Evidence map›Paper›PMID 35652274›Full record

ArticleVascular2023

Utility of 4D CT in endoleak characterization after advanced endovascular aortic repair.

Massimo Tarulli, Kong Teng Tan, Thomas Lindsay, Daniyal Nasir Mahmood, Sam Santiago, Arash Jaberi, Sebastian Mafeld

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Vascular, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
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.

Massimo TarulliUniversity Health Network and Mount Sinai Hospital, Medical Imaging, Toronto, ON, Canada.ORCID 0000-0002-8174-7047
Kong Teng TanUniversity Health Network and Mount Sinai Hospital, Medical Imaging, Toronto, ON, Canada.
Thomas LindsayUniversity Health Network and Mount Sinai Hospital, Medical Imaging, Toronto, ON, Canada.
Daniyal Nasir MahmoodQueen's University, Kingston, ON, Canada.
Sam SantiagoUniversity Health Network and Mount Sinai Hospital, Medical Imaging, Toronto, ON, Canada.
Arash JaberiUniversity Health Network and Mount Sinai Hospital, Medical Imaging, Toronto, ON, Canada.
Sebastian MafeldUniversity Health Network and Mount Sinai Hospital, Medical Imaging, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo assess the performance of dynamic or 4D CT in characterizing endoleaks in advanced endovascular aortic repair (branched and fenestrated) when other modalities fail to fully characterize the leak, most often conventional CTA.

methodsRetrospective review of 13 patients from 2008 to 2021 who underwent 16 4D CTs to characterize endoleaks in branched and fenestrated endovascular aortic repair (FB-EVAR). The 4D CTs were performed covering up to 16 cm of the

resultsOverall sensitivity in 16 scans for endoleak detection was 100%. There was a specificity of 87.5% for determining the type of endoleak (14/16). These results included two studies that were inconclusive and repeated due to technical difficulties. In patients where a specific subtype was not established, the leak was localized to the appropriate target vessel. Average dose for the 4D CT was 4724 mGy*cm (1108-11069), with the outlining higher dose scans secondary to higher iterations in those scans.

conclusions4D CT is a useful adjunctive tool in FB-EVAR surveillance with excellent sensitivity and specificity in characterizing endoleaks. This allows for accurate localization of leaks, which is critical for management planning.

Indexed as

EndoleakFour-Dimensional Computed TomographyEndovascular Aneurysm RepairHumans4D4D CTbranchedendoleakEndovascularfenestrated

Identifiers

PMID35652274
PMCPMC10666521

What OpenQuestion holds

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LicenceCC BY
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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.