Evidence map›Paper›PMID 41454942›Full record

ReviewAbdominal radiology (New York)2026

Dual energy CT of pediatric genitourinary disorders.

Sakura M Noda, Erin K Romberg, Joseph Wishart, Helen H R Kim, A Luana Stanescu, Grace Phillips

Abstract readReview
PubMed Publisher
In one paragraph

Review in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
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

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

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

6 authors.

Sakura M NodaDepartment of Radiology, University of Washington Medical Center, Seattle, USA. sakura.noda@seattlechildrens.org.
Erin K RombergDepartment of Radiology, University of Washington Medical Center, Seattle, USA.
Joseph WishartDepartment of Radiology, University of Washington Medical Center, Seattle, USA.
Helen H R KimDepartment of Radiology, University of Washington Medical Center, Seattle, USA.
A Luana StanescuDepartment of Radiology, University of Washington Medical Center, Seattle, USA.
Grace PhillipsDepartment of Radiology, University of Washington Medical Center, Seattle, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dual-energy CT (DECT) offers advantages over single-energy CT and MRI in the evaluation of the pediatric genitourinary system. Material specific techniques allow for creation of virtual noncontrast and iodine overlay images, which can avoid the radiation needed for a dedicated non-contrast CT or highlight areas of contrast enhancement. DECT also offers improved characterization of cysts and masses by differentiating between iodine, calcium, and proteinaceous/hemorrhagic material. Composition analysis of renal stones may allow for tailored stone therapy. Additionally, energy-specific techniques such as virtual monoenergetic images reconstructed at higher kV can reduce artifacts, especially those related to beam hardening. Conversely, virtual monoenergetic images reconstructed at lower kV offer increased contrast conspicuity, allowing for lower radiation and contrast doses. This paper reviews DECT technologies, post-processing techniques of material decomposition and virtual monoenergetic imaging, and examples of pediatric genitourinary clinical applications of DECT.

Indexed as

Female Urogenital DiseasesMale Urogenital DiseasesRadiography, Dual-Energy Scanned ProjectionTomography, X-Ray ComputedArtifactsChildContrast MediaFemaleHumansMaleContrast MediaComputed tomographyDual energyGenitourinaryMetal artifact reductionPediatricVirtual noncontrast

Identifiers

PMID41454942

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.