Placental biometry for prediction of small for gestational age fetuses in low resource setting


  • Megha Jindal Department of Obstetrics and Gynecology, University College of Medical Sciences and Associated Hospital, Delhi, India
  • Sangeeta Gupta Department of Obstetrics and Gynecology, Maulana Azad Medical College and Associated Hospitals, Delhi, India



Placental biometry, Small for gestational age fetuses


Background: Small for gestational age refers to foetuses with birth weight less than tenth centile for gestational age. Such foetuses are at increased risk of intrauterine fatal demise in comparison to others. Placenta plays a central role in supporting foetal growth. Researchers have emphasized on three dimensional sonographic placental volumetry as a predictor of SGA. This study focussed on role of two dimensional Ultrasonographic placental measurement in predicting SGA foetuses.

Methods: Prospective study was conducted at Department of Obstetrics and Gynecology, Maulana Azad Medical College from November 2013 to February 2015. In singleton pregnancies at 18-22 weeks of gestation, placental biometry (in two dimensions) was performed. Maximal Placental Diameter (MaxPD) and Maximal Placental Thickness (MaxPT) in two orthogonal planes was recorded. Mean Placental Diameter (MPD) and Mean Placental Thickness (MPT) were calculated. At the time of delivery, as per the birth weight the neonate was classified into appropriate for gestational age (AGA)/ SGA/ large for gestational age (LGA). MPD and MPT were analyzed as predictors of SGA.

Results: Both the MaxPDs and MPD were significantly smaller in SGA pregnancies (all with p ≤ 0.001). Similarly, both the MaxPTs (p = 0.006 and p = 0.001) and MPT (p = 0.000) were significantly smaller in SGA pregnancies. The ROC curve for combined placental biometry had the maximum area under the curve (0.805).

Conclusions: Placental measurements taken in mid-gestation are a valuable predictor of SGA. Measurement of placental diameter and thickness is quick and simple. This approach should be explored in future to develop a predictive model for growth restricted foetuses.


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