Application of intelligent imaging sensors to image guided and intensity modulated radiotherapy

新型有源像素传感器是在多学科集成智能成像（Mi 3）项目（由联合研究理事会基础技术奖资助）下开发的，该项目由谢菲尔德领导，癌症研究所（ICR）是合作伙伴。这将导致实现具有增加的功能和集成智能的辐射传感器，用于医学成像领域内的一系列成像应用。这项拟议的研究旨在利用成像和探测器技术的最新发展，以应对图像引导放射治疗（IGRT）和调强放射治疗（IMRT）中的两个挑战，这将有助于优化放射治疗癌症中剂量输送的适形性。第一个挑战是提高对诸如肺等部位中的移动肿瘤的剂量递送准确性。在治疗过程中处理运动的最有前途的技术之一是采用IGRT和X射线透视。使用两个专用的荧光透视装置，在X射线不透射线标记的帮助下连续成像肿瘤运动。然而，该系统存在严重的问题：在肿瘤被成像的时间和肿瘤位置的识别之间存在显著的等待时间段，并且在不想要的剂量方面使用这种系统的成本是不小的。如果要实现这些系统，则必须使用较低的辐射强度，这不可避免地导致较差的图像质量和较低的跟踪精度。较低的跟踪精度将导致更多的错误或不切实际的治疗时间。第二个挑战是优化治疗验证，由于调强放射治疗的复杂性，这是一个耗时的过程，因此需要大量资源。包括ICR集团在内的一些集团率先使用电子射野成像设备进行IMRT验证。在动态射束输送过程中验证放射束相对于治疗计划的位置的成像解决方案已经提出，但是，在日常临床实践中尚未实施全自动验证。正是在这种背景下，该项目将解决以下问题：考虑到当前射野成像装置的图像质量限制和由荧光透视系统赋予的高剂量率，使用智能像素传感器提高分次内肿瘤运动的跟踪精度和IMRT验证的效率是否可行？智能传感器将被构建，具有新的功能，可能有助于加速IMRT验证和优化跟踪过程。例如，这些传感器将具有感兴趣区域读出和自触发检测器读出，其具有提高采集速度和数据减少的优点。这些功能可用于更好地利用可用的辐射，使我们能够获取所需的最小量的数据，以做出关于肿瘤标记物位置或射野叶位置的决策，用于IMRT验证。将设计、构建和测试原型成像系统，以研究可使用有源像素传感器实施的数据采集方法，以充分优化图像采集，从而使射野/荧光透视成像成为IGRT和有效验证的可行解决方案。通过使用智能传感器的跟踪方法的优化将首先通过开发可以在图像传感器内实现的跟踪算法，通过对这种硬件过程的模拟以及通过使用新型传感器和现场可编程门阵列进行测试来进行。该项目的最后阶段将包括开发基于智能传感器的放射治疗成像的概念演示器。

Novel active pixel sensors have been developed under the Multidisciplinary Integrated Intelligent Imaging (Mi3) Project (funded by a Joint Research Council Basic Technology Award), which Sheffield leads and Institute of Cancer Research (ICR) are partners. This will lead to the realisation of radiation sensors that have increased functionality and integrated intelligence for use in a range of imaging applications within the field of medical imaging. This proposed research aims to exploit these latest developments in imaging and detector technology for application to two challenges in image guided radiotherapy (IGRT) and intensity modulated radiotherapy (IMRT), which will help the optimisation of conformality of dose delivery in cancer treatment with radiotherapy. The first challenge is to improve dose delivery accuracy to moving tumours in sites such as the lung. On of the most promising techniques for dealing with motion during treatment employs IGRT with X-ray fluoroscopy. Using two dedicated fluoroscopy units, tumour motion has been imaged continuously with the aid of X-ray radio-opaque markers. However, serious problems with this system exist: there is a significant latency period between the time at which the tumour is imaged and the identification of the tumour position and the cost of using such systems in terms of unwanted dose is non-trivial. If these systems are to be realised lower radiation intensity must be used which inevitably leads to poorer image quality and lower tracking accuracy. Lower tracking accuracy will lead to a greater number of errors or impractical treatment times. The second challenge is to optimise treatment verification, which due to the complex nature of IMRT delivery, is a time-consuming and therefore resource-heavy process. Groups, including the ICR Group, have pioneered the use of electronic portal imaging devices for IMRT verification. Imaging solutions for the verification of the position of the radiation beam during dynamic beam delivery with respect to the treatment plan have been presented, however, fully automated verification has yet to be implemented in day-to-day clinical practice.It is against this background that the project will address the question: given the image quality limitations of current portal imaging devices and the high dose rates imparted by fluoroscopic systems, is it feasible to increase tracking accuracy of intra-fractional tumour motion and the efficiency of IMRT verification using intelligent pixels sensors? Intelligent sensors will be built that have novel functionality that will potentially be useful for speeding up IMRT verification and optimising the tracking process. For example, these sensors will have region of interest read out and self-triggered detector read out that have advantages for increased speed of acquisition and data reduction. These functions can be used to make better use of the radiation available allowing us to acquire the minimum amount of data required to make decisions regarding tumour marker position or field leaf position for IMRT verification. A prototype imaging system will be designed, constructed and tested in order to investigate data acquisition methods that can be implemented with active pixel sensors to fully optimise image acquisition and hence make portal/fluoroscopic imaging a viable solution for IGRT and efficient verification. Optimisation of tracking methods through the use of intelligent sensors will be carried out firstly through the development of tracking algorithms that can be implemented within the image sensor, through simulation of this hard ware processes and through testing using the novel sensors and field programmable gate arrays. The final stage of this project will include the development of a concept demonstrator for intelligent sensor based radiotherapy imaging.