Evidence map›Paper›PMID 34550827›Full record

ArticleThe neuroradiology journal2022

Virtual monoenergetic dual-energy CT reconstructions at 80 keV are optimal non-contrast CT technique for early stroke detection.

Doris Dodig, Zrinka Matana Kaštelan, Nina Bartolović, Slaven Jurković, Damir Miletić, Zoran Rumboldt

Abstract read
In one paragraph

Article in The neuroradiology journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

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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

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Doris DodigRadiology Department, Clinical Hospital Centre Rijeka, Croatia.ORCID https://orcid.org/0000-0001-9462-4516
Zrinka Matana KaštelanRadiology Department, Clinical Hospital Centre Rijeka, Croatia.
Nina BartolovićRadiology Department, Clinical Hospital Centre Rijeka, Croatia.
Slaven JurkovićDepartment of Medical Physics and Biophysics, University of Rijeka, Croatia.
Damir MiletićRadiology Department, Clinical Hospital Centre Rijeka, Croatia.
Zoran RumboldtDepartment of Radiology, University of Rijeka, Croatia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVirtual monoenergetic (VM) dual-energy computed tomography (DE-CT) enables grey-to-white matter contrast-to-noise ratio optimization, potentially increasing ischaemic brain oedema visibility. The aim of this study was to compare the diagnostic accuracy of VM and standard DE-CT reconstructions for early stroke detection.

methodsConsecutive patients with non-contrast DE-CT of the brain scanned within 12 h of stroke symptom onset were prospectively included in the study. Patients with other significant brain pathology were excluded. Two radiologists jointly evaluated standard and VM reconstructions (from 40 to 190 keV at increments of 10 keV) for early stroke signs on a four-point Likert scale: (a) stroke definitely present, (b) stroke probably present, (c) probably no stroke, and (d) definitely no stroke. Follow-up imaging and clinical data served as the standard of reference. Diagnostic accuracy was evaluated by receiver operating characteristic analysis.

resultsStroke incidence among 184 patients was 76%. In 64 patients follow-up imaging served as the standard of reference: ischemic brain oedema detection was significantly more accurate on VM reconstructions at 80 keV compared with standard DE-CT reconstructions (area under the curve (AUC) = 0.821

conclusionVM DE-CT reconstructions at 80 keV appear to be the optimal non-contrast CT technique for diagnosing early ischaemic stroke, particularly within the first 3 h after symptom onset and in severely ill patients.

Indexed as

Brain EdemaBrain IschemiaRadiography, Dual-Energy Scanned ProjectionStrokeHumansRadiographic Image Interpretation, Computer-AssistedRetrospective StudiesTomography, X-Ray Computeddual energy CTStrokevirtual monoenergetic imaging

Identifiers

PMID34550827
PMCPMC9244738

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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.