Evidence map›Paper›PMID 32354378›Full record

ArticleComparative medicine2020

Assessment of Semi-automated Computed Tomographic Measures of Segmental Perfusion Defects in a Swine Model (

Bryan C Ramsey, Amy E Field, Dustin M Thomas, Christopher A Pickett, Alisa J Leon, Bernard J Rubal

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In one paragraph

Article in Comparative medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Bryan C RamseyCardiology Service, Brooke Army Medical Center, Fort Sam Houston, Texas.
Amy E FieldUS Army Institute of Surgical Research, Fort Sam Houston, Texas.
Dustin M ThomasCardiology Service, Brooke Army Medical Center, Fort Sam Houston, Texas.
Christopher A PickettCardiology Service, Brooke Army Medical Center, Fort Sam Houston, Texas.
Alisa J LeonUS Army Institute of Surgical Research, Fort Sam Houston, Texas.
Bernard J RubalCardiology Service, Brooke Army Medical Center, Fort Sam Houston, Texas;, Email: bernard.j.rubal.civ@mail.mil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computed tomographic myocardial perfusion (CTP) imaging is a tool that shows promise in emergent settings for defining the hemodynamic significance of coronary artery disease. In this study, we examined the accuracy with which the transmural perfusion ratio (TPR) derived through semiautomated CTP analysis reflected segmental perfusion defects associated with intermediate coronary artery lesions in swine. Lesions (diameter stenosis, 65% ± 11%) of the left anterior descending coronary artery (LAD) were created in 10 anesthetized female swine (weight, 47.5 ± 1.9 kg) by using a pneumatic occlusion device implanted on the LAD. Occluder inflation pressures were adjusted to maintain fractional flow reserve (FFR, 74.3 ± 1.7) during adenosine infusion (140ug/kg/min). Static CTP imaging using a stress-rest protocol and segmental TPR derived from semiautomated CT perfusion software was compared with microsphere-derived TPR (mTPR) by using a 16-segment model and polar mapping. Intermediate LAD stenosis was verified through multiplanar coronary CT angiography. Receiver operating characteristic analysis identified an optimal threshold for segmental perfusion defects for intermediate lesions (TPR threshold, ≤0.80); however, the area under the receiver operating characteristic curve was 0.58, and the overall accuracy was 63%. At this threshold, the sensitivity and specificity were 65% and 61%, and the positive and negative predictive values were 61% and 65%, respectively. Although CTP-TPR illustrated segmental perfusion defects with intermediate lesions, the disparity between CTP-TPR and mTPR measures of segmental perfusion suggests that further advances in analysis software may be necessary to improve the localization of segmental defects for intermediated lesions.

Indexed as

Fractional Flow Reserve, MyocardialAnimalsComputed Tomography AngiographyCoronary Artery DiseaseDisease Models, AnimalFemaleHumansImaging, Three-DimensionalMyocardial Perfusion ImagingPredictive Value of TestsSwine

Identifiers

PMID32354378
PMCPMC7287383

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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.