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有效辐射剂量的自动测量通过F-氧糖位子发射断层扫描/计算机断层扫描

Yujin Eom¹, Yong-Jin Park², Sumin Lee²

¹Department of AI Mobility Engineering, Ajou University, Suwon 16499, Republic of Korea.

Tomography (Ann Arbor, Mich.)

|December 27, 2024

概括

这项研究开发了一个自动化的深度学习程序,用于标准化18F-PET/CT扫描的辐射剂量计算. 该程序准确地测量有效剂量 (ED),减少辐射剂量测量的变化和提高效率.

科学领域:

医疗成像医学成像
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:

在18F-PET/CT检查中从CT计算辐射剂量是具有挑战性的.
标准化辐射剂量测量对于患者安全和研究至关重要.
操作者之间的变化可能会影响剂量计算的准确性.

研究的目的:

开发基于深度学习的自动化程序,用于在18F-PET/CT中标准化辐射剂量计算.
验证自动化程序的准确性和可靠性.
为了比较较旧的和新的PET/CT扫描仪之间的辐射剂量.

主要方法:

使用TotalSegmentator将干CT细分为六个区域.
开发了一个自动化程序来提取信息并计算PET/CT的有效剂量 (ED).
通过将其ED计算与核医学医生的计算进行比较,并通过比较较老旧的PET/CT扫描仪与较新的PET/CT扫描仪来验证程序的准确性.

主要成果:

自动化程序的CT ED计算与核医学医生相比没有显著差异 (p = 0.7623).
总ED计算也显示自动化程序和医生之间没有显著差异 (p = 0.8957),与非常强的相关性 (r2 = 0.9981-0.9996).
与较旧的扫描仪相比,较新的PET/CT扫描仪导致PET ED和总ED显著降低 (p < 0.0001).

结论:

成功开发了一个自动化程序来计算干18F-PET/CT的有效剂量.
深度学习的整合有效地消除了在辐射剂量计算中的操作者间的变化.
该计划提供了一种标准化和可靠的方法,用于在18F-PET/CT中评估辐射剂量.

关键词:

在18F-FDG中.计算机断层扫描 (CT) 是一种计算机断层扫描.深度学习是一种深度学习.有效剂量的有效剂量.定子发射断层扫描 (PET).

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