Residual neural network-101-feature pyramid network model based on CT for differentiating benign and malignant lung nodules
10.13929/j.issn.1672-8475.2024.07.007
- VernacularTitle:基于CT残差神经网络-101-金字塔网络模型鉴别肺良、恶性结节
- Author:
Gang LIU
1
;
Xiaoting XIE
;
Hui HE
;
Fei LIU
;
Xu MAO
;
Jingyao SANG
;
Haiyun YANG
;
Yueyong XIAO
Author Information
1. 青海红十字医院放射影像介入科,青海 西宁 810000
- Keywords:
lung neoplasms;
tomography,X-ray computed;
artificial intelligence
- From:
Chinese Journal of Interventional Imaging and Therapy
2024;21(7):414-417
- CountryChina
- Language:Chinese
-
Abstract:
Objective To observe the value of residual neural network(ResNet)-101-feature pyramid network(FPN)model based on CT for differentiating benign and malignant lung nodules.Methods Totally 2 040 lung nodules in 2 000 patients were retrospectively enrolled,including 1 150 benign and 890 malignant nodules.The nodules were divided into training set(n=1 632)and test set(n=408)at the ratio of 8∶2,the former including 881 benign and 751 malignant ones,while the latter including 269 benign and 139 malignant ones,respectively.Taken ResNet-101 as the backbone network,combined with FPN,a classification model was established based on chest CT,and the efficiency of this model alone and combined with evaluation of physicians for differentiating benign and malignant lung nodules were evaluated.Results Among 269 benign lung nodules in test set,ResNet-101-FPN model alone correctly diagnosed 214 nodules(214/269,79.55%),while combined with evaluation of physicians correctly diagnosed 230 ones(230/269,85.50%).For 139 malignant nodules in test set,ResNet-101-FPN model alone correctly diagnosed 124 nodules(124/139,89.21%),while combined with evaluation of physicians correctly diagnosed 131 ones(131/139,94.24%).The sensitivity,accuracy and precision of ResNet-101-FPN model combined with evaluation of physicians for distinguishing benign and malignant lung nodules were all higher,while the specificity of the combination was lower than those of ResNet-101-FPN model alone,but the differences were not significant(all P＞0.05).Conclusion ResNet-101-FPN model could be used to distinguish benign and malignant lung nodules based on CT.Combining with evaluation of physicians could improve diagnostic efficiency of this model.
