在肺癌查人群中基于人工智能的身体成分分析的附加值:初步结果
Roberta Eufrasia Ledda1, Federica Sabia2, Camilla Valsecchi2
1Thoracic Surgery Unit, Fondazione IRCCS Istituto Nazionale Tumori, Via Venezian 1, 20133 Milan, Italy; Department of Medicine and Surgery (DiMeC), University of Parma, Via Gramsci 14, 43126, Parma, Italy.
Nutrition, metabolism, and cardiovascular diseases : NMCD
|September 15, 2024
概括
通过人工智能测量肺癌查CT扫描的皮下脂肪体积和密度显示,性别与年龄和吸烟史之间存在不同的关联. 这些身体成分指标与男性和女性的BMI,腰围和代谢标志物相关.
科学领域:
- 放射学和医学成像学 医学成像学
- 医疗保健中的人工智能
- 身体组成分析 身体成分分析
背景情况:
- 身体成分对于癌症和心血管疾病的结果至关重要.
- 在肺癌查 (LCS) 群体中对身体成分的分析是有限的.
- 这项研究探讨了LCS参与者的皮下脂肪体积 (SFV) 和密度 (SFD).
研究的目的:
- 在肺癌查人群中评估SFV和SFD与临床和人类学特征的关联.
- 利用基于人工智能 (AI) 的自动化软件,对超低剂量计算机断层扫描 (ultra-LDCT) 图像进行身体组成分析.
- 调查这些关联中的性别特异性差异.
主要方法:
- 利用人工智能软件从胸部超低频率图像中自动对皮下脂肪和肌肉进行3D细分.
- 包括938名志愿者 (372名女性) 在肺癌查计划中.
- 通过问卷和测量收集人口统计,临床,饮食和人体统计数据.
主要成果:
- 具有≥40包年吸烟史的男性具有较高的SFV;前吸烟者具有较低的SFD.
- 在女性中,SFV和SFD随年龄显著不同.
- 随着更高的BMI,腰围,腰比率和CRP,SFV增加;SFD随着这些参数在两种性别下降. SFV和SFD与血糖和甘油三相关.
结论:
- 在性别之间,SFV和SFD与年龄和吸烟史有明显的关联.
- 与人体测量数据,CRP,血糖和甘油三的关联在两性之间是一致的.
- 基于人工智能对超低发达人群的身体成分分析为LCS人群提供了洞察力.
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