在不同的虚拟单能水平上使用双能CTCT比较全自动化的AI人体成分生物标志物
Giuseppe V Toia1, John W Garret2, Sean D Rose3
1University of Wisconsin School of Medicine and Public Health, Madison, USA. GToia@uwhealth.org.
Abdominal radiology (New York)
|December 6, 2024
概括
人工智能 (AI) 基于CT的身体组成生物标志物在70keV及以上的虚拟单能成像 (VMI) 水平上显示最小的变化. 较低的VMI水平 (低于70keV) 呈现出显著的变化,应避免进行准确的身体成分分析.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 双能CT (DECT) 能够实现虚拟单能成像 (VMI) 的重建.
- 人工智能算法可以从CT图像中量化身体成分生物标志物.
- 了解VMI对AI生物标志物的影响对于一致的分析至关重要.
研究的目的:
- 评估人工智能驱动的CT身体组成生物标志物的行为,跨越各种VMI水平.
- 评估不同VMI能量水平对DECT扫描产生的定量生物标志物的影响.
主要方法:
- 88个腹腔皮层DECT扫描的回顾性分析.
- 在五个VMI级别 (40,55,70,85,100keV) 的图像重建.
- 应用自动化AI算法来量化脂肪,肌肉,骨,和器官大小;分析相对于70keV的生物标志物变化.
主要成果:
- 生物标志物差异 (不包括Agatston评分) 在40,55,85,100keV与70keV相比,分别在39-358,12-102,5-48和9-75 HU之间,以减弱为基础的措施.
- 基于面积的生物标志物显示6-15cm,3-4cm,2-7cm和0-5cm2的差异;基于体积的生物标志物显示12-34cm,8-68cm,12-52cm和1-57cm3的差异.
- 低于70keV的VMI水平与70keV或以上的水平相比,显示出更大的测量变化,Agatston得分表现出特别虚假的行为.
结论:
- 自动化AI CT生物标志物在70keV及以上的VMI水平下显示稳定性.
- 较低的VMI能量水平 (<70 keV) 会导致显著的偏差,应避免进行可靠的身体成分评估.
- 这些发现支持使用70 keV VMI作为使用DECT.AI进行基于AI的身体成分分析的一致参考.
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