Evidence map›Paper›PMID 41059149›Full record

ArticleRadiology advances2024

Incidental pulmonary embolism in abdominal CT: detection rate and characteristics with artificial intelligence.

Peder Wiklund, Koshiar Medson

Abstract read
In one paragraph

Article in Radiology advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

2 authors.

Peder WiklundDepartment of Radiology, Region Halland, Halmstad, 30233, Sweden.ORCID https://orcid.org/0000-0002-4437-5686
Koshiar MedsonDepartment of Radiology and Functional Imaging, Karolinska University Hospital, Stockholm, 17164, Sweden.ORCID https://orcid.org/0000-0002-9209-7801

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Abdominal CT is a mainstay in the evaluation of abdominal infections, trauma, oncology, and postoperative complications. Pulmonary embolism is a common complication, but there is a risk that these ancillary findings are overlooked. In addition, data on detection rate and characteristics of incidental pulmonary embolism (iPE) on abdominal CT are lacking. Purpose: The current study compared the period before and after implementing an artificial intelligence (AI) algorithm for iPE detection regarding detection rate and characteristics. Material and Methods: A retrospective cross-sectional study was performed on abdominal CTs between August 1, 2019, and January 31, 2021 (before AI implementation, 8026 studies) and August 1, 2021, and January 31, 2023 (after AI implementation, 8765 studies). iPE cases were identified through text search and manually confirmed. Study indication and urgency were recorded for iPE patients, and the most proximal iPE level was assessed. A total of 1000 cases after AI implementation were randomly selected and manually reviewed for AI accuracy analysis. Results: A total of 5876 patients with a mean age of 63.6 ± 17.7 years were included before AI implementation, and 6310 patients with a mean age of 63.2 ± 18.3 years after AI implementation. The iPE detection rate was higher after AI implementation, 0.57% (50/8765 studies) vs 0.12% (10/8026), Conclusion: Implementing AI for iPE detection and triage increased the iPE detection rate in abdominal CT. The AI sensitivity was moderate, with very few AI false positives.

Indexed as

abdomenartificial intelligencemultidetector computed tomographypulmonary embolismretrospective studies

Identifiers

PMID41059149
PMCPMC12429247

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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.