Purpose: We performed both, dosimetric and positional accuracy verification of dynamic tumor tracking (DTT) intensity modulated radiation therapy (IMRT), with the Vero4DRT system using a moving phantom (QUASAR respira...Purpose: We performed both, dosimetric and positional accuracy verification of dynamic tumor tracking (DTT) intensity modulated radiation therapy (IMRT), with the Vero4DRT system using a moving phantom (QUASAR respiratory motion platform;QUASAR phantom) and system log files. Methods: The QUASAR phantom was placed on a treatment couch. Measurement of the point dose and dose distribution was performed for conventional IMRT, with the QUASAR phantom static and moving;for DTT IMRT, this was performed with the phantom moving for pyramid shaped, prostate, paranasal sinus, and pancreas targets. The QUASAR phantom was driven by a sinusoidal signal in the superior-inferior direction. Furthermore, predicted positional errors induced by the Vero4DRT system and mechanical positional errors of the gimbal head, were calculated using the system log files. Results and Conclusion: For DTT IMRT, the dose at the evaluation point was within 3% compared with the verification plan, and the dose distribution in the passing rates of γ was 97.9%, with the criteria of 3% dose and 3 mm distance to agreement. The position error calculated from the log files was within 2 mm, suggesting the feasibility of employing DTT IMRT with high accuracy using the Vero4DRT system.展开更多
Purpose: The purposes of this study were to estimate accumulated kV X-ray imaging dose throughout dynamic tumor tracking (DTT) irradiation by Vero 4DRT system and to address an analytical skin dose formula for well-ba...Purpose: The purposes of this study were to estimate accumulated kV X-ray imaging dose throughout dynamic tumor tracking (DTT) irradiation by Vero 4DRT system and to address an analytical skin dose formula for well-balanced kV X-ray imaging conditions between skin dose and image noise. Method: First, skin dose was measured using kV X-ray tube, chamber, and water-equivalent phantoms. Next, imaging dose for six patients in DTT treatment was computed using log files. Subsequently, scattered dose ratio was calculated by amount of ionization in front of flat panel detector (FPD) for fields with size of maximum and the chamber for 0 - 200 mm-thickness phantoms and tube voltage of 60, 80, 100, 120 kV, respectively. Furthermore, image noise was computed from FPD images. Results: The skin dose was greater by a factor of 1.4 - 1.6 than those in Synergy XVI system. The image noise in FPD, ?was expressed as N = 0.045×(1/QFPDen)0.479, where QFPDen denotes amount of ionization in front of FPD. Then, skin dose, D (N, t, v) was formulated as (0.045/N)(1/0.479)/QFPDen/mAs (t, v) ×D/mAs (v), where QFPDen/mAs (t, v) and D/mAs (v) denote amount of ionization in front of FPD and skin dose per mAs, respectively. Using the formulae, it has been demonstrated that skin dose with 120 kV has become lower than any other tube voltage in this study. Conclusion: Using skin doses for the phantom, the skin dose throughout DTT irradiation was estimated as 0.50 Gy. Furthermore, skin dose by kV X-ray imaging was described as a function of image noise, phantom thickness, and tube voltage, suggesting image noise may be reduced with higher X-ray tube voltage in this phantom study.展开更多
Fiducial marker detection algorithms in kilovoltage x-ray images using physical characteristics of transmission x-ray have been proposed. It, however, has been suggested recently that factors besides transmission x-ra...Fiducial marker detection algorithms in kilovoltage x-ray images using physical characteristics of transmission x-ray have been proposed. It, however, has been suggested recently that factors besides transmission x-ray affect x-ray images. The purpose of this study was to develop a new fiducial detection algorithm using fiducial intensity estimation based on physical characteristics of x-ray images with gold fiducials. First, x-ray images of a fiducial on a water-equivalent phantom were acquired. It was observed that the ratio of background to fiducial intensity in the images decreased as phantom thickness increased. Based on the negative correlation, we identified a function for estimating fiducial intensity that consists of background intensity and the amount of scattered radiation by the other x-ray source of an orthogonal imaging system and a treatment beam. Then, we developed an algorithm that extracts fiducial candidates using the estimation function. Its performance was measured using x-ray images which had 3824 fiducials altogether. The average number of false-positive detection of the proposed algorithm in single image was one-tenth of an algorithm considering only transmission x-ray. The proposed algorithm detected 99.5% of all fiducials under an error of 1.0 mm, while the other algorithm detected 94.7% or less (Clinical trial number: UMIN000005324).展开更多
