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Purpose: In this study, we aim to further evaluate the accuracy of ultrasound tracking for intra-fraction pancreatic tumor motion during radiotherapy by a phantom-based study. Methods: Twelve patients with pancreatic cancer who were treated with stereotactic body radiation therapy were enrolled in this study. The displacement points of the respiratory cycle were acquired from 4DCT and transferred to a motion platform to mimic realistic breathing movements in our phantom study. An ultrasound abdominal phantom was placed and fixed in the motion platform. The ground truth of phantom movement was recorded by tracking an optical tracker attached to this phantom. One tumor inside the phantom was the tracking target. In the evaluation of the results, the monitoring results from the ultrasound system were compared with the phantom motion results from the infrared camera. Differences between infrared monitoring motion and ultrasound tracking motion were analyzed by calculating the root-mean-square error. Results: The 82.2% ultrasound tracking motion was within a 0.5 mm difference value between ultrasound tracking displacement and infrared monitoring motion. 0.7% ultrasound tracking failed to track accurately (a difference value > 2.5 mm). These differences between ultrasound tracking motion and infrared monitored motion do not correlate with respiratory displacements, respiratory velocity, or respiratory acceleration by linear regression analysis. Conclusions: The highly accurate monitoring results of this phantom study prove that the ultrasound tracking system may be a potential method for real-time monitoring targets, allowing more accurate delivery of radiation doses.

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BACKGROUND: The reduction of the delaying effect in the respiratory motion compensation system (RMCS) is still impossible to completely correct the respiratory waveform of the human body due to each patient has a unique respiratory rate. In order to further improve the effectiveness of radiation therapy, this study evaluates our previously developed RMCS and uses the fast Fourier transform (FFT) algorithm combined with the phase lead compensator (PLC) to further improve the compensation rate (CR) of different respiratory frequencies and patterns of patients. METHODS: In this study, an algorithm of FFT automatic frequency detection was developed by using LabVIEW software, uisng FFT combined with PLC and RMCS to compensate the system delay time. Respiratory motion compensation experiments were performed using pre-recorded respiratory signals of 25 patients. During the experiment, the respiratory motion simulation system (RMSS) was placed on the RMCS, and the pre-recorded patient breathing signals were sent to the RMCS by using our previously developed ultrasound image tracking algorithm (UITA). The tracking error of the RMCS is obtained by comparing the encoder signals of the RMSS and RMCS. The compensation effect is verified by root mean squared error (RMSE) and system CR. RESULTS: The experimental results show that the patient's respiratory patterns compensated by the RMCS after using the proposed FFT combined with PLC control method, the RMSE is between 1.50-5.71 and 3.15-8.31 mm in the right-left (RL) and superior-inferior (SI) directions, respectively. CR is between 72.86-93.25% and 62.3-83.81% in RL and SI, respectively. CONCLUSIONS: This study used FFT combined with PLC control method to apply to RMCS, and used UITA for respiratory motion compensation. Under the automatic frequency detection, the best dominant frequency of the human respiratory waveform can be determinated. In radiotherapy, it can be used to compensate the tumor movement caused by respiratory motion and reduce the radiation damage and side effects of normal tissues nearby the tumor.

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PURPOSE: This study evaluates the feasibility of our previously developed Respiratory Motion Compensation System (RMCS) combined with the Phase Lead Compensator (PLC) to eliminate system delays during the compensation of respiration-induced tumor motion. The study objective is to improve the compensation effect of RMCS and the efficay of radiation therapy to reduce its side effects to the patients. MATERIAL AND METHODS: In this study, LabVIEW was used to develop the proposed software for calculating real-time adaptive control parameters, combined with PLC and RMCS for the compensation of total system delay time. Experiments of respiratory motion compensation were performed using 6 pre-recorded human respiration patterns and 7 sets of different sine waves. During the experiments, a respiratory simulation device, Respiratory Motion Simulation System (RMSS), was placed on the RMCS, and the detected target motion signals by the Ultrasound Image Tracking Algorithm (UITA) were transmitted to the RMCS, and the compensation of respiration induced motion was started. Finally, the tracking error of the system is obtained by comparing the encoder signals bwtween RMSS and RMCS. The compensation efficacy is verified by the root mean squared error (RMSE) and the system compensation rate (CR). RESULTS: The experimental results show that the calcuated CR with the simulated respiration patterns is between 42.85% ∼3.53% and 33.76% ∼2.62% in the Right-Left (RL) and Superior-Inferior (SI), respectively, after the RMCS compensation of using the adaptive control parameters in PLC. For the compensation results of human respiration patterns, the CR is between 58.95% ∼8.56% and 62.87% ∼9.05% in RL and SI, respectively. CONCLUSIONS: During the respiratory motion compensation, the influence of the delay time of the entire system (RMCS+RMSS+UITA) on the compensation effect was improved by adding an adaptive control PLC, which reduces compensation error and helps improve efficacy of radiation therapy.

