[1]张皓,李琳,吕发金.基于Fisher判别构建CT引导下肺穿刺活检并发症的预测模型[J].介入放射学杂志,2020,29(01):45-50.
　ZHANG Hao,LI Lin,LÜ,et al.The establishment of a model for predicting complications of CT-guided percutaneous transthoracic needle biopsy based on Fisher discriminant[J].journal interventional radiology,2020,29(01):45-50.
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基于Fisher判别构建CT引导下肺穿刺活检并发症的预测模型()

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《介入放射学杂志》[ISSN:1008-794X/CN:31-1796/R]

卷:
29
期数:
2020年01
页码:
45-50
栏目:
非血管介入
出版日期:
2020-02-10

文章信息/Info

Title:
The establishment of a model for predicting complications of CT-guided percutaneous transthoracic needle biopsy based on Fisher discriminant
作者:
张皓; 李琳; 吕发金
Author(s):
ZHANG Hao;  LI Lin;  LÜ Fajin.
Department of Radiology, Dianjiang County People’s Hospital, Chongqing 408300, China
关键词:
【关键词】　CT引导下肺穿刺活检; 并发症; Fisher判别; 预测模型
文献标志码:
A
摘要:
【摘要】　目的?探讨基于机器学习算法的Fisher判别，初步构建CT引导下经皮肺穿刺活检（PTNB）并发症的预测模型。方法　回顾性分析227例CT 引导下PTNB的肺部肿块或结节，用前187例筛选并发症危险因素，纳入有统计学意义的指标，构建Fisher判别式，然后采用交叉核实法和后40例评估预测模型。结果?187例中出现并发症48例（25.7%），主要为气胸29例（15.5%）和肺出血26例（13.9%），其中包含有气胸合并肺出血7例（3.74%）。并发症的危险因素有病灶大小、合并肺气肿、病灶中心与膈面短径、穿刺深度、穿刺角度和穿刺次数，并设参数值：X1=病灶大小（0＞2 cm；1≤2 cm）、X2=合并肺气肿等（0=是；1=否）、X3=病灶中心距离膈面短径（0＞3 cm；1≤3 cm）、X4=穿刺深度（0≤5 cm；1＞5 cm）、X5=穿刺胸膜角度（0≤50°；1＞50°）、X6=穿刺时间（0≤20 min；1＞20 min）、X7=穿刺次数（0=1次；1≥2次）。所得并发症的非标准化Fisher判别公式为Z = 1.531X1+ 1.531X2+ 2.123X3 + 1.390X4 + 1.564X5 + 0.903X6 + 1.716X7 - 3.114，判别界值为0.514。预测模型的交叉核实法和40例实践测评的误判率分别是10.2%和7.5%，准确率为89.8%和92.5%，敏感度为85.4%和88.9%，特异度为91.4%和93.5%。 结论?Fisher判别模型可以用于辅助临床预测CT引导下PTNB并发症的发生概率。

参考文献/References:

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备注/Memo

备注/Memo:
（收稿日期：2019-02-24）
（本文编辑：俞瑞纲）
更新日期/Last Update: 2020-02-08