Development of a semi-automated tool to measure fetal abdominal wall thickness during ultrasound at 20 weeks' gestation.

abdominal wall thickness automated measurement fetal adiposity fetal growth gestational diabetes

Journal

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
ISSN: 1879-3479
Titre abrégé: Int J Gynaecol Obstet
Pays: United States
ID NLM: 0210174

Informations de publication

Date de publication:
12 Apr 2024
Historique:
revised: 27 02 2024
received: 04 06 2023
accepted: 24 03 2024
medline: 12 4 2024
pubmed: 12 4 2024
entrez: 12 4 2024
Statut: aheadofprint

Résumé

To develop a semi-automated tool for measuring fetal abdominal wall thickness (AWT). To validate the software using images captured by other centers and create a nomogram for fetal AWT between 18 and 20 weeks. A semiautomated tool that measured AWT was developed using images captured at the routine 20-week morphology scan. The software was developed using digital images captured routinely during scans of low-risk women. Inter- and intraobserver reliability was assessed between manual and semi-automated measures. The tool was validated using images acquired from other centers. Linear regression and quadratic polynomials were used to create a nomogram for AWT. The semi-automated tool was able to measure AWT in all images. Interoperator reliability was 0.90 and 0.97 (P < 0.05) for manual and semi-automated methods, respectively. Measurement agreement varied between three operators from moderate to excellent (0.77, 0.87, 0.92), with overall agreement being good (0.85). The tool could be successfully applied to 89% of images from other centers. A nomogram was generated for AWT measurements of fetuses at 18-20 weeks in normal, low risk mothers. Semi-automated measurement of AWT was feasible using images captured during the routine 20-week scan. This approach had lower inter- and intraobserver variability compared to manual measurement.

Identifiants

pubmed: 38607348
doi: 10.1002/ijgo.15524
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024 International Federation of Gynecology and Obstetrics.

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Auteurs

Suresh Seshadri (S)

Mediscan Systems, Chennai, India.

Sindhu Pudhukudi (S)

Mediscan Systems, Chennai, India.
Aster Fetal Medicine, Aster Medcity, Cochin, India.

Jayanti Vajiravelu (J)

Mediscan Systems, Chennai, India.

Ponnusamy Saravanan (P)

Populations, Evidence and Technologies, Division of Health Sciences, Warwick Medical School, University of Warwick, Coventry, UK.
Department of Diabetes, Endocrinology and Metabolism, George Eliot Hospital, Nuneaton, UK.

Jon Hyett (J)

Faculty of Medicine, University of Sydney, Sydney, New South Wales, Australia.

Uma Ram (U)

Seethapathy Clinic and Hospital, Chennai, India.

Classifications MeSH