长轴视野正子辐射断层扫描的减弱校正使用合成计算机断层扫描从辐射数据中提取:适用于低数量研究和多个痕迹仪的应用
Maria Elkjær Montgomery1, Flemming Littrup Andersen1,2, Sabrina Honoré d'Este1
1Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet, Copenhagen University Hospital, 2100 København, Denmark.
Diagnostics (Basel, Switzerland)
|December 22, 2023
概括
这项研究引入了一种新的AI方法,可以从PET图像中创建合成CT扫描,减少辐射剂量并提高使用[18F]FDG和 [15O]H2O标志物进行全身PET扫描的图像质量.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 核医学就是核医学.
背景情况:
- 长轴视野 (LAFOV) PET/CT扫描仪提高了PET的灵敏度,降低了标记剂量.
- 患者的辐射剂量现在主要来自基于CT的减弱校正 (AC).
- 开发能够最大限度地减少辐射暴露的交流方法至关重要.
研究的目的:
- 提出和评估一个参数传输的条件生成对抗网络 (PT-cGAN),用于从非减弱校正 (NAC) PET 图像中生成合成CT (sCT) 图像.
- 评估这种方法对[18F]FDG和 [15O]H2O标记物的可行性.
- 为了研究PT-cGAN在低计数扫描场景中的性能.
主要方法:
- 开发了一个PT-cGAN架构,用于[18F]FDG和 [15O]H2O的单独网络.
- 该模型是通过LAFOV扫描仪获得的1018个受试者的数据 (972 [18F]FDG,46 [15O]H2O) 进行训练和测试的.
- 进行了定性和定量分析,包括对模拟低数图像的评估.
主要成果:
- 在大多数FDG案例中,定性分析没有显示出显著的图像质量差异.
- 观察到NAC PET和CT之间的运动器件减少.
- [18F]FDG的平均误差为0.45%, [15O]H2O的平均误差为3.12%.
- 该模型在低计数扫描 (低至45秒) 上表现良好.
结论:
- 拟议的PT-cGAN可实现全身PET的可行衰减校正,跨不同标记物和低计数研究.
- 这种人工智能驱动的方法有可能减少辐射剂量,并减轻PET/CT成像中的运动和金属工件.
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