Optimized CyberKnife Lung Treatment: Effect of Fractionated Tracking Volume Change on Tracking Results. (11th January 2020)

• Record Type: Journal Article
• Authors: Li, Guo-quan; Wang, Ye; Qiu, Meng-jun; Yang, Jing; Peng, Zhen-jun; Zhang, Sheng; Fang, Xiefan; Yang, Sheng-li
• Other Names: Shi Zhongjie Guest Editor.
• Is Part Of: Disease markers. Volume 2020(2020)
• Publication Date: 2020-01-11
• Subjects: Diagnosis -- Periodicals; Biochemical markers -- Periodicals; Pathology -- Periodicals; 616
• DOI: 10.1155/2020/9298263
• Languages: English
• ISSNs: 0278-0240

Abstract

Abstract : Objectives . To explore the impact of volume change in the fractionated tracking of stereotactic radiotherapy on the results of synchronous, respiratory tracking algorithm using CyberKnife. Methods . A total of 38 lung tumor patients receiving stereotactic radiotherapy at our center from March 2018 to October 2019 were counted. Photoshop CS4 image processing software was used to obtain the pixels and the average value of brightness of the tracking volume in the image and calculate the grayscale within the contour of the tracking volume on the real-time X-ray image. At the same time, parameters of the synchronous respiratory tracking algorithm of the fractional CyberKnife were extracted for comparison between the volume of image-guided image tracking and the number of fractions during stereotactic radiotherapy. We also analyzed the relationship between fraction tumor location and characteristics and the calculated results of synchronous respiratory tracking by CyberKnife. Results . There were no significant differences between the first four fractions (p > 0.05 ) for left lung lesions and no significant differences between the first five fractions for right lung lesions (p ≥ 0.05 ). For peripheral lung cancer, longer fractional treatment led to greater variation in grayscale (G-A: >4 fractions p < 0.05 ), while for central lung cancer, longer fractional treatment led to greater variation in parameters of the synchronous respiratory tracking algorithm (Uncertainty A and Uncertainty B: >4 fractions p < 0.05 ). There was a significant correlation between radiotherapy-graded tumor density and relevant parameters, and the correlation was strong (>0.7, p < 0.05 ). Conclusion . With the increase of treatment fractions, the gray value in the patient tracking volume decreased. Patients of >4 fractions were advised to reevaluate with simulated CT and replan. For tumors with small diameter and low density, the imaging changes of volume should be closely followed during treatment. For left lung and central lung cancer, carefully select the synchronous tracking treatment with 2-view.