Evidence map›Paper›PMID 40822255›Full record

ArticleJournal of pediatrics. Clinical practice2025

Quantifying and Contextualizing Radiation Doses in Common Pediatric Medical Imaging Examinations.

Carly Stewart, Susan Alber, Malini Mahendra, Cameron Kofler, Trung Tran, Sean Domal, Erin J A Bowles, Sheila Weinmann, Robert T Greenlee, Natasha K Stout and 8 more

Abstract read
In one paragraph

Article in Journal of pediatrics. Clinical practice, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

18 authors.

Carly StewartDepartment of Epidemiology and Biostatistics, University of California, San Francisco, CA.
Susan AlberDepartment of Public Health Sciences, University of California, Davis, CA.
Malini MahendraDepartment of Pediatrics, University of California, San Francisco, CA.
Cameron KoflerJ. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL.
Trung TranJ. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL.
Sean DomalJ. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL.
Erin J A BowlesKaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, WA.
Sheila WeinmannCenter for Health Research, Kaiser Permanente Northwest, Portland, OR.
Robert T GreenleeMarshfield Clinic Research Institute, Marshfield Clinic, Health System, Marshfield, WI.
Natasha K StoutDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA.
Priscila PequenoICES, Toronto, Ontario, Canada.
Lisa M MoyDivision of Research, Kaiser Permanente Northern California, Pleasanton, CA.
James R DuncanInterventional Radiology Section, Washington University in St. Louis, St. Louis, MI.
Jason D PoleICES, Toronto, Ontario, Canada.
Wesley E BolchJ. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL.
Marilyn L KwanDivision of Research, Kaiser Permanente Northern California, Pleasanton, CA.
Diana L MigliorettiDepartment of Public Health Sciences, University of California, Davis, CA.
Rebecca Smith-BindmanDepartment of Epidemiology and Biostatistics, University of California, San Francisco, CA.

Funding

Risk of Pediatric and Adolescent Cancer Associated with Medical ImagingR01CA185687 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KWAN, MARILYN L, MIGLIORETTI, DIANA L · 2015 to 2019
$10.0M
NCI NIH HHS R01 CA185687
6 · The paper itself

Abstract

Objective: To provide organ and effective radiation doses for common pediatric imaging examinations, which may help clinicians understand site-specific cancer risk, compare exposure across imaging modalities, and make informed care decisions. Study design: Within a large multicenter retrospective cohort, imaging utilization and associated radiation doses were estimated for children enrolled from birth into one of six US health care systems. Doses are described for examinations performed from 2012 to 2017. For computed tomography (CT), doses were estimated using examination-level technical parameters, patient height and weight, and Monte Carlo simulations. For fluoroscopy, angiography, nuclear medicine, and radiography, dose maps were developed by patient age, sex, size, and year through Monte Carlo simulations using technical parameters collected from patient examinations. The mean dose and standard deviation (SD) were calculated for each examination type, and each modality's contribution to the cohort's cumulative effective dose was calculated. Results: Eight hundred thirty-five thousand six hundred forty-three imaging examinations in 278 909 patients are included. Radiographs were the most commonly performed exam but made up 6% of radiation dose exposure. CT exams made up 4% of imaging exams but accounted for 80% of exposure. Head CT was the most common CT exam (44% of all CT). For head CT, the average radiation dose to the bone marrow (associated with hematologic cancer risk) was 9.8 mGy (SD = 6.7) and to the brain (associated with brain cancer risk) was 39 mGy (SD = 14.8). Conclusions: CT radiation doses to the bone marrow and brain fell within ranges associated with increased hematologic and brain cancer risk, and are highest in the youngest children.Keywords: Organ dose; effective dose; pediatric imaging; pediatric radiology; computed tomography; fluoroscopy; angiography; nuclear medicine; radiography; x-ray.

Identifiers

PMID40822255
PMCPMC12355588

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.