开发一种用于非共面放射治疗的有限角度范围内的投影的非共面锥形束计算机断层扫描（CBCT）图像重建方法。利用生成对抗网络（GAN）来重建非共面CBCT图像。本研究使用了 40 名脑肿瘤患者和两个头部模型的数据。在训练阶段，GAN的生成器使用共面CBCT和非共面投影作为输入，并利用具有双分支结构的编码器分别从共面CBCT和非共面投影中提取特征。然后使用解码器结合提取的特征来重建非共面 CBCT 图像。为了提高图像细节的重建精度，使用基于补丁的卷积神经网络作为鉴别器对生成器进行对抗性训练。使用新设计的联合损失来提高全局结构一致性，而不是传统的 GAN 损失。使用八名患者和两个模型在四个治疗床角度（±45°、±90°）的数据对所提出的模型进行了评估，这些角度最常用于我们科室的脑非共面放射治疗。通过计算均方根误差 (RMSE) 和整体配准误差 ε 来评估重建的准确性，而总体配准误差 ε 是通过积分刚性变换参数来计算的。在患者数据和体模数据研究中，定性和定量指标结果表明 ± 45°沙发角度模型的表现优于 ±90° 沙发角度模型，并且具有统计差异。在患者数据研究中，床角在 45°、-45°、90° 和 -90° 时的平均 RMSE 和 ε 值分别为 58.5 HU 和 0.42 mm、56.8 HU 和 0.41 mm、73.6 HU 和 0.48 mm，以及分别为 65.3 HU 和 0.46 毫米。在模型数据研究中，45°、-45°、90° 和 -90° 时床角的平均 RMSE 和 ε 值分别为 91.2 HU 和 0.46 mm、95.0 HU 和 0.45 mm、114.6 HU 和 0.58 mm，以及分别为 102.9 HU 和 0.52 mm。结果表明，重建的非共面 CBCT 图像有可能实现非共面放射治疗的治疗内三维位置验证。© 2024 作者。 《应用临床医学物理学杂志》由 Wiley periodicals, LLC 代表美国医学物理学家协会出版。

To develop a non-coplanar cone-beam computed tomography (CBCT) image reconstruction method using projections within a limited angle range for non-coplanar radiotherapy.A generative adversarial network (GAN) was utilized to reconstruct non-coplanar CBCT images. Data from 40 patients with brain tumors and two head phantoms were used in this study. In the training stage, the generator of the GAN used coplanar CBCT and non-coplanar projections as the input, and an encoder with a dual-branch structure was utilized to extract features from the coplanar CBCT and non-coplanar projections separately. Non-coplanar CBCT images were then reconstructed using a decoder by combining the extracted features. To improve the reconstruction accuracy of the image details, the generator was adversarially trained using a patch-based convolutional neural network as the discriminator. A newly designed joint loss was used to improve the global structure consistency rather than the conventional GAN loss. The proposed model was evaluated using data from eight patients and two phantoms at four couch angles (±45°, ±90°) that are most commonly used for brain non-coplanar radiotherapy in our department. The reconstructed accuracy was evaluated by calculating the root mean square error (RMSE) and an overall registration error ε, computed by integrating the rigid transformation parameters.In both patient data and phantom data studies, the qualitative and quantitative metrics results indicated that ± 45° couch angle models performed better than ±90° couch angle models and had statistical differences. In the patient data study, the mean RMSE and ε values of couch angle at 45°, -45°, 90°, and -90° were 58.5 HU and 0.42 mm, 56.8 HU and 0.41 mm, 73.6 HU and 0.48 mm, and 65.3 HU and 0.46 mm, respectively. In the phantom data study, the mean RMSE and ε values of couch angle at 45°, -45°, 90°, and -90° were 91.2 HU and 0.46 mm, 95.0 HU and 0.45 mm, 114.6 HU and 0.58 mm, and 102.9 HU and 0.52 mm, respectively.The results show that the reconstructed non-coplanar CBCT images can potentially enable intra-treatment three-dimensional position verification for non-coplanar radiotherapy.© 2024 The Author(s). Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.