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SU-F-T-335: Piecewise Uniform Dose Prescription and Optimization Based On PET/CT Images.

PURPOSE
In intensity modulated radiation therapy (IMRT), the tumor target volume is given a uniform dose prescription, which does not consider the heterogeneous characteristics of tumor such as hypoxia, clonogen density, radiosensitivity, tumor proliferation rate and so on. Our goal is to develop a nonuniform target dose prescription method which can spare organs at risk (OARs) better and does not decrease the tumor control probability (TCP).


METHODS
We propose a piecewise uniform dose prescription (PUDP) based on PET/CT images of tumor. First, we propose to delineate biological target volumes (BTV) and sub-biological target volumes (sub-BTVs) by our Hierarchical Mumford-Shah Vector Model based on PET/CT images of tumor. Then, in order to spare OARs better, we make the BTV mean dose minimized while restrict the TCP to a constant. So, we can get a general formula for determining an optimal dose prescription based on a linearquadratic model (LQ). However, this dose prescription is high heterogeneous, it is very difficult to deliver by IMRT. Therefore we propose to use the equivalent uniform dose (EUD) in each sub-BTV as its final dose prescription, which makes a PUDP for the BTV.


RESULTS
We have evaluated the IMRT planning of a patient with nasopharyngeal carcinoma respectively using PUDP and UDP. The results show that the highest and mean doses inside brain stem are 48.425Gy and 19.151Gy respectively when the PUDP is used for IMRT planning, while they are 52.975Gy and 20.0776Gy respectively when the UDP is used. Both of the resulting TCPs(0.9245, 0.9674) are higher than the theoretical TCP(0.8739), when 70Gy is delivered to the BTV.


CONCLUSION
Comparing with the UDP, the PUDP can spare the OARs better while the resulting TCP by PUDP is not significantly lower than by UDP. This work was supported in part by National Natural Science Foundation of China undergrant no.61271382 and by the foundation for construction of scientific project platform forthe cancer hospital of Hunan province.