山东大学学报 (医学版) ›› 2022, Vol. 60 ›› Issue (4): 68-75.doi: 10.6040/j.issn.1671-7554.0.2021.1619
• • 上一篇
袁宏涛1,纪淙山1,2,康冰1,秦松楠1,于鑫鑫1,高琳2,王锡明1,2
YUAN Hongtao1, JI Congshan1,2, KANG Bing1, QIN Songnan1, YU Xinxin1, GAO Lin2, WANG Ximing1,2
摘要: 目的 探讨基于CT平扫图像建立的影像组学诺模图对鉴别肾上腺乏脂腺瘤和肾上腺结节样增生的诊断价值。 方法 回顾性分析经病理学检查证实的44例肾上腺乏脂腺瘤与55例肾上腺结节样增生患者。从CT平扫图像提取并筛选出有诊断价值的影像组学参数,计算影像组学评分构建影像组学模型,分析筛选临床因素构建临床模型并联合临床因素和影像组学模型构建诺模图。分析比较上述3种模型的诊断效能。 结果 13项影像组学参数被筛选用于建立影像组学诊断模型。影像组学模型验证集曲线下面积为0.91,敏感度和特异度分别为84.6%和81.3%。单因素及多因素二分类Logistic回归分析结果显示,肾素和最大径为鉴别二者的独立影响因子,临床模型验证集曲线下面积为0.57, 敏感度和特异度分别为53.9%和68.8%。诺模图验证集AUC为0.94,敏感度和特异度分别为84.6%和93.8%。影像组学模型及诺模图的诊断效能均大于临床模型(z=3.188,P<0.001;z=3.409,P<0.001)。 结论 基于CT平扫图像的影像组学诺模图对鉴别肾上腺乏脂腺瘤和肾上腺结节样增生有较高的诊断效能,具有较高的临床价值。
中图分类号:
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