1
|
Kuo CC, Chuang HC, Liao AH, Yu HW, Cai SR, Tien DC, Jeng SC, Chiou JF. Fast Fourier transform combined with phase leading compensator for respiratory motion compensation system. Quant Imaging Med Surg 2020; 10:907-920. [PMID: 32489916 DOI: 10.21037/qims.2020.03.19] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
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.
Collapse
Affiliation(s)
- Chia-Chun Kuo
- Department of Radiation Oncology, Taipei Medical University Hospital, Taipei, Taiwan.,Department of Radiation Oncology, Wanfang Hospital, Taipei Medical University, Taipei, Taiwan.,School of Health Care Administration, College of Management, Taipei Medical University, Taipei, Taiwan
| | - Ho-Chiao Chuang
- Department of Mechanical Engineering, National Taipei University of Technology, Taipei, Taiwan
| | - Ai-Ho Liao
- Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.,Department of Biomedical Engineering, National Defense Medical Center, Taipei, Taiwan
| | - Hsiao-Wei Yu
- Taipei Cancer Center, Taipei Medical University, Taipei, Taiwan
| | - Syue-Ru Cai
- Department of Mechanical Engineering, National Taipei University of Technology, Taipei, Taiwan
| | - Der-Chi Tien
- Department of Mechanical Engineering, National Taipei University of Technology, Taipei, Taiwan
| | - Shiu-Chen Jeng
- Department of Radiation Oncology, Taipei Medical University Hospital, Taipei, Taiwan.,School of Dentistry, College of Oral Medicine, Taipei Medical University, Taipei, Taiwan
| | - Jeng-Fong Chiou
- Department of Radiation Oncology, Taipei Medical University Hospital, Taipei, Taiwan.,Taipei Cancer Center, Taipei Medical University, Taipei, Taiwan.,Department of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| |
Collapse
|
2
|
A Novel Markerless Lung Tumor-Tracking Method Using Treatment MV Beam Imaging. APPLIED SCIENCES-BASEL 2018. [DOI: 10.3390/app8122525] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
A novel method was developed to track lung tumor motion in real time during radiation therapy with the purpose to allow target radiation dose escalation while simultaneously reducing the dose to sensitive structures, thereby increasing local control without increasing toxicity. This method analyzes beam’s eye view radiation therapy treatment megavoltage (MV) images with simulated digitally reconstructed radiographs (DRRs) as references. Instead of comparing global DRRs with projection images, this method incorporates a technique that divides the global composite DRR and the corresponding MV projection into sub-images called tiles. Registration is performed independently on tile pairs in order to reduce the effects of global discrepancies due to scattering or imaging modality differences. This algorithm was evaluated by phantom studies while simulated tumors were controlled to move with various patterns in a complex humanoid torso. Approximately 15,000 phantom MV images were acquired at nine gantry angles, with different tumors moving within ranges between 10 and 20 mm. Tumors were successfully identified on every projection with a total maximum/average error of 1.84/0.98 mm. This algorithm was also applied to over 5,000 frames of MV projections acquired during radiation therapy of five lung cancer patients. This tumor-tracking methodology is capable of accurately locating lung tumors during treatment without implanting any internal fiducial markers nor delivering extra imaging radiation doses.
Collapse
|
3
|
Ichiji K, Yoshida Y, Homma N, Zhang X, Bukovsky I, Takai Y, Yoshizawa M. A key-point based real-time tracking of lung tumor in x-ray image sequence by using difference of Gaussians filtering and optical flow. ACTA ACUST UNITED AC 2018; 63:185007. [DOI: 10.1088/1361-6560/aada71] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
|