title: On the automated definition of mobile target volumes from 4D-CT images for stereotactic body radiotherapy.
abstract: Stereotactic body radiotherapy (SBRT) can be used to treat small lesions in the chest. A vacuum-based immobilization system is used in our clinic for SBRT, and a motion envelope is used in treatment planning. The purpose of this study is to automatically derive motion envelopes using deformable image registration of 4D-CT images, and to assess the effect of abdominal pressure on the motion envelopes. 4D-CT scans at ten phases were acquired prior to treatment for both free and restricted breathing using a vacuum-based immobilization system that includes an abdominal pressure pillow. To study the stability of the motion envelope over the course of treatment, a mid-treatment 4D-CT scan was obtained after delivery of the third fraction for two patients. The planning target volume excluding breathing motion (PTV(ex)) was defined on the image set at full exhalation phase and transformed into all other phases using displacement maps from deformable image registration. The motion envelope was obtained as the union of PTV(ex) masks of all phases. The ratios of the motion envelope to PTV(ex) volume ranged from 1.3 to 2.5. When pressure was applied, the ratios were reduced by as much as 29% compared to free breathing for some patients, but increased by up to 9% for others. The abdominal pressure pillow has more motion restriction effects on the anterior/inferior region of the lung. For one of the two patients for whom the 4D-CT scan was repeated at mid-treatment, the motion envelope was reproducible. However, for the other patient the tumor location and lung motion pattern significantly changed due to changes in the anatomy surrounding the tumor during the course of treatment, indicating that an image-guided approach to SBRT may increase the efficacy of this treatment.
authors.affiliation: Department of Human Oncology, University of Wisconsin, Madison, Wisconsin 53792, USA. tiezhi.zhang@beaumont.edu
authors.forename: Tiezhi
authors.initials: T
authors.lastname: Zhang
authors.forename: Nigel P
authors.initials: NP
authors.lastname: Orton
authors.forename: Wolfgang A
authors.initials: WA
authors.lastname: Tomé
mesh_terms: D000465:Algorithms; D002289:Carcinoma, Non-Small-Cell Lung / Q000532:radiotherapy*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D008168:Lung / Q000473:pathology; D008175:Lung Neoplasms / Q000532:radiotherapy*; D015233:Models, Statistical; D009038:Motion; D009068:Movement; D010363:Pattern Recognition, Automated / Q000379:methods*; D011312:Pressure; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods; D013382:Subtraction Technique; D013997:Time Factors; D014057:Tomography, X-Ray Computed / Q000379:methods*