax and SUVpeak, respectively. The influence of the different confounding factors studied (lesion size, location, radial offset and patient's BMI) was less than 5%. Adherence to the European Association of Nuclear Medicine (EANM) guidelines for tumour imaging was good. CONCLUSION: These data indicate that it is not necessary to sacrifice the superior lesion detection and image quality achieved by newer reconstruction techniques in the quest for harmonizing quantitative comparability between PET systems.

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  • Compared with non-PSF reconstructed images, PSF can increase lesion SUVmax, SUVmean and SUVpeak by up to 30% on average.

    “Compared with non-PSF reconstructed images, this can increase lesion SUVmax, SUVmean and SUVpeak by up to 30% on average [100,101,102].”

    From Influences on PET Quantification and Interpretation (2022) · cites this paper as [100]

    The Results (Patient studies; page unavailable) show that PSF reconstruction increased lesion SUVmax and SUVpeak relative to conventional OSEM, but the reported mean increases varied by centre: SUVmax reached 57%, while SUVpeak reached 28%. The cited passage does not establish an increase of up to 30% on average for lesion SUVmean, so the three-metric claim is not fully supported. (LLM, conf=0.89)

    Experimental — accuracy not yet measured
  • With appropriate filter width based on sphere CR from standardized phantom measurements, PSF-induced SUV increases can be negated, resulting in comparable lesion SUVs to non-PSF data.

    “With appropriate filter width (FWHM) based on sphere CR from standardized phantom measurements, PSF-induced SUV increases can be negated, resulting in comparable lesion SUVs to those in non-PSF data.”

    From Influences on PET Quantification and Interpretation (2022) · cites this paper as [100]

  • PSF reconstruction improves reconstructed spatial resolution and increases lesion SUV but can lead to overestimation of true activity due to Gibbs' artifacts.

    “This improves reconstructed spatial resolution [97,98] and increases lesion SUV [99,100] but can lead to overestimation of the true activity due to so-called Gibbs’ artifacts [92,93].”

    From Influences on PET Quantification and Interpretation (2022) · cites this paper as [100]

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Authors
Quak, E., Le Roux, P.-Y., Hofman, M. S., Robin, P., Bourhis, D., Callahan, J., Binns, D., Desmonts, C., Salaun, P.-Y., Hicks, R. J., & Aide, N.
Affiliations
  • Centre François Baclesse (FR)
  • The University of Melbourne (AU)
  • Centre Hospitalier Régional Universitaire de Brest (FR)
  • Centre Hospitalier Universitaire de Caen Normandie (FR)
  • Inserm (FR)
Corresponding author
Aide, Nicolas
Venue
European Journal of Nuclear Medicine and Molecular Imaging
Published
2015-07-30
Volume
42
Issue
13
Pages
2072-2082
ISSN
  • 1619-7070 (ISSN-L)
  • 1619-7089
OpenAlex
W941202616
Cited by
107
References
33
Citations by year
2026: 2 · 2025: 4 · 2024: 7 · 2023: 6 · 2022: 12 · 2021: 16 · 2020: 8 · 2019: 9 · 2018: 12 · 2017: 16 · 2016: 11 · 2015: 4
FWCI
11.62
Type
journal article
Language
en
Open access
Locations
  • European Journal of Nuclear Medicine and Molecular Imaging (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • HAL (submittedVersion)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
Keywords
point spread function reconstruction, time-of-flight PET, SUVmax, SUVpeak, EANM guidelines, standardized uptake value, multicentre validation
MeSH terms
Aged, Carcinoma, Non-Small-Cell Lung, Female, Humans, Image Processing, Computer-Assisted, Liver Neoplasms, Lymphoma, Non-Hodgkin, Male, Melanoma, Middle Aged, Radiopharmaceuticals, Fluorodeoxyglucose F18, Positron-Emission Tomography

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