Lai-Lei Ting1, Ho-Chiao Chuang2, Ai-Ho Liao3,4, Chia-Chun Kuo1,5,6, Hsiao-Wei Yu7, Hsin-Chuan Tsai2, Der-Chi Tien2, Shiu-Chen Jeng1,8, Jeng-Fong Chiou1,7,9. 1. Department of Radiation Oncology, Taipei Medical University Hospital, Taipei, Taiwan. 2. Department of Mechanical Engineering, National Taipei University of Technology, Taipei, Taiwan. 3. Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan. 4. Department of Biomedical Engineering, National Defense Medical Center, Taipei, Taiwan. 5. Department of Radiation Oncology, Wanfang Hospital, Taipei Medical University, Taipei, Taiwan. 6. School of Health Care Administration, College of Management, Taipei Medical University, 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: An ultrasound image tracking algorithm (UITA) was combined with four-dimensional computed tomography (4DCT) to create a real-time tumor motion-conversion model. The real-time position of a lung tumor phantom based on the real-time diaphragm motion trajectories detected by ultrasound imaging in the superior-inferior (SI) and medial-lateral (ML) directions were obtained. METHODS: Three different tumor motion-conversion models were created using a respiratory motion simulation system (RMSS) combined with 4DCT. The tumor tracking error was verified using cone-beam computed tomography (CBCT). The tumor motion-conversion model was produced by using the UITA to monitor the motion trajectories of the diaphragm phantom in the SI direction, and using 4DCT to monitor the motion trajectories of the tumor phantom in the SI and ML directions over the same time period, to obtain parameters for the motion-conversion model such as the tumor center position and the amplitude and phase ratios. RESULTS: The tumor movement was monitored for 90 s using CBCT to determine the real motion trajectories of the tumor phantom and using ultrasound imaging to simultaneously record the diaphragm movement. The absolute error of the motion trajectories of the real and estimated tumor varied between 0.5 and 2.1 mm in the two directions. CONCLUSIONS: This study has demonstrated the feasibility of using ultrasound imaging to track diaphragmatic motion combined with a 4DCT tumor motion-conversion model to track tumor motion in the SI and ML directions. The proposed method makes tracking a lung tumor feasible in real time, including under different breathing conditions. 2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.
BACKGROUND: An ultrasound image tracking algorithm (UITA) was combined with four-dimensional computed tomography (4DCT) to create a real-time tumor motion-conversion model. The real-time position of a lung tumor phantom based on the real-time diaphragm motion trajectories detected by ultrasound imaging in the superior-inferior (SI) and medial-lateral (ML) directions were obtained. METHODS: Three different tumor motion-conversion models were created using a respiratory motion simulation system (RMSS) combined with 4DCT. The tumor tracking error was verified using cone-beam computed tomography (CBCT). The tumor motion-conversion model was produced by using the UITA to monitor the motion trajectories of the diaphragm phantom in the SI direction, and using 4DCT to monitor the motion trajectories of the tumor phantom in the SI and ML directions over the same time period, to obtain parameters for the motion-conversion model such as the tumor center position and the amplitude and phase ratios. RESULTS: The tumor movement was monitored for 90 s using CBCT to determine the real motion trajectories of the tumor phantom and using ultrasound imaging to simultaneously record the diaphragm movement. The absolute error of the motion trajectories of the real and estimated tumor varied between 0.5 and 2.1 mm in the two directions. CONCLUSIONS: This study has demonstrated the feasibility of using ultrasound imaging to track diaphragmatic motion combined with a 4DCT tumor motion-conversion model to track tumor motion in the SI and ML directions. The proposed method makes tracking a lung tumor feasible in real time, including under different breathing conditions. 2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.
Authors: Esben S Worm; Morten Høyer; Walther Fledelius; Jens E Nielsen; Lars P Larsen; Per R Poulsen Journal: Int J Radiat Oncol Biol Phys Date: 2012-05-01 Impact factor: 7.038
Authors: James Martin; Jamie McClelland; Connie Yip; Christopher Thomas; Clare Hartill; Shahreen Ahmad; Richard O'Brien; Ivan Meir; David Landau; David Hawkes Journal: Phys Med Biol Date: 2013-02-26 Impact factor: 3.609
Authors: Oluwaseyi M Oderinde; Shervin M Shirvani; Peter D Olcott; Gopinath Kuduvalli; Samuel Mazin; David Larkin Journal: Clin Transl Radiat Oncol Date: 2021-04-17