Radiotherapy Dose Verification with Cherenkov Light

现代放射治疗采用360度旋转机架进行治疗，该机架在患者周围产生连续弧形的X射线。该X射线束通过调整其强度和束的形状而被连续调制和成形。这导致随时间连续变化的高度适形剂量分布，使得治疗期间的剂量测定比使用静态场进行治疗时明显更复杂。目前在临床环境中没有广泛接受的4D体内剂量测定方法，我们认为激发电子的切伦科夫光发射成像可以填补这一空白。随着X射线存款剂量，产生了在组织中移动速度超过光速的高能电子：可以记录切伦科夫光的后续发射以重建4D剂量分布。切伦科夫成像因此允许辐射场在真实的时间内成像并连接到解剖标志（配准）。这将使计划剂量实际上正在输送的信心更大，从而能够实时检测并最终纠正计划剂量和输送剂量之间的差异，使临床医生有信心试验更先进的治疗方法。UCL的实验已经证明，来自放射治疗机架的放射治疗束产生可见的切伦科夫光，该切伦科夫光可以用标准的消费者数字SLR相机成像。其他研究小组已经生成了体内电影，显示了治疗过程中发出的切伦科夫光。该项目将建立在以前的工作，并展示切伦科夫成像的实时体内验证的应用。该项目开发的技术包括医学图像重建、用于模拟切伦科夫发射的基于Geant 4的蒙特卡罗模拟，以及应用深度学习技术优化切伦科夫发射的重建。

Modern radiotherapy delivers treatment with a 360 rotating gantry that produces X-rays in a continuous arc around the patient. This X-ray beam is continuously modulated and shaped by adjusting both its intensity and the shape of the beam. This results in a highly conformal dose distribution that changes continuously over time, making dosimetry during treatment significantly more complex than when treatment is delivered with static fields. There is currently no widely accepted method for 4D in-vivo dosimetry in the clinical setting, and we believe that imaging the Cherenkov light emission of excited electrons could fill that gap. As the X-rays deposit dose, energetic electrons moving faster than the speed of light in tissue are produced: the subsequent emission of Cherenkov light can be recorded to reconstruct the 4D dose distribution. Cherenkov imaging therefore allows the radiation field to be imaged in real time and connected to anatomical landmarks (registration). This will give greater confidence that the planned dose is actually being delivered, enabling real-time detection - and ultimately correction - of discrepancies between the planned and delivered dose, giving clinicians the confidence to trial more advanced therapies. Experiments at UCL have demonstrated that the radiotherapy treatment beam from a radiotherapy gantry generates visible Cherenkov light which can be imaged with a standard consumer digital SLR camera. Other groups have generated in vivo movies showing the Cherenkov light emitted as treatment progresses. This project will build on this previous work and demonstrate the application of Cherenkov imaging for real-time in-vivo verification. The techniques that are developed in this project are medical image reconstruction, Geant4-based Monte Carlo simulations which are used to simulate the Cherenkov emissions, and the application of deep-learning techniques to optimise the reconstruction of the Cherenkov emissions.