Evidence map›Paper›PMID 40059896›Full record

ReviewWorld journal of clinical pediatrics2025

Role of photon-counting computed tomography in pediatric cardiovascular imaging.

Arosh S Perera Molligoda Arachchige, Yash Verma

Abstract readReview
In one paragraph

Review in World journal of clinical pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Imaging of pediatric pulmonary infections: A pictorial review.World journal of clinical pediatrics · 2026
    Review
  3. Review
  4. 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.

Arosh S Perera Molligoda ArachchigeFaculty of Medicine, Humanitas University, Pieve Emanuele 20072, Italy.
Yash VermaDepartment of Radiology, Mayo Clinic, Rochester, MN 55905, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Photon-counting computed tomography (PCCT) represents a significant advancement in pediatric cardiovascular imaging. Traditional CT systems employ energy-integrating detectors that convert X-ray photons into visible light, whereas PCCT utilizes photon-counting detectors that directly transform X-ray photons into electric signals. This direct conversion allows photon-counting detectors to sort photons into discrete energy levels, thereby enhancing image quality through superior noise reduction, improved spatial and contrast resolution, and reduced artifacts. In pediatric applications, PCCT offers substantial benefits, including lower radiation doses, which may help reduce the risk of malignancy in pediatric patients, with perhaps greater potential to benefit those with repeated exposure from a young age. Enhanced spatial resolution facilitates better visualization of small structures, vital for diagnosing congenital heart defects. Additionally, PCCT's spectral capabilities improve tissue characterization and enable the creation of virtual monoenergetic images, which enhance soft-tissue contrast and potentially reduce contrast media doses. Initial clinical results indicate that PCCT provides superior image quality and diagnostic accuracy compared to conventional CT, particularly in challenging pediatric cardiovascular cases. As PCCT technology matures, further research and standardized protocols will be essential to fully integrate it into pediatric imaging practices, ensuring optimized diagnostic outcomes and patient safety.

Indexed as

CardiovascularComputed tomographyPediatricPhoton-counting computed tomographyPhoton-counting detectors

Identifiers

PMID40059896
PMCPMC11686577

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.