Evidence map›Paper›PMID 39888396›Full record

ArticlePediatric radiology2025

Ovarian volume estimation in girls using rapid MR imaging for right lower quadrant pain.

Sharon Gould, Tejal Mody, Mary Gould, Heidi Kecskemethy, Simone Veale, Arabinda Choudhary

Abstract read
PubMed Publisher
In one paragraph

Article in Pediatric radiology, 2025. 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.

Sharon GouldNemours Children's Health, 1600 Rockland Road, Wilmington, DE, 19803, USA. Sharon.Gould@nemours.org.
Tejal ModyNemours Children's Health, 1600 Rockland Road, Wilmington, DE, 19803, USA.
Mary GouldMedical University of South Carolina, Charleston, SC, USA.
Heidi KecskemethyNemours Children's Health, 1600 Rockland Road, Wilmington, DE, 19803, USA.
Simone VealeUniversity of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Arabinda ChoudharySUNY Upstate Medical University, Syracuse, NY, USA.

Funding

Nemours Departments of Biomedical Research and Medical Imaging
6 · The paper itself

Abstract

backgroundMRI provides adequate ovarian imaging to permit accurate measurement. More normative data for children and adolescents is needed as MRI is being used for evaluation of right lower quadrant pain that could be due to ovarian torsion.

objectiveTo determine normative data for ovarian size by MRI using a rapid protocol for right lower quadrant pain. MATERIALS AND

methodsRetrospective evaluation of MRI examinations of girls obtained between 2013 and 2019 was performed including chart and image review. Normative data was determined by age.

resultsMean patient age was 12.8 years (range 1-18 years). Six hundred forty-four scans were included in the study. Thirty-three ovaries contained cysts measuring greater than 3 cm and 8 additional ovaries were torsed. These ovaries were not included in the normal ovary measurements. Patients with known or suspected polycystic ovarian syndrome or torsion also were excluded. Ovarian volumes of normal-appearing ovaries are reported by patient age.

conclusionNormative data for girls and adolescents utilizing a rapid MRI protocol for right lower quadrant pain is provided for increased confidence in assessing ovarian size in girls on MRI.

Indexed as

Abdominal PainMagnetic Resonance ImagingOvaryAdolescentChildChild, PreschoolFemaleHumansInfantOrgan SizeReference ValuesRetrospective StudiesAdnexalAdolescentsChildFemaleMagnetic resonance imagingMeasurementOvarian cystPain

Identifiers

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.