PURPOSE: To apply digital fluoroscopy integrated with CT simulation to measure lung tumor motion and aid in the quantification of individualized planning target volumes. METHODS AND MATERIALS: A flat panel digital fluoroscopy unit was modified and integrated with a CT simulator. The stored fluoroscopy images were overlaid with digitally reconstructed radiographs, allowing measurement of the observed lung tumor motion in relation to the corresponding contours on the static digitally reconstructed radiographs. CT simulation and digital fluoroscopy was performed on 10 patients with non-small-cell lung cancer. Actual tumor motion was measured in three dimensions using the overlaid images. RESULTS: Combining the dynamic data with digitally reconstructed radiographs allowed the tumor shadow from the fluoroscopy to be tracked in relation to the CT lung tumor contour. For all patients, the extent of tumor motion in three dimensions was unique. The motion was greatest in the superoinferior direction and minimal in the AP and lateral directions. CONCLUSION: We have developed a tool that allows CT simulation to be combined with digital fluoroscopy. Quantitative evaluation of the tumor motion in relation to the CT plan allows for customization of the planning target volume. The variability observed clearly demonstrates the need to generate patient-specific internal motion margins.
PURPOSE: To apply digital fluoroscopy integrated with CT simulation to measure lung tumor motion and aid in the quantification of individualized planning target volumes. METHODS AND MATERIALS: A flat panel digital fluoroscopy unit was modified and integrated with a CT simulator. The stored fluoroscopy images were overlaid with digitally reconstructed radiographs, allowing measurement of the observed lung tumor motion in relation to the corresponding contours on the static digitally reconstructed radiographs. CT simulation and digital fluoroscopy was performed on 10 patients with non-small-cell lung cancer. Actual tumor motion was measured in three dimensions using the overlaid images. RESULTS: Combining the dynamic data with digitally reconstructed radiographs allowed the tumor shadow from the fluoroscopy to be tracked in relation to the CT lung tumor contour. For all patients, the extent of tumor motion in three dimensions was unique. The motion was greatest in the superoinferior direction and minimal in the AP and lateral directions. CONCLUSION: We have developed a tool that allows CT simulation to be combined with digital fluoroscopy. Quantitative evaluation of the tumor motion in relation to the CT plan allows for customization of the planning target volume. The variability observed clearly demonstrates the need to generate patient-specific internal motion margins.
Authors: R Caivano; S Clemente; A Fiorentino; C Chiumento; P Pedicini; G Califano; M Cozzolino; V Fusco Journal: Clin Transl Oncol Date: 2013-01-24 Impact factor: 3.405
Authors: Jeffrey R Olsen; Wei Lu; James P Hubenschmidt; Michelle M Nystrom; Paul Klahr; Jeffrey D Bradley; Daniel A Low; Parag J Parikh Journal: Int J Radiat Oncol Biol Phys Date: 2007-11-26 Impact factor: 7.038
Authors: John H Heinzerling; Ross Bland; John C Mansour; Roderich E Schwarz; Ezequiel Ramirez; Chuxiong Ding; Ramzi Abdulrahman; Thomas P Boike; Timothy Solberg; Robert D Timmerman; Jeffrey J Meyer Journal: Radiat Oncol Date: 2011-10-28 Impact factor: 3.481
Authors: Yan Wang; Yong Bao; Li Zhang; Wei Fan; Han He; Zong-Wen Sun; Xiao Hu; Shao-Min Huang; Ming Chen; Xiao-Wu Deng Journal: Biomed Res Int Date: 2013-06-04 Impact factor: 3.411