Clinical Experience of Intrafractional Motion Monitoring of Patients Under Head and Neck Radiation Therapy Using ExacTrac Dynamic System

ADVANCES IN RADIATION ONCOLOGY(2024)

引用 0|浏览0
暂无评分
摘要
Purpose: The combination of surface-guided radiation therapy (SGRT) and image-guided radiation therapy (IGRT) can provide complementary information of patient positioning throughout treatments. The ExacTrac Dynamic (EXTD) system is a combined SGRT and IGRT system that can provide real-time motion detection via optical surface and thermal tracking during treatment delivery, with stereoscopic x-ray for positional verification. The purpose of this study was to examine the performance of EXTD for intrafractional motion monitoring using real clinical cases. Methods and Materials: Treatment log files exported from EXTD for 40 patients with 335 fractions were retrospectively analyzed. Frequency of beam-hold triggered during treatments were recorded, with the comparison of shifts detected by optical surface tracking (EXTD_Thml) and x-ray verification (EXTD_Xray). Results: Among the 335 fractions, automatic beam-holds were triggered 41 times, followed by x-ray positional verification with internal anatomy. The difference of shifts detected by EXTD_Thml and EXTD_Xray were less than 1 mm and 1 degrees in translational and rotational directions, respectively. After x-ray verification, none of them required the application of positional correction. Conclusions: The availability of x-ray imaging with optical surface tracking in EXTD is essential to verify whether geometric shifts are required to correct patient position. Considering the ability of continuous monitoring of patient positions with optical surface tracking and internal imaging, EXTD is an effective tool for intrafractional motion monitoring during radiation therapy. (c) 2023 The Author(s). Published by Elsevier Inc. on behalf of American Society for Radiation Oncology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要