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A Novel Image Guided 3D Treatment Delivery of TMI/TBI for Per-Clinical Trials

D Zuro

D Zuro*, J Brooks , J Wong , S Hui , City of Hope Medical Center, Duarte, CA


TU-RPM-GePD-JT-4 (Tuesday, August 1, 2017) 3:45 PM - 4:15 PM Room: Joint Imaging-Therapy ePoster Theater

Purpose: Clinical Total Marrow Irradiation (TMI) relies on complex treatment plans using IMRT to deliver larger doses to the bone marrow, while sparing soft tissue. When compared with total body irradiation (TBI), this allows for either lower dose delivered to the soft tissue, or increased dose to the bone marrow. Understanding the mechanistic differences between the effects TMI and TBI on marrow transplant engraftment are difficult due in part to the limitations of radiation delivery and tissue dose calculation in the preclinical mouse model. Standard preclinical TBI does not allow targeted tissue specific radiation. We report here newly developed CT image guided 3D TMI treatment delivery.

Methods: Using the PXi Precision Xray machine, a mouse whole body CT was acquired. Monte Carlo based simulation was performed to develop treatment plan to deliver doses of 10Gy to the PTV while minimizing soft tissue. The dose volume histograms were generated. Pre-treatment imaging was performed to re-localize and deliver radiation.

Results: Dose was highly conformed within the skeletal system, while dose to vital organs were substantially reduced (ranging from 50% dose reduction in the lung to 80% dose reduction in the gut). CT scan improved tissue visualization allowing for improved targeting of boney tissues.

Conclusion: The ability to deliver accurate and precise treatment will allow for accurate calculations of dose to tissues within the mouse and provide a quantitative analysis for comparison of TMI and TBI treatments in the preclinical model. Further development is in the process to improve imaging, image registration, as well utilization of TMI model for bone marrow transplant experiments.

Funding Support, Disclosures, and Conflict of Interest: Financially supported by grants from National Institute of Health Grant# 1R01CA154491-01

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