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使用视觉顺序和深度学习评分来量化系统性硬化中的冠状动脉化:与系统性硬化临床特征的关联

Yiming Luo¹, Daniel Hanuska², Jiehui Xu³

¹Division of Rheumatology, Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA.

Seminars in arthritis and rheumatism

|November 29, 2024

概括

患有指尖或肺高血压的全身性硬化症 (SSc) 患者表现出较快的冠状动脉化进展. 早期的SSc疾病过程与加速化有关,这表明微血管病是动脉样硬化心血管疾病的危险因素.

科学领域:

心脏病学心脏病学
类风湿病学类风湿病学
医疗成像医学成像

背景情况:

系统性硬化症 (SSc) 是一种复杂的自身免疫性疾病,其特征是微血管损伤和纤维化.
冠状动脉化 (CAC) 是动脉样硬化和心血管疾病 (CVD) 的标志物.
在SSc临床表现和CAC进展之间的关系仍然不完全理解.

研究的目的:

研究SSc临床特征与冠状动脉化的程度和进展之间的关联.
评估基于深度学习的CAC评分在SSc中的实用性.
为了确定预测CCC进展的SSc相关因素.

主要方法:

对SSc患者进行的回顾性队列研究.
使用视觉顺序评分量化CAC分数的年度进展.
基于深度学习的方法 (DeepCAC) 用于量化CAC.
在SSc临床特征和CAC进展之间进行关联分析.

主要成果:

SSc疾病持续时间与年度顺序CAC得分进展相反相关.
指尖缺血性/数字痕和第一组肺高血压的存在与更高的深度学习CAC分数有关.
在调整人口统计和心血管风险因素后,这两种关联都仍然显著.

结论:

冠状动脉化进展在SSc疾病过程的早期加速.
严重的微血管病变,指指尖和肺高血压,可能是动脉样硬化心血管疾病的风险因素在SSc患者.

关键词:

心血管疾病的风险.图像成像技术可以提供图像.机器学习是机器学习.系统性硬化症系统性硬化症

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