文摘Purpose: We performed both, dosimetric and positional accuracy verification of dynamic tumor tracking (DTT) intensity modulated radiation therapy (IMRT), with the Vero4DRT system using a moving phantom (QUASAR respiratory motion platform;QUASAR phantom) and system log files. Methods: The QUASAR phantom was placed on a treatment couch. Measurement of the point dose and dose distribution was performed for conventional IMRT, with the QUASAR phantom static and moving;for DTT IMRT, this was performed with the phantom moving for pyramid shaped, prostate, paranasal sinus, and pancreas targets. The QUASAR phantom was driven by a sinusoidal signal in the superior-inferior direction. Furthermore, predicted positional errors induced by the Vero4DRT system and mechanical positional errors of the gimbal head, were calculated using the system log files. Results and Conclusion: For DTT IMRT, the dose at the evaluation point was within 3% compared with the verification plan, and the dose distribution in the passing rates of γ was 97.9%, with the criteria of 3% dose and 3 mm distance to agreement. The position error calculated from the log files was within 2 mm, suggesting the feasibility of employing DTT IMRT with high accuracy using the Vero4DRT system.
文摘Purpose: The purposes of this study were to estimate accumulated kV X-ray imaging dose throughout dynamic tumor tracking (DTT) irradiation by Vero 4DRT system and to address an analytical skin dose formula for well-balanced kV X-ray imaging conditions between skin dose and image noise. Method: First, skin dose was measured using kV X-ray tube, chamber, and water-equivalent phantoms. Next, imaging dose for six patients in DTT treatment was computed using log files. Subsequently, scattered dose ratio was calculated by amount of ionization in front of flat panel detector (FPD) for fields with size of maximum and the chamber for 0 - 200 mm-thickness phantoms and tube voltage of 60, 80, 100, 120 kV, respectively. Furthermore, image noise was computed from FPD images. Results: The skin dose was greater by a factor of 1.4 - 1.6 than those in Synergy XVI system. The image noise in FPD, ?was expressed as N = 0.045×(1/QFPDen)0.479, where QFPDen denotes amount of ionization in front of FPD. Then, skin dose, D (N, t, v) was formulated as (0.045/N)(1/0.479)/QFPDen/mAs (t, v) ×D/mAs (v), where QFPDen/mAs (t, v) and D/mAs (v) denote amount of ionization in front of FPD and skin dose per mAs, respectively. Using the formulae, it has been demonstrated that skin dose with 120 kV has become lower than any other tube voltage in this study. Conclusion: Using skin doses for the phantom, the skin dose throughout DTT irradiation was estimated as 0.50 Gy. Furthermore, skin dose by kV X-ray imaging was described as a function of image noise, phantom thickness, and tube voltage, suggesting image noise may be reduced with higher X-ray tube voltage in this phantom study.
文摘Fiducial marker detection algorithms in kilovoltage x-ray images using physical characteristics of transmission x-ray have been proposed. It, however, has been suggested recently that factors besides transmission x-ray affect x-ray images. The purpose of this study was to develop a new fiducial detection algorithm using fiducial intensity estimation based on physical characteristics of x-ray images with gold fiducials. First, x-ray images of a fiducial on a water-equivalent phantom were acquired. It was observed that the ratio of background to fiducial intensity in the images decreased as phantom thickness increased. Based on the negative correlation, we identified a function for estimating fiducial intensity that consists of background intensity and the amount of scattered radiation by the other x-ray source of an orthogonal imaging system and a treatment beam. Then, we developed an algorithm that extracts fiducial candidates using the estimation function. Its performance was measured using x-ray images which had 3824 fiducials altogether. The average number of false-positive detection of the proposed algorithm in single image was one-tenth of an algorithm considering only transmission x-ray. The proposed algorithm detected 99.5% of all fiducials under an error of 1.0 mm, while the other algorithm detected 94.7% or less (Clinical trial number: UMIN000005324).
