Automated diaphragm motion tracking using optical surface monitoring system and X-ray fluoroscopic image(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2022年第12期
- Page:
- 1453-1459
- Research Field:
- 医学放射物理
- Publishing date:
Info
- Title:
- Automated diaphragm motion tracking using optical surface monitoring system and X-ray fluoroscopic image
- Author(s):
- TAN Xiang; DAI Zhenhui; HE Qiang; ZHANG Bailin; ZHU Lin; CAI Chunya; YANG Geng; JIAN Wanwei; WANG Xuetao
- Department of Radiation Therapy, the Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510006, China
- Keywords:
- Keywords: diaphragm tracking artificial intelligence optical surface monitoring system fluoroscopic image
- PACS:
- R815.2
- DOI:
- DOI:10.3969/j.issn.1005-202X.2022.12.001
- Abstract:
- Abstract: Objective To establish an automated diaphragm apex motion tracking model with artificial intelligence based on the optical surface monitoring system of linear accelerator and X-ray fluoroscopic image. Methods The optical surface motion information and kV X-ray fluoroscopic images of the thoracic and abdominal regions in 7 patients with liver tumors were acquired synchronously. The principal component analysis combined with partial least squares regression was used to calculate the correlation coefficients between several body surface regions of interest and diaphragm motion in 3 patients from 7 patients, and the body surface region of interest with the largest correlation coefficient was selected as the optical surface monitoring area. After automatically identifying the position of the diaphragm apex in the fluoroscopic images using fully convolutional neural network model, the correlation model between the body surface and the diaphragm apex motion was established with random forest method to predict the trajectory of the diaphragm apex in real time based on the body surface motion information. The accuracy of the established model was assessed by comparing the automatically tracked diaphragm apex position with the position manually drawn by the radiation oncologist. Results The mean correlation coefficient between body surface regions of interest and diaphragm motion in the 3 patients reached a maximum of (0.73±0.01) mm in the anterior-posterior direction, and a maximum of (0.88±0.01) mm in the superior-inferior direction. The mean absolute error and root mean square error between the predicted results of the automated tracking model and the manually delineated position were (3.09±0.79) mm and (3.89±0.89) mm in superior-inferior direction, (1.42±0.43) mm and (1.78±0.46) mm in anterior-posterior direction. Conclusion The body surface respiratory motion is associated with the internal diaphragm motion. The diaphragm apex motion can be tracked in real time using the optical surface motion information during radiotherapy, and the technique can be used for real time and non-invasive motion management of tumor near the diaphragm during radiotherapy of thoracic and abdominal tumors.
Last Update: 2022-12-23