Evidence map›Paper›PMID 28324340›Full record

ArticleEJNMMI research2017

Quantitative

Joshua D Schaefferkoetter, Ziting Wang, Mary C Stephenson, Sharmili Roy, Maurizio Conti, Lars Eriksson, David W Townsend, Thomas Thamboo, Edmund Chiong

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in EJNMMI research, 2017. 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 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.9field-weighted citation impact, top 8% 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

13 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. International journal of molecular sciences · 2022
    Article
  3. The Role of [Cancers · 2021
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. European journal of nuclear medicine and molecular imaging · 2020
    Article
  9. Article
  10. Quantitative assessment of dynamicThe British journal of radiology · 2019
    Article
  11. Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2018
    Article
  12. Article
  13. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Joshua D SchaefferkoetterA*STAR-NUS Clinical Imaging Research Centre, Centre for Translational Medicine (MD6), 14 Medical Drive, #B1-01, Singapore, 117599, Singapore. dnrjds@nus.edu.sg.
Ziting WangDepartment of Urology, National University Health System, Singapore, Singapore.
Mary C StephensonA*STAR-NUS Clinical Imaging Research Centre, Centre for Translational Medicine (MD6), 14 Medical Drive, #B1-01, Singapore, 117599, Singapore.
Sharmili RoyA*STAR-NUS Clinical Imaging Research Centre, Centre for Translational Medicine (MD6), 14 Medical Drive, #B1-01, Singapore, 117599, Singapore.
Maurizio ContiSiemens Healthcare Molecular Imaging, Knoxville, TN, 37919, USA.
Lars ErikssonSiemens Healthcare Molecular Imaging, Knoxville, TN, 37919, USA.
David W TownsendA*STAR-NUS Clinical Imaging Research Centre, Centre for Translational Medicine (MD6), 14 Medical Drive, #B1-01, Singapore, 117599, Singapore.
Thomas ThambooDepartment of Pathology, National University Health System, Singapore, Singapore.
Edmund ChiongDepartment of Urology, National University Health System, Singapore, Singapore.
A*STAR-NUS Clinical Imaging Research Centre · SGNational University Health System · SGSiemens Healthcare (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe use of radiolabeled choline as a positron emission tomography (PET) agent for imaging primary tumors in the prostate has been evaluated extensively over the past two decades. There are, however, conflicting reports of its sensitivity and the relationship between choline PET imaging and disease staging is not fully understood. Moreover, relatively few studies have investigated the correlation between tracer uptake and histological tumor grade. This work quantified

resultsCholine activity curves in seven tumors, eight healthy prostate regions, and nine muscle regions were analyzed. Net tracer influx was generally higher in tumor relative to healthy prostate, with the values in the highest grade tumors markedly higher than those in lower grade tumors. Influx terms from Patlak and full compartmental modeling showed good correlation within individual tissue groups. Kinetic parameters calculated from the entire 60-min scan data were accurately reproduced from the first 30 min of acquired data (R

conclusionsStrong correlations were observed between K

Indexed as

CholineHistologyPETProstate cancerTracer kinetic modeling

Identifiers

PMID28324340
PMCPMC5360745
OpenAlexW4231101894

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.