Radiotherapy Dose Verification with Cherenkov Light

现代放射治疗通过360度旋转机架提供治疗，该机架在患者周围产生连续弧形的X射线。这种X射线束通过调整其强度和光束形状来连续调制和整形。这导致了高度共形的剂量分布，随着时间的推移不断变化，使得治疗过程中的剂量测定比使用静电场进行治疗时要复杂得多。目前临床上还没有被广泛接受的4D体内剂量测量方法，我们相信成像激发电子的切伦科夫光发射可以填补这一空白。当X射线沉积剂量时，会产生比组织中光速更快的高能电子：随后的切伦科夫光发射可以被记录下来，以重建4D剂量分布。因此，切伦科夫成像允许对辐射场进行实时成像，并与解剖地标连接(配准)。这将增强对计划剂量实际正在交付的信心，使计划和交付剂量之间的差异能够实时检测-并最终得到纠正，从而使临床医生有信心试验更先进的疗法。伦敦大学学院的实验证明，从放射治疗机架发出的放射治疗光束可以产生可见的切伦科夫光，可以用标准的消费类数字单反相机进行成像。其他小组已经制作了活体视频，显示了随着治疗的进行切伦科夫光发出的情况。该项目将在以前工作的基础上，演示切伦科夫成像在实时活体验证中的应用。该项目开发的技术包括医学图像重建、用于模拟切伦科夫辐射的基于Geant4的蒙特卡罗模拟，以及应用深度学习技术优化切伦科夫辐射的重建。

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.