Evidence map›Paper›PMID 38486373›Full record

SynthesisMedical science monitor : international medical journal of experimental and clinical research2024

Accuracy of MRI-Based Radiomics in Diagnosis of Placenta Accreta Spectrum: A PRISMA Systematic Review and Meta-Analysis.

Liqiong Huang, Lin Ma, Qin Zhou, Yi Hu, Lirong Hu, Yang Luo, Yan Li

Open access · hybridAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Medical science monitor : international medical journal of experimental and clinical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
8.9field-weighted citation impact, top 3% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Machine learning applications in placenta accreta spectrum disorders.European journal of obstetrics & gynecology and reproductive biology: X · 2025
    Review
  5. 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

7 authors.

Liqiong HuangDepartment of Ultrasound, Chengdu First People's Hospital, Chengdu, Sichuan, China (mainland).
Lin MaDepartment of Ultrasound, Chengdu First People's Hospital, Chengdu, Sichuan, China (mainland).
Qin ZhouDepartment of Ultrasound, Chengdu First People's Hospital, Chengdu, Sichuan, China (mainland).
Yi HuDepartment of Ultrasound, Chengdu First People's Hospital, Chengdu, Sichuan, China (mainland).
Lirong HuDepartment of Ultrasound, Chengdu First People's Hospital, Chengdu, Sichuan, China (mainland).
Yang LuoDepartment of Ultrasound, Chengdu First People's Hospital, Chengdu, Sichuan, China (mainland).
Yan LiDepartment of Ultrasound, Chengdu First People's Hospital, Chengdu, Sichuan, China (mainland).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND Placenta accreta syndrome (PAS) can lead to severe obstetric bleeding, and can be life-threatening. This study aimed to assess the precision of radiomics features derived from magnetic resonance imaging (MRI) for diagnosing PAS. MATERIAL AND METHODS A comprehensive search was conducted in the databases PubMed, Embase, Web of Science, and the Cochrane library from inception to October 2023. We included diagnostic accuracy studies utilizing radiomics-MRI in PAS patients, with histopathology serving as the reference standard. The overall diagnostic odds ratio (DOR), sensitivity, specificity, and area under the curve (AUC) were computed to gauge the diagnostic accuracy of MRI-based radiomic features in PAS patients. Quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies 2. Statistical analyses were carried out using Stata 14.2, MetaDiSc 1.4, and Review Manager 5.3 software. RESULTS Seven studies involving 672 patients were incorporated. The aggregated DOR, sensitivity, specificity, and AUC for radiomics in detecting PAS were 78% (confidence interval32, 191), 87% (76%, 93%), 92% (89%, 94%), and 0.93 (0.91-0.95), respectively. The meta-analysis revealed notable heterogeneity among the included studies, with no evidence of a threshold effect. Subgroup analysis demonstrated that, in comparison to manual segmentation and validation groups with ≤100 cases and internal validation datasets, automated segmentation, validation groups with >100 cases, and external validation datasets exhibited superior diagnostic performance . CONCLUSIONS Our findings indicate that MRI-based radiomic features perform well in assessing the diagnostic risk of PAS during prenatal diagnosis. This noninvasive and convenient tool may prove valuable in facilitating the identification of PAS.

Indexed as

Placenta AccretaArea Under CurveDatabases, FactualFemaleHumansMagnetic Resonance ImagingPregnancyRadiomics

Identifiers

PMID38486373
PMCPMC10949827
OpenAlexW4391321614

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.