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Patient Lung Tumor Trajectory Based Modified-XCAT and Its Applications

P Mishra

P Mishra1*, S St. James1, W Segars2, R Berbeco1, J Lewis1, (1) Brigham and Women's Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, (2)Duke University, Durham, NC

TU-C-213CD-6 Tuesday 10:30:00 AM - 12:30:00 PM Room: 213CD

Purpose: To modify the digital XCAT phantom to include patient-specific 3D lung tumor trajectories and demonstrate potential applications.

Methods: An algorithm is developed to program the existing XCAT phantom to move according to recorded patient 3D lung trajectory data. The algorithm works in a two-step manner. First, we incorporate a tumor into the existing digital phantom. Introduction of tumor trajectory at this stage would result in an asynchronous motion between tumor and the chest-wall and diaphragm. In the second step, an image processing based methodology is developed to synchronize tumor trajectory with lung motion. Tumor location is calculated and a scale factor is derived based on the distance of the tumor from chest wall and diaphragm. The distances are calculated by extracting the contours of lungs using the Canny edge detection method and then fitting the edges to a quadratic polynomial. This step synchronizes tumor trajectory with lung motion. The internal motion data from 10 patients are used to verify the accuracy between actual tumor location and the location obtained from a modified XCAT phantom. The modified XCAT phantom is then used to simulate a 4DCT data acquisition and rebinning with a phase sorting algorithm.

Results: The accuracy of the tumor locations in the modified XCAT phantom are found to be 0.29, 0.54, and 0.39 mm (RMS) with corresponding standard deviation values of 0.04, 0.17, and 0.06. The sorted 4DCT simulation algorithm produces volume data comparable to ground-truth data. The image artifacts in the simulated 4DCT are similar to those that are seen clinically.

Conclusion: We have developed an algorithm to modify the XCAT digital phantom to realistically account for independent tumor motion. The modified phantom can be used for studies of CT reconstruction, tumor tracking and dose reconstruction.

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