A Meta-analysis of radiomics in differential diagnosis of small cell lung cancer and non-small cell lung cancer
10.3969/j.issn.1002-1671.2024.04.009
- VernacularTitle:影像组学鉴别诊断小细胞肺癌与非小细胞肺癌的Meta分析
- Author:
Fujun YANG
1
;
Fang SHEN
;
Xiaoyang BI
;
Yanlong TANG
Author Information
1. 大理大学临床医学院,云南 大理 671000
- Keywords:
radiomics;
small cell lung cancer;
non-small cell lung cancer;
Meta-analysis
- From:
Journal of Practical Radiology
2024;40(4):552-556
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the value of radiomics in differential diagnosis of small cell lung cancer(SCLC)and non-small cell lung cancer(NSCLC).Methods Literature on the differential diagnosis of SCLC and NSCLC using radiomics was searched in Chinese and English databases.After literature screening and data extraction,Meta-DiSc1.4 and State16.0 SE software were used for analysis.Results A total of 910 patients were included in 8 studies.Meta-analysis results showed that the radiomics differential diag-nosis of SCLC and NSCLC had high co-sensitivity(Sen)and specificity(Spe),0.87[95%confidence interval(CI)0.83-0.91]and 0.88(95%CI 0.85-0.90),respectively.Meta-regression analysis showed that heterogeneity was not caused by feature extraction software type,joint machine learning,image pattern,brain metastasis,and sample size.Publication bias results didn't show any sig-nificant publication bias.Conclusion The radiomics method can differentiate and diagnose SCLC from NSCLC more accurately.When Matlab software is used to extract MRI image features combined with machine learning,and the sample size is large enough,the radiomics can differentiate and diagnose SCLC from NSCLC more accurately.
