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Updated: Mar 11, 2026

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Published on: June 29, 2013
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First-trimester reference centiles of fetal biometry in Indian population
Manisha Kumar1, Ravi Vajala2, Karuna Sharma3
1a Department of Obstetrics & Gynecology , LHMC , New Delhi , India.
Summary
This study created crown-rump length (CRL) charts for Indian fetuses in the first trimester. These biometric charts aid in determining gestational age and identifying potential adverse outcomes.
Area of Science:
- Maternal-fetal medicine
- Prenatal diagnostics
- Human fetal growth
Background:
- Accurate fetal biometry is crucial for monitoring pregnancy progression.
- Existing biometric charts may not fully represent diverse populations like the Indian subcontinent.
- Establishing population-specific reference data is essential for precise gestational age estimation.
Purpose of the Study:
- To develop crown-rump length (CRL)-based biometric charts for fetuses in the first trimester.
- To provide a reference standard tailored for the Indian population.
- To correlate CRL with other key fetal parameters.
Main Methods:
- Cross-sectional study involving 400 singleton pregnancies with normal outcomes (11-14 weeks gestation).
- Linear regression models were employed to establish relationships between CRL and other biometric measurements.
- Mean and standard deviation (SD) were derived as functions of CRL.
Main Results:
- Positive correlations were observed between CRL and nuchal translucency (NT), biparietal diameter (BPD), occipito-frontal diameter (OFD), lateral ventricular diameter (LV), abdominal circumference (AC), femur length (FL), and fetal weight (FW).
- Regression models and centile charts for NT, BPD, OFD, LV, AC, and FW were constructed.
- Linear equations were derived to calculate fetal weight using BPD, AC, and FL with FW as the independent variable.
Conclusions:
- The developed first-trimester centile charts serve as a valuable reference for the Indian population.
- These charts can assist in accurate determination of gestational age.
- The charts are useful for identifying potential adverse pregnancy outcomes.
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