Javascript must be enabled to continue!
Impact of biometric measurement error on identification of small‐ and large‐for‐gestational‐age fetuses
View through CrossRef
ABSTRACTObjectivesFirst, to obtain measurement‐error models for biometric measurements of fetal abdominal circumference (AC), head circumference (HC) and femur length (FL), and, second, to examine the impact of biometric measurement error on sonographic estimated fetal weight (EFW) and its effect on the prediction of small‐ (SGA) and large‐ (LGA) for‐gestational‐age fetuses with EFW < 10th and > 90th percentile, respectively.MethodsMeasurement error standard deviations for fetal AC, HC and FL were obtained from a previous large study on fetal biometry utilizing a standardized measurement protocol and both qualitative and quantitative quality‐control monitoring. Typical combinations of AC, HC and FL that gave EFW on the 10th and 90th percentiles were determined. A Monte‐Carlo simulation study was carried out to examine the effect of measurement error on the classification of fetuses as having EFW above or below the 10th and 90th percentiles.ResultsErrors were assumed to follow a Gaussian distribution with a mean of 0 mm and SDs, obtained from a previous well‐conducted study, of 6.93 mm for AC, 5.15 mm for HC and 1.38 mm for FL. Assuming errors according to such distributions, when the 10th and 90th percentiles are used to screen for SGA and LGA fetuses, respectively, the detection rates would be 78.0% at false‐positive rates of 4.7%. If the cut‐offs were relaxed to the 30th and 70th percentiles, the detection rates would increase to 98.2%, but at false‐positive rates of 24.2%. Assuming half of the spread in the error distribution, using the 10th and 90th percentiles to screen for SGA and LGA fetuses, respectively, the detection rates would be 86.6% at false‐positive rates of 2.3%. If the cut‐offs were relaxed to the 15th and 85th percentiles, respectively, the detection rates would increase to 97.0% and the false‐positive rates would increase to 6.3%.ConclusionsMeasurement error in fetal biometry causes substantial error in EFW, resulting in misclassification of SGA and LGA fetuses. The extent to which improvement can be achieved through effective quality assurance remains to be seen but, as a first step, it is important for practitioners to understand how biometric measurement error impacts the prediction of SGA and LGA fetuses. © 2019 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.
Title: Impact of biometric measurement error on identification of small‐ and large‐for‐gestational‐age fetuses
Description:
ABSTRACTObjectivesFirst, to obtain measurement‐error models for biometric measurements of fetal abdominal circumference (AC), head circumference (HC) and femur length (FL), and, second, to examine the impact of biometric measurement error on sonographic estimated fetal weight (EFW) and its effect on the prediction of small‐ (SGA) and large‐ (LGA) for‐gestational‐age fetuses with EFW < 10th and > 90th percentile, respectively.
MethodsMeasurement error standard deviations for fetal AC, HC and FL were obtained from a previous large study on fetal biometry utilizing a standardized measurement protocol and both qualitative and quantitative quality‐control monitoring.
Typical combinations of AC, HC and FL that gave EFW on the 10th and 90th percentiles were determined.
A Monte‐Carlo simulation study was carried out to examine the effect of measurement error on the classification of fetuses as having EFW above or below the 10th and 90th percentiles.
ResultsErrors were assumed to follow a Gaussian distribution with a mean of 0 mm and SDs, obtained from a previous well‐conducted study, of 6.
93 mm for AC, 5.
15 mm for HC and 1.
38 mm for FL.
Assuming errors according to such distributions, when the 10th and 90th percentiles are used to screen for SGA and LGA fetuses, respectively, the detection rates would be 78.
0% at false‐positive rates of 4.
7%.
If the cut‐offs were relaxed to the 30th and 70th percentiles, the detection rates would increase to 98.
2%, but at false‐positive rates of 24.
2%.
Assuming half of the spread in the error distribution, using the 10th and 90th percentiles to screen for SGA and LGA fetuses, respectively, the detection rates would be 86.
6% at false‐positive rates of 2.
3%.
If the cut‐offs were relaxed to the 15th and 85th percentiles, respectively, the detection rates would increase to 97.
0% and the false‐positive rates would increase to 6.
3%.
ConclusionsMeasurement error in fetal biometry causes substantial error in EFW, resulting in misclassification of SGA and LGA fetuses.
The extent to which improvement can be achieved through effective quality assurance remains to be seen but, as a first step, it is important for practitioners to understand how biometric measurement error impacts the prediction of SGA and LGA fetuses.
© 2019 The Authors.
Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.
Related Results
Anatomy of Inferior Mesenteric Artery in Fetuses
Anatomy of Inferior Mesenteric Artery in Fetuses
Aim. To analyze Inferior Mesenteric Artery in fetuses through its site of origin, length, diameter, and variation of its branches.Method. 100 fetuses were collected from various ho...
Frontal Lobe Development in Fetuses with Growth Restriction: A Case-Control Study
Frontal Lobe Development in Fetuses with Growth Restriction: A Case-Control Study
Objective: To evaluate the impact of fetal circulatory redistribution
(FCR) on frontal lobe development in fetuses with growth restriction
(FGR) compared with appropriately grown f...
A Comprehensive Review of Multi-BiometricAuthentication System: Optimal Trait Combinations, Fusion Strategy, Methodologies, Research Challenges, and Future Directions
A Comprehensive Review of Multi-BiometricAuthentication System: Optimal Trait Combinations, Fusion Strategy, Methodologies, Research Challenges, and Future Directions
Abstract
Multi-biometric authentication is increasingly favored over single-biometric systems due to its enhanced robustness, performance, and security. Over the years, ext...
Early Physical Linear Growth of Small-for-Gestational-Age Infants Based on Computer Analysis Method
Early Physical Linear Growth of Small-for-Gestational-Age Infants Based on Computer Analysis Method
This article proposes that machine learning can break through the technical limitations of the linear growth test for the early physique of infants smaller than gestational age and...
Optimizing Secure Selective Face Template Generation Exchange over Open Network
Optimizing Secure Selective Face Template Generation Exchange over Open Network
Abstract
Many modern authentication systems utilize human biometrics instead of traditional passwords and security codes to overcome their limitations. To enhance security,...
Multi-Biometrics: Survey and Projection of a New Biometric System
Multi-Biometrics: Survey and Projection of a New Biometric System
Multi-biometric systems using feature-level fusion allow more accuracy and reliability in recognition performance than uni-biometric systems. But in practice, this type of fusion i...
Cerebrovascular Blood Flow Dynamic Changes in Fetuses with Congenital Heart Disease
Cerebrovascular Blood Flow Dynamic Changes in Fetuses with Congenital Heart Disease
<i>Objective:</i> The aim of this study was to determine whether the type of congenital heart disease (CHD) or heart function influence fetal cerebrovascular blood flow...
Impact of pre-pregnancy BMI and gestational weight gain on adverse pregnancy outcomes in Chinese women with gestational diabetes mellitus: A systematic review and meta-analysis
Impact of pre-pregnancy BMI and gestational weight gain on adverse pregnancy outcomes in Chinese women with gestational diabetes mellitus: A systematic review and meta-analysis
Abstract
Background Pre-pregnancy BMI and gestational weight gain are associated with pregnancy outcomes. This review aimed to explore pregestational BMI and gestational we...

