基于计算机断层扫描的放射性诺米克图,用于预测肺癌中隐性肺转移的情况
Xiaoyi Zhao1,2, Heng Zhao1,2, Kongxu Dai1,2
1Department of Thoracic Surgery, Peking University People's Hospital, No. 11 Xizhimen South Street, Xicheng District, Beijing 100044, China.
Current oncology (Toronto, Ont.)
|April 25, 2025
概括
在肺癌前手术中识别隐藏性肺转移 (OPM) 是具有挑战性的. 一个新的模型将CT放射学与CEA和NLR等临床因素结合起来,准确地预测肺癌患者的OPM风险.
科学领域:
- 医疗成像医学成像
- 在瘤学瘤学.
- 放射学 放射学是一门学科.
背景情况:
- 在肺癌中隐藏的多叶性转移 (OPM) 的术前鉴定是一个重大的临床挑战.
- 准确的OPM检测对于适当的治疗计划和患者管理至关重要.
研究的目的:
- 开发和验证一个预测模型,用于在肺癌中进行手术前OPM识别.
- 该模型将临床数据与来自胸部CT扫描的放射性特征集成.
主要方法:
- 使用了50名OPM阳性和50名非转移性肺癌患者的培训队列.
- 最小绝对收缩和选择操作员 (LASSO) 后勤回归确定了关键的放射性特征.
- 使用临床因素和放射性评分构建了一个预测性名录,然后对545名患者进行验证.
主要成果:
- 显著的临床预测因素包括癌胚抗原 (CEA),中性粒细胞与淋巴细胞的比率 (NLR),临床T阶段和瘤与多发性关系.
- 结合放射性评分 (VOI) 与CEA和NLR的综合模型实现了高预测性能 (AUC为0.890培训,0.855验证).
结论:
- 来自CT的放射性特征对识别OPM风险的肺癌患者显得有前途.
- 开发的nomogram,集成CEA,NLR和放射性评分,改善了临床决策的手术前OPM预测准确性.
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