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WE-E-213CD-07: Deformable Registration Between CT and Truncated CBCT for Adaptive Therapy Dose Calculation
X Zhen1,2, Y Graves1,2, H Yan1,2
1Center for Advanced Radiotherapy Technologies and Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA.
Purpose:
Deformable image registration (DIR) is a crucial step in adaptive radiation therapy (ART) to deform the planning CT to the current CBCT for dose calculation and for contour propagation. CBCT images are sometimes truncated in the axial plane due to limited field of view (FOV). DIR between CT and truncated CBCT often leads to unphysical results, especially in and near missing regions, which may result in significant errors in dose calculation afterwards. The purpose of this work is to develop and evaluate a method to improve existing DIR algorithms to solve the truncation problem.
Methods:
The radius of FOV of CBCT is first estimated. A recently developed robust CT-CBCT DIR algorithm, called Deformation with Intensity Simultaneously Corrected (DISC), is used for deformation field calculation. At each iteration of DISC, the calculated deformation vector field outside the FOV is replaced by a smooth propagation of the deformation field inside the FOV. Six head-and-neck cancer cases and two prostate cancer cases are used for evaluation. Dose calculation is performed to test the impacts on the resulting dose distribution.
Results:
In terms of DIR accuracy, it is found that the average normalized mutual information (NMI), normalized cross correlation (NCC) and feature similarity index (FSIM) increase from 0.638, 0.948 and 0.917, to 0.641, 0.951 and 0.919, respectively, when compared with DISC without propagation. In terms of dose distribution, the relative L2 distance of dose (inside the FOV) between the ground truth and that calculated on deformed CT with propagation reduces from 9.25%to 1.41%, compared with those without propagation.
Conclusions:
We have developed a deformation field propagation method for DIR to register the planning CT and the CBCT image with small FOV. Tests on head-and-neck and prostate cancer cases have demonstrated that our algorithm can generate more accurate registration results for dose calculation. This work is supported in part by the University of California Lab Fees Research Program, the Master Research Agreement from Varian Medical Systems, Inc., and the grants from the National Natural Science Foundation of China (No.30970866).
