title: Automated registration of large deformations for adaptive radiation therapy of prostate cancer.
abstract: Available deformable registration methods are often inaccurate over large organ variation encountered, for example, in the rectum and bladder. The authors developed a novel approach to accurately and effectively register large deformations in the prostate region for adaptive radiation therapy. A software tool combining a fast symmetric demons algorithm and the use of masks was developed in C++ based on ITK libraries to register CT images acquired at planning and before treatment fractions. The deformation field determined was subsequently used to deform the delivered dose to match the anatomy of the planning CT. The large deformations involved required that the bladder and rectum volume be masked with uniform intensities of -1000 and 1000 HU, respectively, in both the planning and treatment CTs. The tool was tested for five prostate IGRT patients. The average rectum planning to treatment contour overlap improved from 67% to 93%, the lowest initial overlap is 43%. The average bladder overlap improved from 83% to 98%, with a lowest initial overlap of 60%. Registration regions were set to include a volume receiving 4% of the maximum dose. The average region was 320 x 210 x 63, taking approximately 9 min to register on a dual 2.8 GHz Linux system. The prostate and seminal vesicles were correctly placed even though they are not masked. The accumulated doses for multiple fractions with large deformation were computed and verified. The tool developed can effectively supply the previously delivered dose for adaptive planning to correct for interfractional changes.
authors.affiliation: Department of Radiation Oncology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, Wisconsin 53226, USA. agodley@mcw.edu
authors.forename: Andrew
authors.initials: A
authors.lastname: Godley
authors.forename: Ergun
authors.initials: E
authors.lastname: Ahunbay
authors.forename: Cheng
authors.initials: C
authors.lastname: Peng
authors.forename: X Allen
authors.initials: XA
authors.lastname: Li
mesh_terms: D000465:Algorithms; D001331:Automation; D003201:Computers; D004307:Dose-Response Relationship, Radiation; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D010363:Pattern Recognition, Automated; D011467:Prostate / Q000000981:diagnostic imaging; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000532:radiotherapy*; D011857:Radiographic Image Interpretation, Computer-Assisted; D011874:Radiometry; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012984:Software