计算机断层扫描中的辐射剂量减少的人工智能:从2020年到2025年的临床证据的叙事综合
1Medical Physics and Clinical Engineering, East Kent Hospitals University NHS Foundation Trust, Kent and Canterbury Hospital, Ethelbert Road, Canterbury, Kent, CT1 3NG, Canterbury, Kent, CT1 3NG, United Kingdom of Great Britain and Northern Ireland.
概括
人工智能 (AI) 在计算机断层扫描 (CT) 扫描中显著降低了40-90%的辐射剂量,在各种应用中保持了诊断质量. 这种人工智能驱动的剂量优化对于瘤学,查和儿科成像至关重要.
科学领域:
- 医学成像技术 医学成像技术
- 放射学 放射学是一门学科.
- 人工智能在医学中的应用
背景情况:
- 计算机断层扫描 (CT) 在临床实践中至关重要,但对人口的辐射暴露有重大贡献.
- 瘤学,儿科和查途径特别受到CT扫描的高辐射剂量的影响.
- 越来越需要采取剂量降低策略,而不损害诊断性能,符合ALARP原则和IR(ME) R要求.
研究的目的:
- 综合基于人工智能 (AI) 的CT剂量优化策略的证据.
- 评估AI在降低辐射剂量的有效性,同时保持诊断性能.
- 确定关键的人工智能应用和从剂量减少中受益的解剖区域.
主要方法:
- 在PubMed,Scopus和IEEE Xplore进行了系统的文献搜索,搜索了2020年1月至2025年5月期间发表的研究.
- 根据与辐射剂量,诊断准确性和图像质量相关的临床或基于患者的结果,选择了86项符合纳入标准的研究.
- 由于方法异质性,研究结果被叙述性合成并按解剖区域和人工智能应用分组.
主要成果:
- 人工智能始终能够在各种适应症中大幅降低剂量 (40-90%),包括胸部成像 (30-95%),腹部/肝脏成像 (40-70%),以及儿科应用 (50-95%).
- 超低剂量协议支持肺癌查和结节检测;"双低"和"三低"血管协议减少了辐射和.
- 工作流 AI,如自动定位,提供了额外的独立好处.
结论:
- 人工智能在CT成像中提供临床上有意义的辐射剂量减少,同时保持诊断信心.
- 最强有力的证据支持人工智能用于胸部查,瘤学随访,血管成像和儿科.
- 在医疗保健系统中成功实施需要强有力的治理,质量保证,培训和多中心评估.
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