title: Auto-propagation of contours for adaptive prostate radiation therapy.
abstract: The purpose of this work is to develop an effective technique to automatically propagate contours from planning CT to cone beam CT (CBCT) to facilitate CBCT-guided prostate adaptive radiation therapy. Different from other disease sites, such as the lungs, the contour mapping here is complicated by two factors: (i) the physical one-to-one correspondence may not exist due to the insertion or removal of some image contents within the region of interest (ROI); and (ii) reduced contrast to noise ratio of the CBCT images due to increased scatter. To overcome these issues, we investigate a strategy of excluding the regions with variable contents by a careful design of a narrow shell signifying the contour of an ROI. For rectum, for example, a narrow shell with the delineated contours as its interior surface was constructed to avoid the adverse influence of the day-to-day content change inside the rectum on the contour mapping. The corresponding contours in the CBCT were found by warping the narrow shell through the use of BSpline deformable model. Both digital phantom experiments and clinical case testing were carried out to validate the proposed ROI mapping method. It was found that the approach was able to reliably warp the constructed narrow band with an accuracy better than 1.3 mm. For all five clinical cases enrolled in this study, the method yielded satisfactory results even when there were significant rectal content changes between the planning CT and CBCT scans. The overlapped area of the auto-mapped contours over 90% to the manually drawn contours is readily achievable. The proposed approach permits us to take advantage of the regional calculation algorithm yet avoiding the nuisance of rectum/bladder filling and provide a useful tool for adaptive radiotherapy of prostate in the future.
authors.affiliation: Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, CA 94305-5847, USA.
authors.forename: Ming
authors.initials: M
authors.lastname: Chao
authors.forename: Yaoqin
authors.initials: Y
authors.lastname: Xie
authors.forename: Lei
authors.initials: L
authors.lastname: Xing
mesh_terms: D000465:Algorithms; D054893:Cone-Beam Computed Tomography / Q000379:methods; D006801:Humans; D008297:Male; D015233:Models, Statistical; D019047:Phantoms, Imaging; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000532:radiotherapy*; D011856:Radiographic Image Enhancement / Q000379:methods; D011878:Radiotherapy / Q000379:methods*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D011881:Radiotherapy, Computer-Assisted; D015203:Reproducibility of Results; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods