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The University of Florida Library of Pregnant Female Hybrid Computational Phantoms

S Domal1*, W Bolch2 , C Paulbeck3 , M Maynard4 , (1) University of Florida, Gainesville, FL, (2) Univ Florida, Gainesville, FL, (3) University of Florida, Gainesville, FL, (4) Willis-Knighton Cancer Center, Shreveport, LA


(Thursday, 7/18/2019) 10:00 AM - 12:00 PM

Room: 304ABC

Purpose: To develop a series of pregnant female computational phantoms that better quantify fetal dose as a function of maternal size and fetal depth for x-ray imaging applications.

Methods: Six gestational ages were modeled (15, 20, 25, 30, 35, and 38 weeks) for women of 50th percentile height and 10th, 25th, 50th, 75thand 90th percentile weight. Target height, weight and waist circumference values for each percentile were derived from the most current non-pregnant U.S adult female population body morphometry data detailed in the NHANES surveys obtained by the CDC. Pregnancy weight gain charts provided by the CDC and waist circumference trends present in the current series of UF pregnant female phantoms allowed the derivation of these parameters for the pregnant U.S. adult female population. Each phantom from the existing UF series of pregnant female phantoms was first scaled to the appropriate 50th percentile height. Once the correct height was established, the outer body contour was scaled to match the appropriate waist circumference. To complete this process, weight was iteratively matched by adjusting control points of structures commonly associated with weight gain. This included upper and lower regions of the arms and legs, buttocks, neck and the glandular and adipose layers of the breast.

Results: This unique library consists of pregnant females at six gestational ages for five weight percentiles of 50th percentile height. For a particular gestational age both maternal size (visceral layer of abdominal adipose) and fetal depth increase across each percentile in accordance to the derived values of maternal weight and waist circumference.

Conclusion: This work allows better phantom selection based on patient size for computational dosimetry in a multitude of exposure scenarios where the fetus is potentially exposed.


Dosimetry, Phantoms, Fetal Dose


IM- Radiation dose and risk: Models

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