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三维超声与图像识别优化胎儿生物测量(EPICEA):一项前瞻性横断面研究方案。

Optimization of Fetal Biometry With 3D Ultrasound and Image Recognition (EPICEA): protocol for a prospective cross-sectional study.

机构信息

Obstetrics Department, CHRU Nancy, Nancy, Lorraine, France

Midwifery Department, Université de Lorraine, Nancy, France.

出版信息

BMJ Open. 2019 Dec 15;9(12):e031777. doi: 10.1136/bmjopen-2019-031777.


DOI:10.1136/bmjopen-2019-031777
PMID:31843832
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6924693/
Abstract

CONTEXT: Variability in 2D ultrasound (US) is related to the acquisition of planes of reference and the positioning of callipers and could be reduced in combining US volume acquisitions and anatomical structures recognition. OBJECTIVES: The primary objective is to assess the consistency between 3D measurements (automated and manual) extracted from a fetal US volume with standard 2D US measurements (I). Secondary objectives are to evaluate the feasibility of the use of software to obtain automated measurements of the fetal head, abdomen and femur from US acquisitions (II) and to assess the impact of automation on intraobserver and interobserver reproducibility (III). METHODS AND ANALYSIS: 225 fetuses will be measured at 16-30 weeks of gestation. For each fetus, six volumes (two for head, abdomen and thigh, respectively) will be prospectively acquired after performing standard 2D biometry measurements (head and abdominal circumference, femoral length). Each volume will be processed later by both a software and an operator to extract the reference planes and to perform the corresponding measurements. The different sets of measurements will be compared using Bland-Altman plots to assess the agreement between the different processes (I). The feasibility of using the software in clinical practice will be assessed through the failure rate of processing and the score of quality of measurements (II). Interclass correlation coefficients will be used to evaluate the intraobserver and interobserver reproducibility (III). ETHICS AND DISSEMINATION: The study and related consent forms were approved by an institutional review board (CPP SUD-EST 3) on 2 October 2018, under reference number 2018-033 B. The study has been registered in https://clinicaltrials.gov registry on 23 January 2019, under the number NCT03812471. This study will enable an improved understanding and dissemination of the potential benefits of 3D automated measurements and is a prerequisite for the design of intention to treat randomised studies assessing their impact. TRIAL REGISTRATION NUMBER: NCT03812471; Pre-results.

摘要

背景:二维超声(US)的变异性与参考平面的获取以及卡尺的定位有关,结合 US 容积采集和解剖结构识别可以减少这种变异性。

目的:主要目的是评估从胎儿 US 容积中提取的 3D 测量值(自动和手动)与标准 2D US 测量值(I)之间的一致性。次要目的是评估使用软件从 US 采集获得胎儿头部、腹部和股骨自动测量值的可行性(II),并评估自动化对观察者内和观察者间可重复性的影响(III)。

方法和分析:将在 16-30 孕周对 225 例胎儿进行测量。对于每个胎儿,将在进行标准 2D 生物测量(头围和腹围、股骨长度)后,前瞻性采集两个头、腹部和大腿的六个容积(各两个)。之后,每个容积将由软件和操作人员分别处理,以提取参考平面并进行相应的测量。将使用 Bland-Altman 图比较不同数据集的测量值,以评估不同处理过程之间的一致性(I)。将通过处理失败率和测量质量评分评估软件在临床实践中的可行性(II)。观察者内和观察者间可重复性将使用组内相关系数进行评估(III)。

伦理和传播:该研究及其相关同意书于 2018 年 10 月 2 日由机构审查委员会(CPP SUD-EST 3)批准,参考编号为 2018-033 B。该研究于 2019 年 1 月 23 日在 https://clinicaltrials.gov 注册,注册号为 NCT03812471。本研究将有助于更好地理解和传播 3D 自动测量的潜在益处,是设计评估其影响的意向治疗随机研究的前提。

试验注册号:NCT03812471;预结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4c2/6924693/a742b9e29d62/bmjopen-2019-031777f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4c2/6924693/c6ea42c7b433/bmjopen-2019-031777f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4c2/6924693/a742b9e29d62/bmjopen-2019-031777f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4c2/6924693/c6ea42c7b433/bmjopen-2019-031777f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4c2/6924693/a742b9e29d62/bmjopen-2019-031777f02.jpg

相似文献

[1]
Optimization of Fetal Biometry With 3D Ultrasound and Image Recognition (EPICEA): protocol for a prospective cross-sectional study.

BMJ Open. 2019-12-15

[2]
Fetal biometry: how well can offline measurements from three-dimensional volumes substitute real-time two-dimensional measurements?

Ultrasound Obstet Gynecol. 2013-10-2

[3]
Artificial intelligence assistance for fetal head biometry: Assessment of automated measurement software.

Diagn Interv Imaging. 2018-9-1

[4]
Fetal biometry by an inexperienced operator using two- and three-dimensional ultrasound.

Ultrasound Obstet Gynecol. 2010-5

[5]
The feasibility of using 5D CNS software in obtaining standard fetal head measurements from volumes acquired by three-dimensional ultrasonography: comparison with two-dimensional ultrasound.

J Matern Fetal Neonatal Med. 2016

[6]
Volumetric (3D) imaging reduces inter- and intraobserver variation of fetal biometry measurements.

Ultrasound Obstet Gynecol. 2009-4

[7]
Accuracy of automated three-dimensional ultrasound imaging technique for fetal head biometry.

Ultrasound Obstet Gynecol. 2021-5

[8]
Biometry and fetal weight estimation by two-dimensional and three-dimensional ultrasonography: an intraobserver and interobserver reliability and agreement study.

Ultrasound Obstet Gynecol. 2012-7-3

[9]
Use of focus point for plane acquisition to improve reproducibility in fetal biometry.

Ultrasound Obstet Gynecol. 2024-2

[10]
Intraobserver and interobserver reproducibility of fetal biometry.

Ultrasound Obstet Gynecol. 2004-11

本文引用的文献

[1]
Artificial Intelligence for Medical Image Analysis: A Guide for Authors and Reviewers.

AJR Am J Roentgenol. 2018-12-17

[2]
Machine-learning-based automatic identification of fetal abdominal circumference from ultrasound images.

Physiol Meas. 2018-10-22

[3]
Artificial intelligence assistance for fetal head biometry: Assessment of automated measurement software.

Diagn Interv Imaging. 2018-9-1

[4]
Automated measurement of fetal head circumference using 2D ultrasound images.

PLoS One. 2018-8-23

[5]
VP-Nets : Efficient automatic localization of key brain structures in 3D fetal neurosonography.

Med Image Anal. 2018-4-23

[6]
Five-dimensional long bones biometry for estimation of femur length and fetal weight at term compared to two-dimensional ultrasound: a pilot study.

J Matern Fetal Neonatal Med. 2018-8

[7]
SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound.

IEEE Trans Med Imaging. 2017-11

[8]
The feasibility of using 5D CNS software in obtaining standard fetal head measurements from volumes acquired by three-dimensional ultrasonography: comparison with two-dimensional ultrasound.

J Matern Fetal Neonatal Med. 2016

[9]
Feasibility of three-dimensional reconstruction and automated measurement of fetal long bones using 5D Long Bone.

Obstet Gynecol Sci. 2015-7

[10]
True Reproducibility of UltraSound Techniques (TRUST): systematic review of reliability studies in obstetrics and gynecology.

Ultrasound Obstet Gynecol. 2015-7

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