Evidence map›Paper›PMID 33444284›Full record

ArticleBiomedical physics & engineering express2020

Characterization and comparison of imaging contrast enhancement with PEG-functionalized gold nanoparticles in kV cone beam computed tomography and computed tomography imaging.

Tara Gray, Nema Bassiri, Shaquan David, Devanshi Yogeshkumar Patel, Mohammad Abdul-Moqueet, Neil Kirby, Kathryn M Mayer

Abstract read
In one paragraph

Article in Biomedical physics & engineering express, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Tara GrayThe University of Texas at San Antonio, Department of Physics and Astronomy, San Antonio, TX 78249, United States of America.
Nema BassiriThe University of Texas Health Science Center at San Antonio, Department of Radiation Oncology, San Antonio, TX 78229, United States of America.
Shaquan DavidThe University of Texas at San Antonio, Department of Physics and Astronomy, San Antonio, TX 78249, United States of America.
Devanshi Yogeshkumar PatelThe University of Texas at San Antonio, Department of Physics and Astronomy, San Antonio, TX 78249, United States of America.
Mohammad Abdul-MoqueetThe University of Texas at San Antonio, Department of Physics and Astronomy, San Antonio, TX 78249, United States of America.
Neil KirbyThe University of Texas Health Science Center at San Antonio, Department of Radiation Oncology, San Antonio, TX 78229, United States of America.
Kathryn M MayerThe University of Texas at San Antonio, Department of Physics and Astronomy, San Antonio, TX 78249, United States of America.ORCID 0000-0002-9533-8527

Funding

UTSA RISE Research Training ProgramR25GM060655 · NIGMS · UNIVERSITY OF TEXAS SAN ANTONIO · PI BAREA-RODRIGUEZ, EDWIN J · 2000 to 2022
$21.6M
NIGMS NIH HHS R25 GM060655
6 · The paper itself

Abstract

The purpose of this study is to define a simplified method to accurately predict and characterize kV cone beam computed tomography (kV CBCT) and computed tomography (CT) image contrast enhancement from gold nanoparticles (GNPs). Parameters of the kV CBCT of a Varian Novalis Tx linear accelerator and of a GE LightSpeed 4 Big Bore CT machine were modeled using the MCNP 6.2 Monte Carlo code. A 0.25 × 0.25 cm

Indexed as

AlgorithmsAnimalsCell LineComputer SimulationCone-Beam Computed TomographyContrast MediaGoldHumansImage Processing, Computer-AssistedMetal NanoparticlesMiceMonte Carlo MethodParticle AcceleratorsPhantoms, ImagingPolyethylene GlycolsRadiation DosageContrast MediaGoldPolyethylene Glycols

Identifiers

PMID33444284
PMCPMC7927153

What OpenQuestion holds

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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.