Chen Xiaolin,Xie Yangchao,Lin Xingfu,Huang Fenpen,Chen Tingying,Chen Wanquan,Wang Shaofeng.Application of machine vision in fractionated radiotherapy[J].Chinese Journal of Radiological Medicine and Protection,2024,44(3):202-206
Application of machine vision in fractionated radiotherapy
Received:June 27, 2023  
DOI:10.3760/cma.j.cn112271-20230627-00212
KeyWords:Machine vision  Radiotherapy  Real-time monitoring  Set-up errors
FundProject:厦门市科技计划项目(3502Z20209171)
Author NameAffiliationE-mail
Chen Xiaolin Department of Radiation Oncology, the Second Affiliated Hospital of Xiamen Medical College, Xiamen 361021, China  
Xie Yangchao Department of Radiation Oncology, the Second Affiliated Hospital of Xiamen Medical College, Xiamen 361021, China  
Lin Xingfu Department of Radiation Oncology, the Second Affiliated Hospital of Xiamen Medical College, Xiamen 361021, China  
Huang Fenpen Department of Radiation Oncology, the Second Affiliated Hospital of Xiamen Medical College, Xiamen 361021, China  
Chen Tingying Department of Radiation Oncology, the Second Affiliated Hospital of Xiamen Medical College, Xiamen 361021, China  
Chen Wanquan Department of Radiation Oncology, the Second Affiliated Hospital of Xiamen Medical College, Xiamen 361021, China  
Wang Shaofeng Department of Radiation Oncology, the Second Affiliated Hospital of Xiamen Medical College, Xiamen 361021, China 329988105@qq.com 
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Abstract::
      Objective To monitor intra-fractional set-up errors in tumor radiotherapy using a real-time intelligent capture system for precision displacement. Methods A simulated radiotherapy environment was created in both the laboratory and the treatment room. A three-axis (xyz) displacement platform (LD60-LM) and dial gauges were used as displacement measurement tools. Moreover, a real-time intelligent capture system for precision displacement was developed for displacement monitoring. With 23 patients treated with radiotherapy enrolled in this study, the above system was employed to monitor their intra-fractional set-up errors in fractionated radiotherapy. Descriptive analyses were conducted on the deviations between the data captured by cameras and the actual displacement, obtaining the mean values and standard deviation. Results The monitoring calibration data from the laboratory revealed displacement differences of ≤ 0.5 mm within 20 mm and a maximum displacement difference of 1.47 mm for 50 mm. In contrast, the calibration result from the treatment room exhibited deviations of ± 0.2 mm on the y-z axes, as displayed by both the left and right cameras, and ± 0.31 mm on the x-z axes, as displayed by the middle camera. During 37 radiotherapy sessions in 23 patients, the monitoring result from the middle camera revealed five deviations exceeding the threshold of 5 mm, with the maximum deviation duration and displacement of 57.2 s and 9.24 mm, respectively. Conclusions The real-time intelligent capture system for precision displacement based on machine vision can achieve real-time monitoring of set-up errors during tumor radiotherapy. Nevertheless, further improvements and service testing are necessary for this system.
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