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Updated: Feb 1, 2026

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Determining Glucose Metabolism Kinetics Using 18F-FDG Micro-PET/CT
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自动化长轴视野PET图像处理和动态建模,使用TurBO工具箱
Jouni Tuisku1,2, Santeri Palonen3,4, Henri Kärpijoki3,4
1Turku PET Centre, University of Turku, Turku, Finland. joupes@utu.fi.
European journal of nuclear medicine and molecular imaging
|January 30, 2026
概括
图尔库全身 (TurBO) 管道自动处理长轴视野 (LAFOV) PET成像,使组织输液和新陈代谢的有效和可重复量化. 这种开源工具可以减少手工工作量,以加强机构间评估.
科学领域:
- 核医学是一种核医学.
- 医学成像分析 医学成像分析
- 定量化PET成像技术使用
背景情况:
- 长轴视野 (LAFOV) PET成像产生大型数据集,需要显著的自动化.
- 精确量化组织输液和新陈代谢对于疾病诊断和监测至关重要.
研究的目的:
- 介绍Turku total-BOdy (TurBO),这是一个开源管道,用于LAFOV PET数据的自动化预处理和动态建模.
- 能够有效和可重复量化区域和voxel层面的组织 perfusion 和代谢.
主要方法:
- 使用LAFOV PET/CT数据 ([15O]H2O和[18F]FDG) 来验证TurBO管道,分别来自21名和16名受试者.
- 采用了自动联合注册,运动校正,基于CT的ROI细分和图像衍生输入函数 (IDIF) 提取.
- 对6个CT细分的ROI进行了区域特定的动力建模.
主要成果:
- 高质量的模型匹配得到了一致的估计 (R2>0.83为 [15O]H2O,R2>0.99为 [18F]FDG).
- 手动和自动化的IDIF显示出强烈的一致性 (R2>0.74),偏差最小 (<4%和<10%).
- 运动校正对估计的影响最小 (R2 > 0.71).
结论:
- 博管道为LAFOV PET数据提供完全自动化和可靠的量化.
- 它显著减少了手工劳动,促进了标准化和可重复的器官间输液和新陈代谢评估.
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