Evidence map›Paper›PMID 40251906›Full record

ArticleInternational journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics2025

Do MRI structured reports with FIGO classifications of leiomyomas contain adequate information for clinical decision making?

Laura Tordjman, Haleh Amirian, Alexandra Alvarez, Sara Shir, Julieta Aristizabal, Patricia Castillo, Prasoon Mohan, Stephanie Delgado, Francesco Alessandrino

Abstract read
In one paragraph

Article in International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Do MRI structured reports with FIGO classifications of leiomyomas contain adequate information for clinical decision making?International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025
    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

9 authors.

Laura TordjmanDepartment of Radiology, Jackson Memorial Hospital, Miami, Florida, USA.
Haleh AmirianDepartment of Surgery, University of Miami Miller School of Medicine, Miami, Florida, USA.ORCID https://orcid.org/0000-0002-6094-1342
Alexandra AlvarezDepartment of Obstetrics and Gynecology, Jackson Memorial Hospital, Miami, Florida, USA.
Sara ShirUniversity of Miami Miller School of Medicine, Miami, Florida, USA.
Julieta AristizabalDepartment of Radiology, Jackson Memorial Hospital, Miami, Florida, USA.
Patricia CastilloDepartment of Radiology, Jackson Memorial Hospital, Miami, Florida, USA.
Prasoon MohanDepartment of Interventional Radiology, University of Miami Miller School of Medicine, Miami, Florida, USA.
Stephanie DelgadoDepartment of Obstetrics and Gynecology, University of Miami Miller School of Medicine, Miami, Florida, USA.
Francesco AlessandrinoDepartment of Radiology, Jackson Memorial Hospital, Miami, Florida, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate if structured reports (SR) of pelvic magnetic resonance imaging (MRI) scans using the PALM-COEIN FIGO (the International Federation of Gynecology & Obstetrics) uterine leiomyomas classification (SR-FIGO) contain adequate information for clinical decision making compared with narrative reports (NR).

methodsThree reporting templates for pelvic MRI scans were compared: NR, SR without the PALM-COEIN FIGO classification of leiomyomas, and SR-FIGO, for presence of 19 key-features (KF) deemed relevant for leiomyoma management. Kruskal-Wallis test was used to evaluate KF distribution across the report types. One gynecologist and one gynecologist-in-training evaluated the reports and MRI scans to assess the presence of sufficient information to decide on: (1) treatment type (observation/medical treatment/surgery/uterine artery embolization); (2) surgical approach (hysteroscopic/laparoscopic/robotic/open); (3) surgery type (myomectomy/hysterectomy); (4) necessity to review MRI scans; and (5) time spent reviewing MRI scans. The responses of the gynecologist and gynecologist-in-training to points 1 to 5 among report types were compared using χ

resultsTwenty NR, 20 SR, and 20 SR-FIGO were reviewed. The number of KF was significantly different among reports (P < 0.001): SR-FIGO had the highest number of KF, followed by SR, and NR. In pairwise comparison, significant differences were observed between NR and SR (P = 0.001) and between NR and SR-FIGO (P = 0.001), but not between SR and SR-FIGO (P = 0.063). There were significant differences in answers to question 1 between the gynecologist and gynecologist-in-training for SR (P = 0.007) and SR-FIGO (P = 0.024), with the gynecologist deeming SR and SR-FIGO to provide enough information for treatment decisions more commonly than the gynecologist-in-training.

conclusionAlthough this investigation revealed that SR offers a greater wealth of information in contrast to NR, additional investigation is required to ascertain whether the integration of the PALM-COEIN FIGO classification in SR enhances the clinical decision making capacity of gynecologists.

Indexed as

Clinical Decision-MakingLeiomyomaMagnetic Resonance ImagingUterine NeoplasmsFemaleGynecologyHumansFIGO (the International Federation of Gynecology & Obstetrics)leiomyomamagnetic resonance imaging

Identifiers

PMID40251906
PMCPMC12447691

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.