Chia-Chun Kuo1,2,3, Ho-Chiao Chuang4, Ai-Ho Liao5,6, Hsiao-Wei Yu7, Syue-Ru Cai4, Der-Chi Tien4, Shiu-Chen Jeng1,8, Jeng-Fong Chiou1,7,9. 1. Department of Radiation Oncology, Taipei Medical University Hospital, Taipei, Taiwan. 2. Department of Radiation Oncology, Wanfang Hospital, Taipei Medical University, Taipei, Taiwan. 3. School of Health Care Administration, College of Management, Taipei Medical University, Taipei, Taiwan. 4. Department of Mechanical Engineering, National Taipei University of Technology, Taipei, Taiwan. 5. Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. 6. Department of Biomedical Engineering, National Defense Medical Center, Taipei, Taiwan. 7. Taipei Cancer Center, Taipei Medical University, Taipei, Taiwan. 8. School of Dentistry, College of Oral Medicine, Taipei Medical University, Taipei, Taiwan. 9. Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
Abstract
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. 2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.
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. 2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.
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