[用于剂量管理的诊断放射学的人工智能:以计算机断层扫描为例的进步和前景]
Laura Garajová1, Stephan Garbe1,2, Alois M Sprinkart3
1Klinik für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Bonn, Venusberg-Campus 1, 53127, Bonn, Deutschland.
Radiologie (Heidelberg, Germany)
|June 14, 2024
概括
人工智能 (AI) 为优化成像中的医疗辐射剂量管理提供了有希望的工具. 虽然人工智能有助于规划和实时剂量估计,但其与剂量管理系统 (DMS) 的集成需要进一步研究才能广泛临床使用.
科学领域:
- 医疗成像医学成像
- 辐射物理学 辐射物理学
- 医疗信息学 医疗信息学
背景情况:
- 使用电离辐射的成像程序必须遵守严格的欧洲指令和国家患者保护法规.
- 合规性包括精细的指示,个体适应,暴露的记录和报告不可接受的剂量超标,这些都是耗时的任务.
- 计算机断层扫描 (CT) 对医疗辐射暴露有显著的贡献,使剂量优化成为放射学实践的关键强制性方面.
研究的目的:
- 探索人工智能 (AI) 在优化医疗成像程序期间患者辐射剂量的作用.
- 评估人工智能辅助技术对放射学工作流程中的剂量管理系统 (DMS) 的当前和潜在影响.
- 确定人工智能可以加强辐射保护措施并简化遵守监管要求的领域.
主要方法:
- 对人工智能辅助技术的审查,应用于放射学工作流程的各个阶段,包括检查计划,患者定位和扫描参数调整.
- 分析AI在提供实时估计个体器官剂量的能力.
- 检查AI与现有剂量管理系统 (DMS) 的整合,以全面监测辐射剂量.
主要成果:
- 人工智能辅助技术已经在医疗成像的不同方面优化辐射剂量方面取得了成功,从图像重建到检查执行.
- 人工智能工具支持关键过程步骤,如指示检查,检查规划和性能,有助于有效的辐射保护.
- 虽然人工智能显示了实时器官剂量估计的潜力,但其与DMS进行剂量管理的大规模集成尚未得到广泛探索.
结论:
- 人工智能驱动的过程为改善医学成像中的辐射剂量管理提供了有价值的工具.
- 进一步的研究,广泛的验证和持续的临床监测对于AI在剂量管理中的成功实施至关重要.
- 人工智能和DMS之间的协同作用有望改善放射学实践中的患者安全和监管合规性.
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