Accuracy of a time-of-flight (ToF) imaging system for monitoring deep-inspiration breath-hold radiotherapy (DIBH-RT) for left breast cancer patients

用于监测左侧乳腺癌患者深吸气屏气放射治疗(DIBH-RT)的飞行时间(ToF)成像系统的准确性

阅读:1

Abstract

Deep inspiration breath-hold radiotherapy (DIBH-RT) reduces cardiac dose by over 50%. However, poor breath-hold reproducibility could result in target miss which compromises the treatment success. This study aimed to benchmark the accuracy of a Time-of-Flight (ToF) imaging system for monitoring breath-hold during DIBH-RT. The accuracy of an Argos P330 3D ToF camera (Bluetechnix, Austria) was evaluated for patient setup verification and intra-fraction monitoring among 13 DIBH-RT left breast cancer patients. The ToF imaging was performed simultaneously with in-room cone beam computed tomography (CBCT) and electronic portal imaging device (EPID) imaging systems during patient setup and treatment delivery, respectively. Patient surface depths (PSD) during setup were extracted from the ToF and the CBCT images during free breathing and DIBH using MATLAB (MathWorks, Natick, MA) and the chest surface displacement were compared. The mean difference ± standard deviation, correlation coefficient, and limit of agreement between the CBCT and ToF were 2.88 ± 5.89 mm, 0.92, and - 7.36, 1.60 mm, respectively. The breath-hold stability and reproducibility were estimated using the central lung depth extracted from the EPID images during treatment and compared with the PSD from the ToF. The average correlation between ToF and EPID was - 0.84. The average intra-field reproducibility for all the fields was within 2.70 mm. The average intra-fraction reproducibility and stability were 3.74 mm, and 0.80 mm, respectively. The study demonstrated the feasibility of using ToF camera for monitoring breath-hold during DIBH-RT and shows good breath-hold reproducibility and stability during the treatment delivery.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。