McNutt T R, Mackie T R, Reckwerdt P, Paliwal B R
Med Phys. 1996 Aug;23(8):1381-92. doi: 10.1118/1.597872.
Post-treatment dose verification refers to the process of reconstructing delivered dose distributions internal to a patient from information obtained during the treatment. The exit dose is commonly used to describe the dose beyond the exit surface of the patient from a megavoltage photon beam. Portal imaging provides a method of determining the dose in a plane distal to a patient from a megavoltage therapeutic beam. This exit dose enables reconstruction of the dose distribution from external beam radiation throughout the patient utilizing the convolution/superposition method and an extended phantom. An iterative convolution/superposition algorithm has been created to reconstruct dose distributions in patients from exit dose measurements during a radiotherapy treatment. The method is based on an extended phantom that includes the patient CT representation and an electronic portal imaging device (EPID). The convolution/superposition method computes the dose throughout the extended phantom, which allows the portal dose image to be predicted in the EPID. The process is then reversed to take the portal dose measurement and infer what the dose distribution must have been to produce the measured portal dose. The dose distribution is modeled without knowledge of the incident intensity distribution, and includes the effects of scatter in the computation. The iterative method begins by assuming that the primary energy fluence (PEF) at the portal image plane is equal to the portal dose image, the PEF is then back-projected through the extended phantom and convolved with the dose deposition kernel to determine a new prediction of the portal dose image. The image of the ratio of the computed PEF to the computed portal dose is then multiplied by the measured portal dose image to produce a better representation of the PEF. Successive iterations of this process then converge to the exiting PEF image that would produce the measured portal dose image. Once convergence is established, the dose distribution is determined by back-projecting the PEF and convolving with the dose deposition kernel. The method is accurate, provided the patient representation during treatment is known. The method was used on three phantoms with a photon energy of 6 MV to verify convergence and accuracy of the algorithm. The reconstructed dose volumes agree to within 3% of the forward computation dose volumes. Furthermore, this technique assumes no prior knowledge of the incident fluence and therefore may better represent the dose actually delivered.
治疗后剂量验证是指根据治疗过程中获取的信息重建患者体内已交付剂量分布的过程。出射剂量通常用于描述兆伏级光子束在患者出射表面之外的剂量。门静脉成像提供了一种从兆伏级治疗束确定患者远端面剂量的方法。这种出射剂量能够利用卷积/叠加方法和扩展体模重建患者体内外照射的剂量分布。已经创建了一种迭代卷积/叠加算法，用于根据放射治疗期间的出射剂量测量重建患者体内的剂量分布。该方法基于一个扩展体模，该体模包括患者CT图像和电子门静脉成像设备（EPID）。卷积/叠加方法计算扩展体模内的剂量，从而可以在EPID中预测门静脉剂量图像。然后将该过程反过来，获取门静脉剂量测量值，并推断产生测量到的门静脉剂量所需的剂量分布。在不知道入射强度分布的情况下对剂量分布进行建模，并在计算中包括散射的影响。迭代方法首先假设门静脉图像平面处的初始能量注量（PEF）等于门静脉剂量图像，然后将PEF通过扩展体模反向投影并与剂量沉积核卷积，以确定门静脉剂量图像的新预测值。然后将计算得到的PEF与计算得到的门静脉剂量的比值图像乘以测量到的门静脉剂量图像，以更好地表示PEF。该过程的连续迭代然后收敛到能够产生测量到的门静脉剂量图像的出射PEF图像。一旦建立收敛，通过对PEF进行反向投影并与剂量沉积核卷积来确定剂量分布。如果知道治疗期间的患者图像，该方法是准确的。该方法用于三个光子能量为6 MV的体模，以验证算法的收敛性和准确性。重建的剂量体积与正向计算剂量体积的误差在3%以内。此外，该技术不假设入射注量的先验知识，因此可能更好地表示实际交付的剂量。
