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18F-FDG PET/CT combined with tumor markers for diagnosis of non stage ⅠA limited-stage small cell lung cancer / 中国医学影像技术
Article em Zh | WPRIM | ID: wpr-1026249
Biblioteca responsável: WPRO
ABSTRACT
Objective To observe the value of 18F-FDG PET/CT combined with tumor markers for diagnosis of non stageⅠ A limited-stage small cell lung cancer(LS-SCLC).Methods Totally 87 cases of non stage Ⅰ A LS-SCLC(LS-SCLC group),137 of non stage Ⅰ A non-small cell lung cancer(NSCLC,NSCLC group)and 48 cases of pulmonary inflammatory lesions(inflammatory group)were enrolled.Patients'general data,tumor marker levels and PET/CT findings were comparatively analyzed.Logistic regression analysis was performed to evaluate the efficacy of parameters for diagnosing non stage Ⅰ A LS-SCLC.Results There were significant differences of patients'age,neuron-specific enolase(NSE),pro-gastrin-releasing peptide(ProGRP),carcinoembryonic antigen(CEA),squamous cell carcinoma antigen(SCCA)and cytokeratin-19-fragment(CYFRA21-1),as well as of the maximum lesion diameter,maximum standard uptake value(SUVmax),morphology,spiculation sign,relationship between long axis and bronchus,lymph node fusion and proportion of lymph node with higher SUVmax than primary lesion among 3 groups(all P<0.05).The area under the curve(AUC)of the combination of spiculation sign,NSE>23.5 μg/L,ProGRP>111.8 ng/L,SCCA≤2.5 μg/L and CYFRA21-1≤7.4 μg/L for differentiating LS-SCLC and NSCLC was 0.91,higher than that of each single parameter(all P<0.05).AUC of the combination of SUVmax>8.1,NSE>19.4 μg/L,ProGRP>72.5 ng/L and lymph node fusion for differentiating LS-SCLC and pulmonary inflammatory lesions was 0.99,higher than each single parameter(all P<0.05).Conclusion 18F-FDG PET/CT combined with tumor markers ProGRP and NSE was helpful for diagnosing non stage ⅠA LS-SCLC.
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Texto completo: 1 Base de dados: WPRIM Idioma: Zh Revista: Chinese Journal of Medical Imaging Technology Ano de publicação: 2023 Tipo de documento: Article
Texto completo: 1 Base de dados: WPRIM Idioma: Zh Revista: Chinese Journal of Medical Imaging Technology Ano de publicação: 2023 Tipo de documento: Article