基于人工智能的高分辨率计算机断层扫描参数与连接组织疾病相关的间歇性肺病患者全因死亡率的关联:纵向队列研究
Chen Chu1, An Yan2, Jingyu Xu1
1Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Journal of thoracic disease
|February 9, 2026
概括
高分辨率计算机断层扫描 (HRCT) 的人工智能 (AI) 分析可以预测结缔组织疾病相关的间歇性肺病 (CTD-ILD) 的存活率. 人工智能参数与疾病严重程度和患者的结果相关,有助于预后评估.
科学领域:
- 放射学 放射学是一门学科.
- 肺部病理学 肺部病理学
- 人工智能的人工智能
背景情况:
- 连接组织疾病相关的间歇性肺病 (CTD-ILD) 严重程度会影响患者的预后和生活质量.
- 准确的预后评估对于管理CTD-ILD患者至关重要.
研究的目的:
- 评估基于人工智能 (AI) 的定量高分辨率计算机断层扫描 (HRCT) 分析在预测CTD-ILD患者预后方面的实用性.
- 为了将AI衍生的HRCT参数与疾病严重程度和整体存活率相关联.
主要方法:
- 对116名CTD-ILD患者的HRCT扫描进行了回顾性分析.
- 根据肺功能测试 (PFTs) 将患者分为轻度,中度和重度的分层.
- 统计分析包括ANOVA,斯皮尔曼相关性,卡普兰-梅尔和考克斯回归来评估AI参数和生存率.
主要成果:
- 在疾病严重程度组中观察到17个AI参数的显著变化.
- 人工智能参数与肺功能存在关联,其中一些表明保护作用,而另一些则表明生存风险因素.
- 左肺体积和疾病成分百分比 (≤-751 HU) 成为关键预后因素.
结论:
- 基于AI的定量HRCT分析是评估CTD-ILD患者的宝贵工具.
- 人工智能衍生的参数与整体存活率相关,为改善预后评估提供了潜力.
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