CoChat
Sign Up
Cited by 79Medical Imaging Techniques and ApplicationsLung Cancer Diagnosis and TreatmentRadiation Dose and Imaging

Quantitative implications of the updated EARL 2019 PET–CT performance standards

Open access
Kaalep, Andres, Burggraaff, Coreline N., Pieplenbosch, Simone, Verwer, Eline E., Sera, Terez, Zijlstra, Josee, Hoekstra, Otto S., Oprea-Lager, Daniela E. +1 more·2019·EJNMMI Physics
DOI 10.1186/s40658-019-0257-8PMC PMC6933045
Open this paper in CoChat — free accountOpen PDF

Abstract

PURPOSE: Recently, updated EARL specifications (EARL2) have been developed and announced. This study aims at investigating the impact of the EARL2 specifications on the quantitative reads of clinical PET-CT studies and testing a method to enable the use of the EARL2 standards whilst still generating quantitative reads compliant with current EARL standards (EARL1). METHODS: Thirteen non-small cell lung cancer (NSCLC) and seventeen lymphoma PET-CT studies were used to derive four image datasets-the first dataset complying with EARL1 specifications and the second reconstructed using parameters as described in EARL2. For the third (EARL2F6) and fourth (EARL2F7) dataset in EARL2, respectively, 6 mm and 7 mm Gaussian post-filtering was applied. We compared the results of quantitative metrics (MATV, SUVmax, SUVpeak, SUVmean, TLG, and tumor-to-liver and tumor-to-blood pool ratios) obtained with these 4 datasets in 55 suspected malignant lesions using three commonly used segmentation/volume of interest (VOI) methods (MAX41, A50P, SUV4). RESULTS: We found that with EARL2 MAX41 VOI method, MATV decreases by 22%, TLG remains unchanged and SUV values increase by 23-30% depending on the specific metric used. The EARL2F7 dataset produced quantitative metrics best aligning with EARL1, with no significant differences between most of the datasets (p>0.05). Different VOI methods performed similarly with regard to SUV metrics but differences in MATV as well as TLG were observed. No significant difference between NSCLC and lymphoma cancer types was observed. CONCLUSIONS: Application of EARL2 standards can result in higher SUVs, reduced MATV and slightly changed TLG values relative to EARL1. Applying a Gaussian filter to PET images reconstructed using EARL2 parameters successfully yielded EARL1 compliant data.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s40658-019-0257-8

Cites

33 of 33 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Kaalep et al. showed that filtering PSF-reconstructed data compliant with the updated EARL2 standard achieved SUV and metabolic tumor volumes (MTV) in lung cancer and lymphoma lesions similar to non-PSF data (EARL1-compliant).

    “Kaalep et al. showed that by filtering PSF-reconstructed data that were compliant with the updated EARL2 standard, SUV and metabolic tumor volumes (MTV) in lung cancer and lymphoma lesions could be achieved that were similar to non-PSF data (EARL1-compliant) [102].”

    From Influences on PET Quantification and Interpretation (2022) · cites this paper as [102]

  • 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 [102]

  • 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 [102]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

2 of the 35 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. [28]Boellaard R. Quantitative oncology molecular analysis suite: ACCURATE. J. Nucl. Med. [Internet]. 2018;59:1753. Available from: http://jnm.snmjournals.org/content/59/supplement_1/1753.abstract

Cited by

Sorted by citations

Related

Authors
Kaalep, A., Burggraaff, C. N., Pieplenbosch, S., Verwer, E. E., Sera, T., Zijlstra, J., Hoekstra, O. S., Oprea-Lager, D. E., & Boellaard, R.
Affiliations
  • North Estonia Medical Centre (EE)
  • Amsterdam University Medical Centers (NL)
  • University Medical Center Groningen (NL)
Corresponding author
  • Kaalep, Andres
  • Boellaard, Ronald
ORCID
Venue
EJNMMI Physics
Publisher
Springer Science and Business Media LLC
Published
2019-12
Volume
6
Issue
1
Pages
28-28
ISSN
2197-7364 (ISSN-L)
DOI
10.1186/s40658-019-0257-8
PMC
PMC6933045
OpenAlex
W2997842132
Cited by
79
References
35
Citations by year
2026: 12 · 2025: 11 · 2024: 6 · 2023: 11 · 2022: 20 · 2021: 14 · 2020: 4 · 2012: 1
FWCI
6.28
Type
journal article
Language
en
Open access
Licence
Locations
  • EJNMMI Physics (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
  • SZTE Publicatio Repozitórium (University of Szeged) (acceptedVersion, other-oa)
  • Pure Amsterdam UMC (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiation Dose and Imaging
Keywords
standardized uptake value, total lesion glycolysis, non-small cell lung cancer, lymphoma, tumor-to-liver ratio

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review