使用基于人工智能的CT协议测量脂肪体构成及其与住院患者严重急性胰腺炎的关联
Pedro Cortés1, Tyler A Mistretta2, Brittany Jackson2
1Division of Gastroenterology and Hepatology, University of Washington, Seattle, WA, USA; Division of Medicine, Mayo Clinic, Jacksonville, FL, USA.
概括
肌肉间脂肪组织 (IMAT) 的升高预测严重的急性胰腺炎 (AP). 人工智能 (AI) 对身体组成的分析确定IMAT是住院患者的关键预测因素.
科学领域:
- 医学成像和诊断 医学成像和诊断
- 人工智能在医学中的应用
- 胃肠病学和肝病学 胃肠学和肝病学
背景情况:
- 身体组成在预测急性胰腺炎 (AP) 严重程度方面的临床意义尚未得到充分证实.
- 目前用于身体成分分析的方法可能无法在急性环境中立即适用.
研究的目的:
- 利用人工智能 (AI) 进行自动化身体组成分析.
- 为了确定人工智能衍生的身体组成指标是否可以预测住院患者的严重AP.
主要方法:
- 在3个三级保健中心对352名患者进行了回顾性研究,这些患者患有AP入院.
- 腹部CT成像分析使用验证的AI驱动的细分算法对身体组成进行分析.
- 根据修订的亚特兰大分类,严重的AP定义为持续的器官衰竭.
主要成果:
- 严重的AP发生在9.9%的患者中.
- 肌肉间脂肪组织 (IMAT) 的增加与严重的AP显著相关 (OR = 1.06每5厘米2,p = 0.0207).
- 皮下脂肪组织 (SAT) 接近统计学意义 (OR = 1.05,p = 0.17);内脏脂肪组织 (VAT) 和骨肌肉 (SM) 并不是显著的预测因素.
结论:
- 基于人工智能的身体组成分析可以识别高IMAT作为严重AP的预测因素.
- 需要进一步的前性研究来验证这些发现.
- 身体成分指标,特别是IMAT,可能为AP严重性评估提供新的见解.
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