基于计算机断层扫描的身体组成测量的患者内变化的纵向评估.
B Dustin Pooler1, John W Garrett2, Matthew H Lee2
1School of Medicine and Public Health, University of Wisconsin-Madison, Madison, USA. bpooler@uwhealth.org.
Abdominal radiology (New York)
|March 5, 2026
概括
纵向的身体组成变化在性别和年龄组之间有显著差异. 自动化的人工智能工具揭示了CT测量身体组成的年龄和性别特异性变化.
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:
- 随着年龄和性别的变化,身体成分发生变化.
- 准确评估这些变化对于健康监测至关重要.
- 自动化工具为有效分析身体成分提供了潜力.
研究的目的:
- 分析基于CT的身体组成的纵向,患者内变化.
- 利用全自动化的人工智能 (AI) 工具进行身体组成评估.
- 研究年龄和性别作为这些变化的预测因素.
主要方法:
- 对15616名成年患者进行了至少两次腹部CT扫描的回顾性研究.
- 人工智能工具量化了脊椎椎衰减,骨肌,内脏脂肪组织 (VAT) 和皮下脂肪组织 (SAT).
- 在9.1年的平均间隔内分析了纵向变化,并对年龄和性别预测因素进行了统计分析.
主要成果:
- 在大多数测量指标 (p < 0.05) 中,观察到身体组成变化率的性别特异性差异很大,不包括肌肉衰减.
- 年龄预测的身体组成措施,虽然效果大小小 (R2 0.002-0.040),在不同年龄组之间有所不同.
- 内脏脂肪组织 (VAT) 和皮下脂肪组织 (SAT) 的变化显示出不同的模式,受年龄和性别的影响.
结论:
- 纵向的身体组成变化表现出显著的年龄和性别特异性变化.
- 自动化的人工智能分析提供了对患者体内身体组成随时间推移的动态有价值的见解.
- 调查结果强调了在解释人体成分数据时考虑人口因素的重要性.
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