Three-dimensional ultrasonography using the VOCAL technique for estimation of reference range between 7 and 11 weeks embryonic volume

Objective: Accurate estimation of gestational age (GA) is the basis of vital decisions in pregnancy and hence its importance in obstetric management. This study tries estimating a reference range of 3D embryonic volume using the VOCAL technique for pregnancies between 7 and 11 weeks. Materials and m...

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Bibliographic Details
Main Authors: Hassan Mostafa Gaafar, Ghada Abdel Fattah Abdel Moety, Waleed El-Khayat
Format: Article
Language:English
Published: SpringerOpen 2013-06-01
Series:Middle East Fertility Society Journal
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Online Access:http://www.sciencedirect.com/science/article/pii/S1110569013000034
Description
Summary:Objective: Accurate estimation of gestational age (GA) is the basis of vital decisions in pregnancy and hence its importance in obstetric management. This study tries estimating a reference range of 3D embryonic volume using the VOCAL technique for pregnancies between 7 and 11 weeks. Materials and methods: This cross-sectional study included 62 singleton normal uneventful pregnancies. All women were essentially sure of the date of last menstrual period. All women were submitted to 3D ultrasonographic examination with VOCAL technique to determine the embryonic volume. In addition the crown-rump length was measured. Regression analysis was performed to predict the gestational age from the fetal volume. Results: There was a strong positive correlation between embryonic volume and menstrual age, gestational age and crown-rump length (r = 0.919, 0.938 and 0.941, respectively). Power regression model produced R2 value of 0.838 with a regression equation (y = 52.22 + 6.5 x). Conclusion: This study demonstrated that embryonic/fetal volume is a good predictor of gestational age with a power regression equation (y = 52.22 + 6.5 x) for the period from 7 to 10 weeks + 6 days. We suggest using the embryo volume as an early evidence of growth restriction in high risk pregnancy.
ISSN:1110-5690