■在质子治疗中,合成计算机断层扫描(sCT)是否存在争议,来自磁共振成像(MRI),允许精确的剂量计算。一方面,仅MRI工作流程可以消除由以下原因引起的错误,例如,MRI-CT配准。另一方面,由于sCT生成模型,将导致额外的错误。这项工作研究了由广泛讨论的深度学习模型的sCT生成引起的系统和随机模型误差,pix2pix.
■采用了19名骨盆癌症患者的开源图像数据集,并分为10、5和4进行训练,测试,和模型的验证,分别。在真实CT上模拟质子笔形光束(200MeV),并使用粒子模拟工具(TOPAS)生成sCT。蒙特卡罗(MC)缺失用于误差估计(50个随机sCT样本)。研究了sCT生成和sCT剂量计算的系统和随机模型误差。
■对于sCT生成,身体边缘附近的随机模型误差(〜200HU)高于身体内部的随机模型误差(在骨骼边缘附近为100HU,在软组织中<10HU)。全身平均绝对误差(MAE)为49±5,191±23,503±70HU,骨头,和病人体内的空气,分别。质子范围的随机模型误差对于所有点都很小(<0.2mm),并且在整个质子场中均匀分布。质子范围的系统误差为-1.0(±2.2)mm和0.4(±0.9)%,分别,并且在质子场中分布不均。对于4.5%的斑点,发现较大的误差(>5毫米),这可能与MRI-CT不匹配有关,例如,注册,MRI畸变解剖学改变,等。
■sCT模型被证明是稳健的,即,具有较低的随机模型误差。然而,对于未来的仅MRI质子治疗,仍需要进一步研究以减少甚至预测和管理系统误差.
UNASSIGNED: In proton therapy, it is disputed whether synthetic computed tomography (sCT), derived from magnetic resonance imaging (MRI), permits accurate dose calculations. On the one hand, an MRI-only workflow could eliminate errors caused by, e.g., MRI-CT registration. On the other hand, the extra error would be induced due to an sCT generation model. This work investigated the systematic and random model error induced by sCT generation of a widely discussed deep learning model, pix2pix.
UNASSIGNED: An open-source image dataset of 19 patients with cancer in the pelvis was employed and split into 10, 5, and 4 for training, testing, and validation of the model, respectively. Proton pencil beams (200 MeV) were simulated on the real CT and generated sCT using the tool for particle simulation (TOPAS). Monte Carlo (MC) dropout was used for error estimation (50 random sCT samples). Systematic and random model errors were investigated for sCT generation and dose calculation on sCT.
UNASSIGNED: For sCT generation, random model error near the edge of the body (∼200 HU) was higher than that within the body (∼100 HU near the bone edge and <10 HU in soft tissue). The mean absolute error (MAE) was 49 ± 5, 191 ± 23, and 503 ± 70 HU for the whole body, bone, and air in the patient, respectively. Random model errors of the proton range were small (<0.2 mm) for all spots and evenly distributed throughout the proton fields. Systematic errors of the proton range were -1.0(±2.2) mm and 0.4(±0.9)%, respectively, and were unevenly distributed within the proton fields. For 4.5% of the spots, large errors (>5 mm) were found, which may relate to MRI-CT mismatch due to, e.g., registration, MRI distortion anatomical changes, etc.
UNASSIGNED: The sCT model was shown to be robust, i.e., had a low random model error. However, further investigation to reduce and even predict and manage systematic error is still needed for future MRI-only proton therapy.