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

智能成像传感器在图像引导调强放疗中的应用

• 批准号: EP/F035985/1
• 负责人: Philip Evans
• 金额: $ 44.29万
• 依托单位: Institute of Cancer Research
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FF035985%2F1
• 关键词: Application; intelligent; imaging; sensors; image

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.

新型有源像素传感器已经在多学科综合智能成像（Mi3）项目（由联合研究委员会基础技术奖资助）下开发出来，谢菲尔德领导和癌症研究所（ICR）是合作伙伴。这将导致实现具有增强功能和集成智能的辐射传感器，用于医学成像领域的一系列成像应用。本研究旨在利用成像和探测器技术的最新发展，应用于图像引导放疗（IGRT）和调强放疗（IMRT）这两个挑战，这将有助于优化癌症治疗与放疗的剂量传递一致性。第一个挑战是提高对肺等部位移动肿瘤的剂量输送准确性。在治疗期间处理运动的最有前途的技术之一是使用IGRT与x射线透视。使用两个专用的透视装置，肿瘤运动在x射线不透明标记的帮助下连续成像。然而，该系统存在严重的问题：在肿瘤成像和确定肿瘤位置之间有一个明显的潜伏期，并且使用这种系统的不必要剂量的成本是不小的。如果要实现这些系统，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处理时间。第二个挑战是优化治疗验证，由于IMRT提供的复杂性，这是一个耗时且资源繁重的过程。包括ICR集团在内的团体率先使用电子门户成像设备进行IMRT验证。在治疗计划的动态光束传输过程中，已经提出了用于验证辐射束位置的成像解决方案，然而，在日常临床实践中尚未实现全自动验证。在此背景下，该项目将解决以下问题：考虑到当前门静脉成像设备的图像质量限制和透视系统赋予的高剂量率，是否有可能提高分数阶内肿瘤运动的跟踪精度和使用智能像素传感器的IMRT验证效率？智能传感器将具有新颖的功能，可能有助于加快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，这在提高采集速度和减少数据方面具有优势。这些功能可用于更好地利用现有的辐射，使我们能够获得所需的最少数据，以决定肿瘤标记物的位置或用于IMRT验证的野叶位置。将设计、构建和测试一个原型成像系统，以研究可以与主动像素传感器一起实施的数据采集方法，以充分优化图像采集，从而使门户/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优化跟踪方法将首先通过开发可在图像传感器内实现的跟踪算法，通过模拟该硬件过程并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。

项目成果

Imaging of moving fiducial markers during radiotherapy using a fast, efficient active pixel sensor based EPID.

使用基于 EPID 的快速、高效有源像素传感器对放射治疗期间移动基准标记进行成像。

• DOI: 10.1118/1.3651632
• 发表时间: 2011
• 期刊: Medical physics
• 影响因子: 3.8
• 作者: Osmond JP

DynAMITe: a wafer scale sensor for biomedical applications

• DOI: 10.1088/1748-0221/6/12/c12064
• 发表时间: 2011-12-01
• 期刊: JOURNAL OF INSTRUMENTATION
• 影响因子: 1.3
• 作者: Esposito, M.;Anaxagoras, T.;Allinson, N. M.
• 通讯作者: Allinson, N. M.

High-speed tracking of moving radio-opaque markers during radiotherapy using a CMOS active pixel sensor

使用 CMOS 有源像素传感器在放射治疗期间高速跟踪移动的不透射线标记

• 作者: John Osmond (Author)

Proton-counting radiography for proton therapy: a proof of principle using CMOS APS technology.

• DOI: 10.1088/0031-9155/59/11/2569
• 发表时间: 2014-06-07
• 期刊: Physics in medicine and biology
• 影响因子: 3.5
• 作者: Poludniowski G;Allinson NM;Anaxagoras T;Esposito M;Green S;Manolopoulos S;Nieto-Camero J;Parker DJ;Price T;Evans PM
• 通讯作者: Evans PM

An automatic method for the tracking of implanted fiducial markers in lung tumours: a phantom study

追踪肺部肿瘤中植入的基准标记的自动方法：一项模型研究

• 作者: Gio Lupica (Author)