SU‐E‐J‐54: Evaluation of a Toolkit for Automatic Deformable Registration and Segmentation of Treatment Images in Clinical Prostate Cancer IGRT Applications

• Published in: Medical Physics 2011-06, Vol.38 (6), p.3454-3454
• Main Authors: Xu, Z, Chaney, E, Kress, A, Tracton, G, Foskey, M, Lian, J, Chang, S
• Format: Article
• Language: English
• Subjects: Anatomy; Biomedical modeling; Cancer; Computed tomography; Image guided radiation therapy; Medical image quality; Medical image segmentation; Medical imaging; Therapeutics; Tissues
• ISSN: 0094-2405; 2473-4209
• DOI: 10.1118/1.3611822

Purpose: High quality IGRT is only practical when robust tools are available for accurate and fast deformable registration and segmentation of the treatment images. We have implemented such a toolkit for the male pelvis using a class of statistically trainable deformable models (SDMs) of anatomical structures, called medial representations (m‐reps). The aim of this study is to evaluate its capabilities and performance in clinical prostate cancer IGRT applications. Methods: An image collection for prostate cancer patients treated with IGRT using a CT‐on‐Rails (CTORs) system was studied retrospectively with this toolkit to determine the actual delivered dose throughout the treatment course. The patient‐specific planning models of the male pelvic organs, including the prostate, bladder, rectum, and femoral heads, were constructed via user‐guided autosegmentation of the planning CT. The planning CT was then automatically registered to the CTORs images via a rigid‐body, soft‐tissue‐based registration method. The planning models were then transformed into initialized treatment models to segment the CTORs images. The essential tissue‐voxel correspondence across treatment images was established by this model‐based segmentation process. The dose delivered to the same tissue elements can, therefore, be accumulated for adaptive planning and/or outcome assessment. Results: Preliminary results show that the m‐rep‐based planning image segmentations are clinically acceptable to the physicians and can be readily constructed from the planning CT with nominal user guidance. The automatic image registration with the treatment‐day image, occasionally followed by manual refinement, also considered acceptable by clinical staff. Treatment image segmentation with intrinsic tissue‐voxel correspondence used substantially less time (5 ± 1.3 minutes) in comparison to manual contouring. Conclusions: Our clinic‐oriented toolkit is effective in segmentation of treatment images of the male pelvis. Application for dose accumulation and adaptive IGRT is in progress. This work has been conducted in collaboration with Morphormics, Inc. with grant support from NCI R44 CA119571.