Evidence map›Paper›PMID 32844310›Full record

ArticleEJNMMI physics2020

Vishnu Murthy, Raven L Smith, Dora H Tao, Courtney A Lawhn-Heath, Dave E Korenchan, Peder E Z Larson, Robert R Flavell, Thomas A Hope

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in EJNMMI physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Theranostics · 2020
    Review
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

8 authors.

Vishnu MurthyDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
Raven L SmithDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
Dora H TaoDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
Courtney A Lawhn-HeathDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
Dave E KorenchanDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
Peder E Z LarsonDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
Robert R FlavellDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
Thomas A HopeDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA. thomas.hope@ucsf.edu.ORCID http://orcid.org/0000-0002-2228-5823

Funding

Qualification and Harmonization of PET/MRI for Cancer Clinical TrialsR01CA212148 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HOPE, THOMAS, LAFOREST, RICHARD ANDRE · 2017 to 2022
$2.7M
NCI NIH HHS R01 CA212148NCI NIH HHS R01CA212148
6 · The paper itself

Abstract

backgroundIn this study, we investigate the impact of increased PET acquisition time per bed position on lesion detectability, standard uptake value, and image noise in

methodsScans of twenty patients were analyzed in this study. Patients were injected with

resultsA total of 55 lesions were identified, and lesion detectability increased from 2.07 ± 1.14 for 0.5 min to 4.93 ± 0.26 for 10 min (p < 0.001), with no significant difference detected between 7 and 10 min of scan time. Average SUV

conclusionsIncreased acquisition duration improves image quality by increasing detectability and reducing noise. In patients with biochemical recurrence, increased acquisition time up to 7 min improves lesion detection.

Identifiers

PMID32844310
PMCPMC7447708

What OpenQuestion holds

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Registered trials

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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.