A score‐based method for quality control of fetal images at routine second‐trimester ultrasound examination
Abstract
Objectives: Our aim was to develop and evaluate the feasibility and reproducibility of score‐based quality control for routine standardized fetal ultrasound images obtained in the second trimester of pregnancy. Study Design: In France, a minimum of three biometrical and six anatomical standardized ultrasound planes are to be produced with any mid‐trimester scan. All anatomical standardized ultrasound images, routinely obtained by one trained operator at 20 to 24 weeks, were stored prospectively during a 1‐year period. Twenty‐five examinations containing these images were later randomly selected. These were then analyzed by two reviewers, according to predefined criteria agreed upon on the basis of established standards. This yielded a total score of up to 32 points. Feasibility, inter‐ and intra‐reviewer reproducibility were analyzed. Results: Routine second‐trimester ultrasound examinations numbering 1160 performed over a one year period by one trained sonographer unaware of the subsequent study at the time the images were recorded and stored in a database. Among the 150 images randomly selected and analyzed, adjusted kappa values were above 0.8 for 27 (84%) and 30 (94%) criteria, intra‐class correlation coefficient was 0.86 (0.75; 0.96) and 0.98 (0.94; 1) and the mean difference (95% CI) in score was − 0.44 (−3.0; 2.1) and − 0.2(−2; 1.6) for inter‐ and intra‐reviewer comparisons respectively. Conclusion: A quality control policy based on image scoring is feasible and allows for good inter‐ and intra‐reviewer reproducibility. Besides its potential for audit and quality control, this could also be useful during the training process. Copyright © 2008 John Wiley & Sons, Ltd.
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A study of prenatal detection of malformations using ultrasound images demonstrated performance sensitivity ranged from 27.5% to 96% among different medical institutions.
“A study of the prenatal detection of malformations using ultrasound images demonstrated that the performance sensitivity ranged from 27.5% to 96% among different medical institutions [24].”
From Deep Learning Strategies for Ultrasound in Pregnancy (2020) · cites this paper as [24]
A study on prenatal detection of malformations using US images demonstrated that sensitivity ranged from 27.5% to 96% among different medical institutes.
“For example, a study on the prenatal detection of malformations using US images demonstrated that the sensitivity ranged from 27.5% to 96% among different medical institutes [3].”
From Deep Learning in Medical Ultrasound Analysis: A Review (2019) · cites this paper as [3]
Medical US has high inter- and intra-observer variability across different institutes and manufacturers' US systems.
“However, US also presents unique challenges, such as low imaging quality caused by noise and artifacts, high dependence on abundant operator or diagnostician experience, and high inter-and intra-observer variability across different institutes and manufacturers' US systems.”
From Deep Learning in Medical Ultrasound Analysis: A Review (2019) · cites this paper as [3]
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- Authors
- Salomon, L. J., Winer, N., Bernard, J. P., & Ville, Y.
- Affiliations
- Centre Hospitalier Intercommunal de Poissy (FR)
- Centre Hospitalier Universitaire de Nantes (FR)
- Corresponding author
- Ville, Y.
- Venue
- Prenatal Diagnosis
- Publisher
- Wiley
- Published
- 2008-07-22
- Volume
- 28
- Issue
- 9
- Pages
- 822-827
- ISSN
- 0197-3851 (ISSN-L)
- 1097-0223
- OpenAlex
- W2023785047
- Cited by
- 85
- References
- 20
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 9 · 2023: 13 · 2022: 12 · 2021: 5 · 2020: 7 · 2019: 4 · 2018: 5 · 2017: 4 · 2016: 1 · 2015: 3 · 2014: 3 · 2013: 6 · 2012: 4
- FWCI
- 0.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Prenatal Diagnosis (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Prenatal Screening and Diagnostics
- Health Sciences › Medicine › Critical Care and Intensive Care Medicine › Ultrasound in Clinical Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiology practices and education
- Keywords
- image scoring, second-trimester ultrasound, sonographer training
- MeSH terms
- Biometry, Female, Humans, Pregnancy, Pregnancy Trimester, Second, Quality Control, Ultrasonography, Prenatal
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