Evidence map›Paper›PMID 29322068›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2018

Measuring temporal stability of positron emission tomography standardized uptake value bias using long-lived sources in a multicenter network.

Darrin Byrd, Rebecca Christopfel, Grae Arabasz, Ciprian Catana, Joel Karp, Martin A Lodge, Charles Laymon, Eduardo G Moros, Mikalai Budzevich, Sadek Nehmeh and 4 more

Erratum issuedOpen access · bronzeAbstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Measurement of PET Quantitative Bias In Vivo.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2021
    Article
  5. Article
  6. Prospective Study of SerialJournal of nuclear medicine : official publication, Society of Nuclear Medicine · 2018
    Article
  7. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 7 institutions in 1 country.

Darrin ByrdUniversity of Washington, Department of Radiology, Seattle, Washington, United States.
Rebecca ChristopfelUniversity of Washington, Department of Radiology, Seattle, Washington, United States.ORCID https://orcid.org/0000-0001-5653-6654
Grae ArabaszAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, United States.
Ciprian CatanaAthinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, United States.ORCID https://orcid.org/0000-0002-3249-5971
Joel KarpUniversity of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania, United States.
Martin A LodgeJohns Hopkins University, Department of Radiology and Radiological Science, Baltimore, Maryland, United States.
Charles LaymonUniversity of Pittsburgh, Presbyterian University Hospital, Department of Radiology, Pittsburgh, Pennsylvania, United States.
Eduardo G MorosMoffitt Cancer Center, Tampa, Florida, United States.
Mikalai BudzevichMoffitt Cancer Center, Tampa, Florida, United States.
Sadek NehmehWeill Cornell Medical College, Department of Radiology, New York, United States.
Joshua ScheuermannUniversity of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania, United States.
John SunderlandUniversity of Iowa, Department of Radiology, Iowa City, Iowa, United States.
Jun ZhangThe Ohio State University, Department of Radiology, Columbus, Ohio, United States.
Paul KinahanUniversity of Washington, Department of Radiology, Seattle, Washington, United States.ORCID https://orcid.org/0000-0001-6461-3306
Athinoula A. Martinos Center for Biomedical Imaging · USMoffitt Cancer Center · USUniversity of Washington · USCornell University · USJohns Hopkins University · USUniversity of Pennsylvania · USUniversity of Pittsburgh · US

Funding

Viral VectorP30CA086862 · NCI · UNIVERSITY OF IOWA · PI Douglas Robert Spitz · 2000 to 2026
$70.0M
Advanced PET/CT Imaging for Improving Clinical TrialsU01CA148131 · NCI · UNIVERSITY OF WASHINGTON · PI KINAHAN, PAUL E., LINDEN, HANNAH M · 2010 to 2019
$6.0M
MR-assisted PET data optimization for neuroimaging studiesR01EB014894 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI CATANA, CIPRIAN · 2013 to 2016
$2.6M
NCI NIH HHS U01 CA148131NIBIB NIH HHS R01 EB014894
6 · The paper itself

Abstract

Positron emission tomography (PET) is a quantitative imaging modality, but the computation of standardized uptake values (SUVs) requires several instruments to be correctly calibrated. Variability in the calibration process may lead to unreliable quantitation. Sealed source kits containing traceable amounts of [Formula: see text] were used to measure signal stability for 19 PET scanners at nine hospitals in the National Cancer Institute's Quantitative Imaging Network. Repeated measurements of the sources were performed on PET scanners and in dose calibrators. The measured scanner and dose calibrator signal biases were used to compute the bias in SUVs at multiple time points for each site over a 14-month period. Estimation of absolute SUV accuracy was confounded by bias from the solid phantoms' physical properties. On average, the intrascanner coefficient of variation for SUV measurements was 3.5%. Over the entire length of the study, single-scanner SUV values varied over a range of 11%. Dose calibrator bias was not correlated with scanner bias. Calibration factors from the image metadata were nearly as variable as scanner signal, and were correlated with signal for many scanners. SUVs often showed low intrascanner variability between successive measurements but were also prone to shifts in apparent bias, possibly in part due to scanner recalibrations that are part of regular scanner quality control. Biases of key factors in the computation of SUVs were not correlated and their temporal variations did not cancel out of the computation. Long-lived sources and image metadata may provide a check on the recalibration process.

Indexed as

calibrationclinical trialsquantitative positron emission tomography imagingstandardized uptake value

Identifiers

PMID29322068
PMCPMC5753626
OpenAlexW2782215450

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.