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This study proposed respiratory motion compensation system (RMCS) combined with an ultrasound image tracking algorithm (UITA) to compensate for respiration-induced tumor motion during radiotherapy, and to address the problem of inaccurate radiation dose delivery caused by respiratory movement. This study used an ultrasound imaging system to monitor respiratory movements combined with the proposed UITA and RMCS for tracking and compensation of the respiratory motion. Respiratory motion compensation was performed using prerecorded human respiratory motion signals and also sinusoidal signals. A linear accelerator was used to deliver radiation doses to GAFchromic EBT3 dosimetry film, and the conformity index (CI), root-mean-square error, compensation rate (CR), and planning target volume (PTV) were used to evaluate the tracking and compensation performance of the proposed system. Human respiratory pattern signals were captured using the UITA and compensated by the RMCS, which yielded CR values of 34-78%. In addition, the maximum coronal area of the PTV ranged from 85.53 mm2 to 351.11 mm2 (uncompensated), which reduced to from 17.72 mm2 to 66.17 mm2 after compensation, with an area reduction ratio of up to 90%. In real-time monitoring of the respiration compensation state, the CI values for 85% and 90% isodose areas increased to 0.7 and 0.68, respectively. The proposed UITA and RMCS can reduce the movement of the tracked target relative to the LINAC in radiation therapy, thereby reducing the required size of the PTV margin and increasing the effect of the radiation dose received by the treatment target.

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The purpose of this study is to assess the feasibility of using the analytical technique of ultrasound images in combination with an auto tumor localization system. During respiration, the activity of breathing in and out causes organs displacement at the lower lobe of the lung, and the maximum displacement range happens in the Superior-Inferior (SI) direction. Therefore, in this study all the tumor positioning is in SI direction under respiratory compensation, in which the compensations are carried out to the organs at the lower lobe and adjacent to the lower lobe of lung.In this research, due to the processes of ultrasound imaging generation, image analysis and signal transmission, when the captured respiratory signals are sent to auto tumor localization system, there was a signal time delay. The total delay time of the entire signal transmission process was 0.254 ± 0.023 seconds (with the lowest standard deviation) after implementing a series of analyses. To compensate for this signal delay time (0.254 ± 0.023 sec), a phase lead compensator (PLC) was designed and built into the auto tumor localization system. By analyzing the impact of the delay time and the respiratory waveforms under different frequencies on the phase lead compensator, an overall system delay time can be configured. Results showed as the respiratory frequency increased, variable value ``a'' and the subsequent gain ``k'' in the controller becomes larger. Moreover, value ``a'' and ``k'' increased as the system delay time increased when the respiratory frequency was fixed. The relationship of value ``a'' and ``k'' to the respiratory frequency can be obtained by using the curve fitting method to compensate for the respiratory motion for tumor localization. Through the comparison of the uncompensated signal and the compensated signal performed by the auto tumor localization system on the simulated respiratory signal, the feasibility of using ultrasound image analysis technology combined with the developed auto tumor localization system can be evaluated. The results show that the simulated respiratory signals under different frequencies of 0.5, 0.333, 0.25, 0.2 and 0.167 Hz with phase lead compensators were improved and stabilized. The compensation rate increased to the range of 7.04$∼ $18.82%, and the final compensation rate is about 97%. Therefore the auto tumor localization system combined with the ultrasound image analysis techniques is feasible.In this study, the developed ultrasound image analysis techniques combined into the auto tumor localization system has the following four advantages: (1) It is a non-invasive way (ultrasonic images) to monitor the entire compensating process of the active respiration instead of using a C-arm (invasive) to observe the organs motion. (2) During radiation therapy, the whole treatment process can be continuous, which can save the overall treatment time. (3) It is an independent system, which can be mounted onto any treatment couch. (4) Users can operate this system easily without the need of prior complicated training process.

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