Preliminary External and Internal Dosimetry Data from a new set of mother/fetus models JY Zhang, V Taranenko, D Zhang, X. George Xu, Rensselaer Polytechnic Institute, Troy, NY CY Shi Cancer Therapy and Research Center, San Antonio, TX

Project Motivation (Pregnant Female Models) High radio-sensitivity for the fetus Needs for accurate dosimetry –Occupational (if the pregnancy is declared) –Nuclear medicine –Radiation treatment of pregnant patients (increasing!) –Air traveling –non-ionizing radiation (RF etc) Models difficult to develop –Twice as many tissues and organs –3-month, 6-month and 9-month gestational periods –Medical images are rare

Project Goals 1) Development a new set of models of pregnant mother and fetus at the end of 3-, 6- and 9-month gestational periods 2) Compile organ dose parameters for external and internal irradiations

Existing Pregnant Female Models Stylized models - Stabin Chen 2004 From partial-body CT image set - Shi and Xu (2004) They are un-realistic and in-complete

Method: Flow Chart of Pregnant Female Model Development Model Extraction of 3D representation from CT Images (external uterine wall). This is a new approach!

Organ Masses Adjusted to ICRP References

From Surfaces to Voxels Surface Model Adjusted to ICRP reference values Voxel Model Geometry in MCNPX code Re-voxelize at any size (1mm shown here) Put into MC codes - MCNPX - EGSnrc

RPI-P3, RPI-P6, and RPI-P9 Models 9-month 6-month3-month

Results - Internal photon Specific Absorbed Fractions (RPI-P9 phantom)

Results - External photons RPI-P9 phantom; total fetal dose

Conclusion A series of pregnant female and fetus phantoms have been developed Organ masses are adjusted according to ICRP reference values External photon, electron, neutron and proton sources have been studied Internal photon and electron sources have been studied ICRP is hoped to adopt the RPI-P series as standard pregnant-female models

Visualization for RPI-P9 Pregnant Female Model (available at RRMDG.rpi.edu) Acknowledgements This work is supported by grants 1R42CA and 5R01CA from the National Institutes of Health Drs Mike Stabin and Keith Eckerman provided valuable help on ICRP data analysis