SU-E-J-177: A Computational Approach for Determination of Anisotropic PTV Margins Based On Statistical Shape Analysis for Prostate Cancer Radiotherapy

Purpose: Our aim of this study was to propose a computational approach for determination of anisotropic planning target volume (PTV) margins based on statistical shape analysis with taking into account time variations of clinical target volume (CTV) shapes for the prostate cancer radiation treatment planning (RTP). Methods: Systematic and random setup errors were measured using orthogonal projection and cone beam computed tomography (CBCT) images for data of 20 patients, who underwent the intensity modulated radiation therapy for prostate cancer. The low-risk, intermediate-risk, and high-risk CTVs were defined as only a prostate, a prostate plus proximal 1-cm seminal vesicles, and a prostate plus proximal 2-cm seminal vesicles, respectively. All CTV regions were registered with a reference CTV region with a median volume to remove the effect of the setup errors, and converted to a point distribution models. The systematic and random errors for translations of CTV regions were automatically evaluated by analyzing the movements of centroids of CTV regions. The random and systematic errors for shape variations of CTV regions were obtained from covariance matrices based on point distributions for the CTV contours on CBCT images of 72 fractions of 10 patients. Anisotropic PTV margins for 6 directions (right, left, anterior, posterior, superior and inferior) were derived by using Yoda’s PTV margin model. Results: PTV margins with and without shape variations were 5.75 to 8.03 mm and 5.23 to 7.67 mm for low-risk group, 5.87 to 8.33 mm and 5.23 to 7.67 mm for intermediate-risk group, and 5.88 to 8.25 mm and 5.29 to 7.82 mm for highrisk group, respectively. Conclusion: The proposed computational approach could be feasible for determination of the anisotropic PTV margins with taking into account CTV shape variations for the RTP.