现型生物衰老的CT生物标志物:新兴概念和优势
Matthew H Lee1, John W Garrett1, Daniel Liu1
1Department of Radiology, University of Wisconsin School of Medicine & Public Health, 600 Highland Ave, Madison, WI 53792.
概括
生物年龄 (BA) 可以使用计算机断层扫描 (CT) 来估计肌肉,脂肪和骨的生物标志物. 这种成像方法提供了一种实用,机会主义的方法来改进健康评估和风险预测,补充现有的脆弱性.
科学领域:
- 老年学和医学成像学
- 医疗保健中的人工智能
背景情况:
- 衰老是一个复杂的累积损伤过程,导致功能衰退和疾病风险增加.
- 年代年龄 (CA) 是医疗保健决策的关键因素,但生物年龄 (BA) 提供了更全面的健康评估.
- 现有的BA模型通常依赖于"omics"数据,但成像生物标志物仍未得到充分利用.
研究的目的:
- 探索计算机断层扫描 (CT) 生物标志物用于估计生物年龄 (BA) 的实用性.
- 突出基于CT的BA相对于传统的"omics"方法的优势.
- 强调人工智能 (AI) 在推进基于成像的BA估计中的作用.
主要方法:
- 利用肌肉,脂肪,大动脉化和骨的CT生物标志物构建基于CT的BA模型.
- 利用AI和可解释AI (XAI) 实现自动化,快速和可靠的图像分析.
- 在回顾性或前性研究中机会地应用基于成像的自动化身体构成工具.
主要成果:
- CT生物标志物提供了可访问,可重复的措施,反映了组织层面的衰老表型.
- 由人工智能驱动的自动化工具能够对成像数据进行可扩展的,人口级别的分析.
- 可解释的人工智能增强了对基于成像的BA预测的信任.
结论:
- 基于CT的表型BA估计是一种实用的,机会性的成像方法.
- 这种方法可以改善医疗决策和风险预测,超出目前的微弱学.
- 它通过提供更全面的健康评估,为社会和个人带来好处.
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