Evidence map›Paper›PMID 29059038›Full record

ArticleRadiology2018

Comprehensive Assessment of Coronary Artery Disease by Using First-Pass Analysis Dynamic CT Perfusion: Validation in a Swine Model.

Logan Hubbard, Jerry Lipinski, Benjamin Ziemer, Shant Malkasian, Bahman Sadeghi, Hanna Javan, Elliott M Groves, Brian Dertli, Sabee Molloi

Abstract read
In one paragraph

Article in Radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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  18. Imaging of coronary flow capacity: is there a role for dynamic CT perfusion imaging?European journal of nuclear medicine and molecular imaging · 2019
    Article
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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

9 authors.

Logan HubbardFrom the Department of Radiological Sciences (L.H., J.L., B.Z., S. Malkasian, B.S., H.J., B.D., S. Molloi) and Division of Cardiology (E.M.G.), University of California, Irvine, Medical Sciences I, B-140, Irvine, CA 92697.
Jerry LipinskiFrom the Department of Radiological Sciences (L.H., J.L., B.Z., S. Malkasian, B.S., H.J., B.D., S. Molloi) and Division of Cardiology (E.M.G.), University of California, Irvine, Medical Sciences I, B-140, Irvine, CA 92697.
Benjamin ZiemerFrom the Department of Radiological Sciences (L.H., J.L., B.Z., S. Malkasian, B.S., H.J., B.D., S. Molloi) and Division of Cardiology (E.M.G.), University of California, Irvine, Medical Sciences I, B-140, Irvine, CA 92697.ORCID 0000-0003-0489-5238
Shant MalkasianFrom the Department of Radiological Sciences (L.H., J.L., B.Z., S. Malkasian, B.S., H.J., B.D., S. Molloi) and Division of Cardiology (E.M.G.), University of California, Irvine, Medical Sciences I, B-140, Irvine, CA 92697.
Bahman SadeghiFrom the Department of Radiological Sciences (L.H., J.L., B.Z., S. Malkasian, B.S., H.J., B.D., S. Molloi) and Division of Cardiology (E.M.G.), University of California, Irvine, Medical Sciences I, B-140, Irvine, CA 92697.
Hanna JavanFrom the Department of Radiological Sciences (L.H., J.L., B.Z., S. Malkasian, B.S., H.J., B.D., S. Molloi) and Division of Cardiology (E.M.G.), University of California, Irvine, Medical Sciences I, B-140, Irvine, CA 92697.
Elliott M GrovesFrom the Department of Radiological Sciences (L.H., J.L., B.Z., S. Malkasian, B.S., H.J., B.D., S. Molloi) and Division of Cardiology (E.M.G.), University of California, Irvine, Medical Sciences I, B-140, Irvine, CA 92697.
Brian DertliFrom the Department of Radiological Sciences (L.H., J.L., B.Z., S. Malkasian, B.S., H.J., B.D., S. Molloi) and Division of Cardiology (E.M.G.), University of California, Irvine, Medical Sciences I, B-140, Irvine, CA 92697.
Sabee MolloiFrom the Department of Radiological Sciences (L.H., J.L., B.Z., S. Malkasian, B.S., H.J., B.D., S. Molloi) and Division of Cardiology (E.M.G.), University of California, Irvine, Medical Sciences I, B-140, Irvine, CA 92697.

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM008620 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI GOLDIN, ALAN L · 1999 to 2023
$8.1M
Training Program in Cardiovascular Applied Research and EntrepreneurshipT32HL116270 · NHLBI · UNIVERSITY OF CALIFORNIA-IRVINE · PI HUGHES, CHRISTOPHER C. W. · 2013 to 2022
$1.6M
NHLBI NIH HHS T32 HL116270NIGMS NIH HHS T32 GM008620
6 · The paper itself

Abstract

Purpose To retrospectively validate a first-pass analysis (FPA) technique that combines computed tomographic (CT) angiography and dynamic CT perfusion measurement into one low-dose examination. Materials and Methods The study was approved by the animal care committee. The FPA technique was retrospectively validated in six swine (mean weight, 37.3 kg ± 7.5 [standard deviation]) between April 2015 and October 2016. Four to five intermediate-severity stenoses were generated in the left anterior descending artery (LAD), and 20 contrast material-enhanced volume scans were acquired per stenosis. All volume scans were used for maximum slope model (MSM) perfusion measurement, but only two volume scans were used for FPA perfusion measurement. Perfusion measurements in the LAD, left circumflex artery (LCx), right coronary artery, and all three coronary arteries combined were compared with microsphere perfusion measurements by using regression, root-mean-square error, root-mean-square deviation, Lin concordance correlation, and diagnostic outcomes analysis. The CT dose index and size-specific dose estimate per two-volume FPA perfusion measurement were also determined. Results FPA and MSM perfusion measurements (P

Indexed as

AnimalsArea Under CurveBlood PressureCoronary Artery DiseaseDisease Models, AnimalHeart RateImage Interpretation, Computer-AssistedMyocardial Perfusion ImagingReproducibility of ResultsSwineTomography, X-Ray Computed

Identifiers

PMID29059038
PMCPMC5749593

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.