Evidence map›Paper›PMID 39728220›Full record

ReviewJournal of imaging2024

Current Role of CT Pulmonary Angiography in Pulmonary Embolism: A State-of-the-Art Review.

Ignacio Diaz-Lorenzo, Alberto Alonso-Burgos, Alfonsa Friera Reyes, Ruben Eduardo Pacios Blanco, Maria Del Carmen de Benavides Bernaldo de Quiros, Guillermo Gallardo Madueño

Abstract readReview
In one paragraph

Review in Journal of imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
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  6. Review
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  14. The Role of Non-invasive Tests in Pulmonary Embolism.Interventional cardiology (London, England) · 2025
    Review
  15. 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

6 authors.

Ignacio Diaz-LorenzoRadiology Department, University Hospital La Princesa, Calle Diego de Leon n. 62, 28006 Madrid, Spain.ORCID 0000-0002-4895-9689
Alberto Alonso-BurgosRadiology Department, Clinica Universidad de Navarra, Calle Santa Marta n. 1, 28027 Madrid, Spain.
Alfonsa Friera ReyesRadiology Department, University Hospital La Princesa, Calle Diego de Leon n. 62, 28006 Madrid, Spain.
Ruben Eduardo Pacios BlancoRadiology Department, University Hospital La Princesa, Calle Diego de Leon n. 62, 28006 Madrid, Spain.ORCID 0000-0002-5861-6292
Maria Del Carmen de Benavides Bernaldo de QuirosRadiology Department, University Hospital La Princesa, Calle Diego de Leon n. 62, 28006 Madrid, Spain.
Guillermo Gallardo MadueñoRadiology Department, Clinica Universidad de Navarra, Calle Santa Marta n. 1, 28027 Madrid, Spain.ORCID 0000-0002-7502-3544

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study is to conduct a literature review on the current role of computed tomography pulmonary angiography (CTPA) in the diagnosis and prognosis of pulmonary embolism (PE). It addresses key topics such as the quantification of the thrombotic burden, its role as a predictor of mortality, new diagnostic techniques that are available, the possibility of analyzing the thrombus composition to differentiate its evolutionary stage, and the applicability of artificial intelligence (AI) in PE through CTPA. The only finding from CTPA that has been validated as a prognostic factor so far is the right ventricle/left ventricle (RV/LV) diameter ratio being >1, which is associated with a 2.5-fold higher risk of all-cause mortality or adverse events, and a 5-fold higher risk of PE-related mortality. The increasing use of techniques such as dual-energy computed tomography allows for the more accurate diagnosis of perfusion defects, which may go undetected in conventional computed tomography, identifying up to 92% of these defects compared to 78% being detected by CTPA. Additionally, it is essential to explore the latest advances in the application of AI to CTPA, which are currently expanding and have demonstrated a 23% improvement in the detection of subsegmental emboli compared to manual interpretation. With deep image analysis, up to a 95% accuracy has been achieved in predicting PE severity based on the thrombus volume and perfusion deficits. These advancements over the past 10 years significantly contribute to early intervention strategies and, therefore, to the improvement of morbidity and mortality outcomes for these patients.

Indexed as

artificial intelligence (AI)computed tomography pulmonary angiography (CTPA)dual-energy CT (DECT)pulmonary embolism (PE)risk stratificationthrombotic burden

Identifiers

PMID39728220
PMCPMC11678867

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.