title: Development of an automatic evaluation method for patient positioning error.
abstract: Highly accurate radiotherapy needs highly accurate patient positioning. At our facility, patient positioning is manually performed by radiology technicians. After the positioning, positioning error is measured by manually comparing some positions on a digital radiography image (DR) to the corresponding positions on a digitally reconstructed radiography image (DRR). This method is prone to error and can be time-consuming because of its manual nature. Therefore, we propose an automated measuring method for positioning error to improve patient throughput and achieve higher reliability. The error between a position on the DR and a position on the DRR was calculated to determine the best matched position using the block-matching method. The zero-mean normalized cross correlation was used as our evaluation function, and the Gaussian weight function was used to increase importance as the pixel position approached the isocenter. The accuracy of the calculation method was evaluated using pelvic phantom images, and the method's effectiveness was evaluated on images of prostate cancer patients before the positioning, comparing them with the results of radiology technicians' measurements. The root mean square error (RMSE) of the calculation method for the pelvic phantom was 0.23 ± 0.05 mm. The coefficients between the calculation method and the measurement results of the technicians were 0.989 for the phantom images and 0.980 for the patient images. The RMSE of the total evaluation results of positioning for prostate cancer patients using the calculation method was 0.32 ± 0.18 mm. Using the proposed method, we successfully measured residual positioning errors. The accuracy and effectiveness of the method was evaluated for pelvic phantom images and images of prostate cancer patients. In the future, positioning for cancer patients at other sites will be evaluated using the calculation method. Consequently, we expect an improvement in treatment throughput for these other sites.
authors.affiliation: Gunma University Heavy Ion Medical Center. y_kubota@gunma-u.ac.jp.
authors.forename: Yoshiki
authors.initials: Y
authors.lastname: Kubota
authors.forename: Mutsumi
authors.initials: M
authors.lastname: Tashiro
authors.forename: Ayaka
authors.initials: A
authors.lastname: Shinohara
authors.forename: Satoshi
authors.initials: S
authors.lastname: Abe
authors.forename: Saki
authors.initials: S
authors.lastname: Souda
authors.forename: Ryosuke
authors.initials: R
authors.lastname: Okada
authors.forename: Takayoshi
authors.initials: T
authors.lastname: Ishii
authors.forename: Tatsuaki
authors.initials: T
authors.lastname: Kanai
authors.forename: Tatsuya
authors.initials: T
authors.lastname: Ohno
authors.forename: Takashi
authors.initials: T
authors.lastname: Nakano
mesh_terms: D000465:Algorithms; D001331:Automation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D056888:Patient Positioning; D010388:Pelvis / Q000000981:diagnostic imaging; D019047:Phantoms, Imaging; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D011879:Radiotherapy Dosage; D061106:Radiotherapy Setup Errors / Q000517:prevention & control*; D014057:Tomography, X-Ray Computed / Q000379:methods