BACKGROUND: An important issue in indirect dynamic tumor tracking with the Vero4DRT system is the accuracy of the model predictions of the internal target position based on surrogate infrared (IR) marker measurement. We investigated the predictive uncertainty of 4D modeling using an external IR marker, focusing on the effect of the target and surrogate amplitudes and periods. METHODS: A programmable respiratory motion table was used to simulate breathing induced organ motion. Sinusoidal motion sequences were produced by a dynamic phantom with different amplitudes and periods. To investigate the 4D modeling error, the following amplitudes (peak-to-peak: 10-40 mm) and periods (2-8 s) were considered. The 95th percentile 4D modeling error (4D-E95%) between the detected and predicted target position (μ + 2SD) was calculated to investigate the 4D modeling error. RESULTS: 4D-E95% was linearly related to the target motion amplitude with a coefficient of determination R2 = 0.99 and ranged from 0.21 to 0.88 mm. The 4D modeling error ranged from 1.49 to 0.14 mm and gradually decreased with increasing target motion period. CONCLUSIONS: We analyzed the predictive error in 4D modeling and the error due to the amplitude and period of target. 4D modeling error substantially increased with increasing amplitude and decreasing period of the target motion.
BACKGROUND: An important issue in indirect dynamic tumor tracking with the Vero4DRT system is the accuracy of the model predictions of the internal target position based on surrogate infrared (IR) marker measurement. We investigated the predictive uncertainty of 4D modeling using an external IR marker, focusing on the effect of the target and surrogate amplitudes and periods. METHODS: A programmable respiratory motion table was used to simulate breathing induced organ motion. Sinusoidal motion sequences were produced by a dynamic phantom with different amplitudes and periods. To investigate the 4D modeling error, the following amplitudes (peak-to-peak: 10-40 mm) and periods (2-8 s) were considered. The 95th percentile 4D modeling error (4D-E95%) between the detected and predicted target position (μ + 2SD) was calculated to investigate the 4D modeling error. RESULTS: 4D-E95% was linearly related to the target motion amplitude with a coefficient of determination R2 = 0.99 and ranged from 0.21 to 0.88 mm. The 4D modeling error ranged from 1.49 to 0.14 mm and gradually decreased with increasing target motion period. CONCLUSIONS: We analyzed the predictive error in 4D modeling and the error due to the amplitude and period of target. 4D modeling error substantially increased with increasing amplitude and decreasing period of the target motion.
Entities:
Keywords:
Correlation model; IR tracking; Predictive uncertainty; Respiratory surrogates; Vero4DRT
Authors: P Giraud; M Antoine; A Larrouy; B Milleron; P Callard; Y De Rycke; M F Carette; J C Rosenwald; J M Cosset; M Housset; E Touboul Journal: Int J Radiat Oncol Biol Phys Date: 2000-11-01 Impact factor: 7.038
Authors: H Shirato; S Shimizu; T Kunieda; K Kitamura; M van Herk; K Kagei; T Nishioka; S Hashimoto; K Fujita; H Aoyama; K Tsuchiya; K Kudo; K Miyasaka Journal: Int J Radiat Oncol Biol Phys Date: 2000-11-01 Impact factor: 7.038
Authors: D Mah; J Hanley; K E Rosenzweig; E Yorke; L Braban; C C Ling; S A Leibel; G Mageras Journal: Int J Radiat Oncol Biol Phys Date: 2000-11-01 Impact factor: 7.038
Authors: Paul J Keall; Gig S Mageras; James M Balter; Richard S Emery; Kenneth M Forster; Steve B Jiang; Jeffrey M Kapatoes; Daniel A Low; Martin J Murphy; Brad R Murray; Chester R Ramsey; Marcel B Van Herk; S Sastry Vedam; John W Wong; Ellen Yorke Journal: Med Phys Date: 2006-10 Impact factor: 4.071