title: A time-varying seasonal autoregressive model-based prediction of respiratory motion for tumor following radiotherapy.
abstract: To achieve a better therapeutic effect and suppress side effects for lung cancer treatments, latency involved in current radiotherapy devices is aimed to be compensated for improving accuracy of continuous (not gating) irradiation to a respiratory moving tumor. A novel prediction method of lung tumor motion is developed for compensating the latency. An essential core of the method is to extract information valuable for the prediction, that is, the periodic nature inherent in respiratory motion. A seasonal autoregressive model useful to represent periodic motion has been extended to take into account the fluctuation of periodic nature in respiratory motion. The extended model estimates the fluctuation by using a correlation-based analysis for adaptation. The prediction performance of the proposed method was evaluated by using data sets of actual tumor motion and compared with those of the state-of-the-art methods. The proposed method demonstrated a high performance within submillimeter accuracy. That is, the average error of 1.0 s ahead predictions was 0.931 ± 0.055 mm. The accuracy achieved by the proposed method was the best among those by the others. The results suggest that the method can compensate the latency with sufficient accuracy for clinical use and contribute to improve the irradiation accuracy to the moving tumor.
authors.affiliation: Department of Electrical and Communication Engineering, Graduate School of Engineering, Tohoku University, 6-3 Aoba, Aramaki, Aoba-ku, Sendai, Miyagi 980-8578, Japan. ichiji@yoshizawa.ecei.tohoku.ac.jp
authors.forename: Kei
authors.initials: K
authors.lastname: Ichiji
authors.forename: Noriyasu
authors.initials: N
authors.lastname: Homma
authors.forename: Masao
authors.initials: M
authors.lastname: Sakai
authors.forename: Yuichiro
authors.initials: Y
authors.lastname: Narita
authors.forename: Yoshihiro
authors.initials: Y
authors.lastname: Takai
authors.forename: Xiaoyong
authors.initials: X
authors.lastname: Zhang
authors.forename: Makoto
authors.initials: M
authors.lastname: Abe
authors.forename: Norihiro
authors.initials: N
authors.lastname: Sugita
authors.forename: Makoto
authors.initials: M
authors.lastname: Yoshizawa
mesh_terms: D019295:Computational Biology; D003198:Computer Simulation; D016208:Databases, Factual; D006801:Humans; D008175:Lung Neoplasms / Q000503:physiopathology* / Q000532:radiotherapy*; D009068:Movement / Q000502:physiology; D010507:Periodicity; D011881:Radiotherapy, Computer-Assisted / Q000706:statistics & numerical data*; D012044:Regression Analysis; D012119:Respiration; D013997:Time Factors