Evidence map›Paper›PMID 35581304›Full record

ArticleScientific reports2022

Contrast timing optimization of a two-volume dynamic CT pulmonary perfusion technique.

Yixiao Zhao, Logan Hubbard, Shant Malkasian, Pablo Abbona, Sabee Molloi

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. A patient-specific timing protocol for improved CT pulmonary angiography.Research in diagnostic and interventional imaging · 2023
    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

5 authors.

Yixiao ZhaoDepartment of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA.
Logan HubbardDepartment of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA.
Shant MalkasianDepartment of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA.
Pablo AbbonaDepartment of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA.
Sabee MolloiDepartment of Radiological Sciences, Medical Sciences I, B-140, University of California, Irvine, Irvine, CA, 92697, USA. symolloi@uci.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study is to develop and validate an optimal timing protocol for a low-radiation-dose CT pulmonary perfusion technique using only two volume scans. A total of 24 swine (48.5 ± 14.3 kg) underwent contrast-enhanced dynamic CT. Multiple contrast injections were made under different pulmonary perfusion conditions, resulting in a total of 141 complete pulmonary arterial input functions (AIFs). Using all the AIF curves, an optimal contrast timing protocol was developed for a first-pass, two-volume dynamic CT perfusion technique (one at the base and the other at the peak of AIF curve). A subset of swine was used to validate the prospective two-volume pulmonary perfusion technique. The prospective two-volume perfusion measurements were quantitatively compared to the previously validated retrospective perfusion measurements with t-test, linear regression, and Bland-Altman analysis. As a result, the pulmonary artery time-to-peak ([Formula: see text]) was related to one-half of the contrast injection duration ([Formula: see text]) by [Formula: see text] (r = 0.95). The prospective two-volume perfusion measurements (P

Indexed as

Myocardial Perfusion ImagingAnimalsCone-Beam Computed TomographyContrast MediaPerfusionProspective StudiesRetrospective StudiesSwineTomography, X-Ray ComputedContrast Media

Identifiers

PMID35581304
PMCPMC9114423

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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.