基于CT放射学的端到端管道,用于预测CKD患者的脏间歇性纤维化程度
Yue Ren1, Fei Yang2, Weiwei Li1
1Department of Radiology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou 310007, Zhejiang Province, China (Y.R., W.L., Y.Z., S.K., F.C.).
Academic radiology
|January 17, 2025
概括
结合放射学和临床数据的新型非侵入性方法准确预测慢性病 (CKD) 患者的纤维化. 这种方法提供了一种有前途的工具,可以在没有侵入性手术的情况下评估间歇性纤维化 (IF).
科学领域:
- 腎臟病學 (nephrology) 是一種醫學專業.
- 放射学 放射学是一门学科.
- 医疗成像医学成像
背景情况:
- 在慢性病 (CKD) 中对纤维化进行非侵入性评估至关重要但具有挑战性.
- 间歇性纤维化 (IF) 是CKD进展的关键指标.
研究的目的:
- 开发一个端到端的管道,整合放射学和临床因素,用于预测CKD患者间歇性纤维化 (IF).
- 评估结合放射学与临床模型的性能与仅放射学模型的性能.
主要方法:
- 追溯分析80名CKD患者的脏CT扫描和活检数据.
- 从CT图像中提取放射性特征,并使用LASSO回归构建放射性特征.
- 后勤回归模型的开发:放射学模型和结合模型,包括临床因素.
主要成果:
- 结合的模型在训练和测试集中表现出优越的预测性能,与放射学模型相比.
- 组合模型在训练组中实现了0.935的交叉验证AUC,在测试组中达到0.918.
- 校准曲线和决策曲线分析 (DCA) 证实了组合模型的良好校准和临床实用性.
结论:
- 综合放射学和临床因素工作流可以作为一种潜在的非侵入性工具,用于预测脏间歇性纤维化 (IF) 级别的CKD患者.
- 这种方法可能有助于临床决策和CKD患者管理.
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