【摘要】 目的：提出并验证一种基于半数投影重建双能锥形束CT(DE CBCT)进行双能分解的方法，为自适应放疗的解剖结构监测和剂量重建优化等场景提供潜在可行的低剂量成像技术方案。方法：采用VitalBeam加速器机载千伏CBCT系统对Gammex模体分别进行15和7 f/s的双能扫描，并基于投影数据重建图像。对7 f/s的双能图像进行双能分解，通过加权公式和经验函数分别获取相对电子密度（RED）和阻止本领比（SPR）并进行准确性评估。基于扫描参数计算各条件下的加权CT剂量指数（CTDIw）。结果：双能分解可以有效抑制图像伪影，并且其获取的RED和SPR误差分别低于2.82%和2.56%。相较于传统基于高低能双次扫描，半数投影DE CBCT的CTDIw可减少11.60 mGy（降幅52.90%），比单独扫描全数投影高能CBCT的剂量低2.58 mGy（降幅19.98%），仅比低能CBCT高1.31 mGy（增幅14.52%）。结论：本研究提出的方法能够在较低辐射剂量的条件下有效抑制图像伪影，其获取的RED和SPR具有较高的准确性，在需要反复进行图像引导的自适应放疗等场景具有潜在的应用价值。更多还原

【Abstract】 Objective To propose and validate a decomposition method based on half-projection reconstruction for dualenergy cone beam CT(DE CBCT), thereby providing a potentially feasible low-dose imaging solution for anatomical monitoring and dose reconstruction optimization in adaptive radiotherapy. Methods Dual-energy scans were performed on a Gammex phantom using the on-board kilovoltage CBCT system of a VitalBeam accelerator at acquisition frame rates of 15 and 7 frames per second(f/s). Images were reconstructed from the projection data, and dual-energy decomposition was applied to the 7 f/s dual-energy images to derive relative electron density(RED) and stopping power ratio(SPR) using weighted formulas and empirical functions, followed by accuracy evaluation. Additionally, the weighted CT dose index was calculated for different scanning parameters. Results Dual-energy decomposition effectively suppressed image artifacts, with RED and SPR errors remaining below 2.82% and 2.56%, respectively. Compared with the traditional dual-scan method which required high-and low-energy acquisitions, the weighted CT dose index of the half-projection DE CBCT was reduced by 11.60 mGy(a 52.90% reduction). Furthermore, it was 2.58 mGy lower than the dose of the full-projection high-energy CBCT alone(a 19.98% reduction) and only 1.31 mGy higher than that of the low-energy CBCT(a 14.52% increase).Conclusion The proposed method effectively suppresses image artifacts while maintaining high accuracy in RED and SPR under low radiation dose conditions, demonstrating its potential value for scenarios requiring frequent image guidance, such as adaptive radiotherapy.更多还原