Capaldi Dante P I, Nano Tomi F, Zhang Hao, Skinner Lawrie B, Xing Lei
Department of Radiation Oncology, School of Medicine, Stanford University, Stanford, CA, USA.
San Francisco (UCSF) Comprehensive Cancer Centre, University of California, San Francisco, CA, USA.
Med Phys. 2020 Nov;47(11):5496-5504. doi: 10.1002/mp.14484. Epub 2020 Oct 10.
Radiation dose delivered to targets located near the upper abdomen or thorax are significantly affected by respiratory motion, necessitating large margins, limiting dose escalation. Surrogate motion management devices, such as the Real-time Position Management (RPM™) system (Varian Medical Systems, Palo Alto, CA), are commonly used to improve normal tissue sparing. Alternative to current solutions, we have developed and evaluated the feasibility of a real-time position management system that leverages the motion data from the onboard hardware of Apple iOS devices to provide patients with visual coaching with the potential to improve the reproducibility of breathing as well as improve patient compliance and reduce treatment delivery time.
The iOS application, coined the Instant Respiratory Feedback (IRF) system, was developed in Swift (Apple Inc., Cupertino, CA) using the Core-Motion library and implemented on an Apple iPhone® devices. Operation requires an iPhone®, a three-dimensional printed arm, and a radiolucent projector screen system for feedback. Direct comparison between IRF, which leverages sensor fusion data from the iPhone®, and RPM™, an optical-based system, was performed on multiple respiratory motion phantoms and volunteers. The IRF system and RPM™ camera tracking marker were placed on the same location allowing for simultaneous data acquisition. The IRF surrogate measurement of displacement was compared to the signal trace acquired using RPM™ with univariate linear regressions and Bland-Altman analysis.
Periodic motion shows excellent agreement between both systems, and subject motion shows good agreement during regular and irregular breathing motion. Comparison of IRF and RPM™ show very similar signal traces that were significantly related across all phantoms, including those motion with different amplitude and frequency, and subjects' waveforms (all r > 0.9, P < 0.0001). We demonstrate the feasibility of performing four-dimensional cone beam computed tomography using IRF which provided similar image quality as RPM™ when reconstructing dynamic motion phantom images.
Feasibility of an iOS application to provide real-time respiratory motion is demonstrated. This system generated comparable signal traces to a commercially available system and offers an alternative method to monitor respiratory motion.
输送到上腹部或胸部附近靶区的辐射剂量会受到呼吸运动的显著影响，这就需要设置较大的边界，从而限制了剂量递增。诸如实时位置管理（RPM™）系统（瓦里安医疗系统公司，加利福尼亚州帕洛阿尔托）等替代运动管理设备通常用于改善对正常组织的保护。作为当前解决方案的替代方案，我们开发并评估了一种实时位置管理系统的可行性，该系统利用苹果iOS设备的机载硬件的运动数据为患者提供视觉指导，有可能提高呼吸的可重复性，以及提高患者的依从性并减少治疗交付时间。
iOS应用程序，即即时呼吸反馈（IRF）系统，使用Core-Motion库用Swift（苹果公司，加利福尼亚州库比蒂诺）开发，并在苹果iPhone®设备上实现。操作需要一部iPhone®、一个三维打印手臂和一个用于反馈的射线可穿透投影仪屏幕系统。在多个呼吸运动体模和志愿者身上，对利用iPhone®的传感器融合数据的IRF和基于光学的系统RPM™进行了直接比较。将IRF系统和RPM™相机跟踪标记放置在同一位置，以便同时进行数据采集。使用单变量线性回归和布兰德-奥特曼分析，将IRF替代测量的位移与使用RPM™获取的信号轨迹进行比较。
周期性运动在两个系统之间显示出极好的一致性，并且在正常和不规则呼吸运动期间，受试者运动显示出良好的一致性。IRF和RPM™的比较显示出非常相似的信号轨迹，在所有体模中都具有显著相关性，包括那些具有不同幅度和频率的运动以及受试者的波形（所有r>0.9，P<0.0001）。我们证明了使用IRF进行四维锥形束计算机断层扫描的可行性，在重建动态运动体模图像时，IRF提供了与RPM™相似的图像质量。
证明了一个iOS应用程序提供实时呼吸运动的可行性。该系统生成的信号轨迹与市售系统相当，并提供了一种监测呼吸运动的替代方法。
