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Development of a PET/CT molecular radiomics-clinical model to predict thoracic lymph node metastasis of invasive lung adenocarcinoma ≤ 3 cm in diameter.
- Source :
- EJNMMI Research; 4/21/2022, Vol. 12 Issue 1, p1-11, 11p
- Publication Year :
- 2022
-
Abstract
- Background: To investigate the value of <superscript>18</superscript>F-FDG PET/CT molecular radiomics combined with a clinical model in predicting thoracic lymph node metastasis (LNM) in invasive lung adenocarcinoma (≤ 3 cm). Methods: A total of 528 lung adenocarcinoma patients were enrolled in this retrospective study. Five models were developed for the prediction of thoracic LNM, including PET radiomics, CT radiomics, PET/CT radiomics, clinical and integrated PET/CT radiomics-clinical models. Ten PET/CT radiomics features and two clinical characteristics were selected for the construction of the integrated PET/CT radiomics-clinical model. The predictive performance of all models was examined by receiver operating characteristic (ROC) curve analysis, and clinical utility was validated by nomogram analysis and decision curve analysis (DCA). Results: According to ROC curve analysis, the integrated PET/CT molecular radiomics-clinical model outperformed the clinical model and the three other radiomics models, and the area under the curve (AUC) values of the integrated model were 0.95 (95% CI: 0.93–0.97) in the training group and 0.94 (95% CI: 0.89–0.97) in the test group. The nomogram analysis and DCA confirmed the clinical application value of this integrated model in predicting thoracic LNM. Conclusions: The integrated PET/CT molecular radiomics-clinical model proposed in this study can ensure a higher level of accuracy in predicting the thoracic LNM of clinical invasive lung adenocarcinoma (≤ 3 cm) compared with the radiomics model or clinical model alone. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 2191219X
- Volume :
- 12
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- EJNMMI Research
- Publication Type :
- Academic Journal
- Accession number :
- 156445148
- Full Text :
- https://doi.org/10.1186/s13550-022-00895-x