Your browser doesn't support javascript.
loading
A Meta-analysis of radiomics in differential diagnosis of small cell lung cancer and non-small cell lung cancer / 实用放射学杂志
Journal of Practical Radiology ; (12): 552-556, 2024.
Article en Zh | WPRIM | ID: wpr-1020253
Biblioteca responsable: WPRO
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.
Palabras clave
Texto completo: 1 Índice: WPRIM Idioma: Zh Revista: Journal of Practical Radiology Año: 2024 Tipo del documento: Article
Texto completo: 1 Índice: WPRIM Idioma: Zh Revista: Journal of Practical Radiology Año: 2024 Tipo del documento: Article