Evidence map›Paper›PMID 24772207›Full record

ArticleTranslational oncology2014

Biases in Multicenter Longitudinal PET Standardized Uptake Value Measurements.

Robert K Doot, Larry A Pierce, Darrin Byrd, Brian Elston, Keith C Allberg, Paul E Kinahan

Abstract read
In one paragraph

Article in Translational oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

  1. Article
  2. Hot spot imaging in cardiovascular diseases: an information statement from SNMMI, ASNC, and EANM.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023
    Article
  3. Shortened duration whole bodyEJNMMI physics · 2022
    Article
  4. Article
  5. Article
  6. Article
  7. Test-Retest Reproducibility ofJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2019
    Article
  8. Article
  9. Feasibility of state of the art PET/CT systems performance harmonisation.European journal of nuclear medicine and molecular imaging · 2018
    Article
  10. Two determinations of the Ge-68 half-life.Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine · 2018
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Qualification of National Cancer Institute-Designated Cancer Centers for Quantitative PET/CT Imaging in Clinical Trials.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2017
    Review
  16. Article
  17. Evaluation of Cross-CalibratedTomography (Ann Arbor, Mich.) · 2016
    Article
  18. Long-term stability of carrier-added (68)Ge standardized solutions.Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine · 2016
    Article
  19. Quantitative Imaging in Cancer Clinical Trials.Clinical cancer research : an official journal of the American Association for Cancer Research · 2016
    Review
  20. Multimodality molecular imaging of the lung.Clinical and translational imaging · 2014
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Robert K DootDepartment of Radiology, University of Pennsylvania, Philadelphia, PA.
Larry A PierceDepartment of Radiology, University of Washington, Seattle, WA.
Darrin ByrdDepartment of Radiology, University of Washington, Seattle, WA.
Brian ElstonDepartment of Radiology, University of Washington, Seattle, WA.
Keith C AllbergRadQual, LLC, Weare, NH.
Paul E KinahanDepartment of Radiology, University of Washington, Seattle, WA.

Funding

Advanced PET/CT Imaging for Improving Clinical TrialsU01CA148131 · NCI · UNIVERSITY OF WASHINGTON · PI KINAHAN, PAUL E., LINDEN, HANNAH M · 2010 to 2019
$6.0M
NCI NIH HHS U01 CA148131
6 · The paper itself

Abstract

This study investigates measurement biases in longitudinal positron-emission tomography/computed tomography (PET/CT) studies that are due to instrumentation variability including human error. Improved estimation of variability between patient scans is of particular importance for assessing response to therapy and multicenter trials. We used National Institute of Standards and Technology-traceable calibration methodology for solid germanium-68/gallium-68 ((68)Ge/(68)Ga) sources used as surrogates for fluorine-18 ((18)F) in radionuclide activity calibrators. One cross-calibration kit was constructed for both dose calibrators and PET scanners using the same 9-month half-life batch of (68)Ge/(68)Ga in epoxy. Repeat measurements occurred in a local network of PET imaging sites to assess standardized uptake value (SUV) errors over time for six dose calibrators from two major manufacturers and for six PET/CT scanners from three major manufacturers. Bias in activity measures by dose calibrators ranged from -50% to 9% and was relatively stable over time except at one site that modified settings between measurements. Bias in activity concentration measures by PET scanners ranged from -27% to 13% with a median of 174 days between the six repeat scans (range, 29 to 226 days). Corresponding errors in SUV measurements ranged from -20% to 47%. SUV biases were not stable over time with longitudinal differences for individual scanners ranging from -11% to 59%. Bias in SUV measurements varied over time and between scanner sites. These results suggest that attention should be paid to PET scanner calibration for longitudinal studies and use of dose calibrator and scanner cross-calibration kits could be helpful for quality assurance and control.

Identifiers

PMID24772207
PMCPMC3998681

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.