Frontiers in Oncology · 2020 · 27 citations · 47 references
MedicineNuclear MedicineOncologyDiagnostic ImagingDiagnostic RadiologyThoracic ImagingComputed TomographyOncologic Nuclear ImagingPositron Emission TomographyThoracic Oncology ImagingTumor Imaging18F-fluorodeoxyglucose Imaging18F-fluorodeoxyglucose Positron Emission TomographyCox RegressionFluorine-18 Fluorodeoxyglucose Positron Emission TomographyOutcome PrognosticationRadiomicsRadiomics In Lung CancerRadiomics Prognosis
Purpose: This study aimed toIn this study, we developed and validated a radiomicsradiomics nomogram by combining the radiomic features extracted from 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) images and clinicopathological factors to evaluate the overall survival (OS) of patients with non-small cell lung cancer (NSCLC). Patients and methods: A total of 315 consecutive patients with NSCLC (221 in the training cohort and 94 in the validation cohort) were enrolled in this study. A total of 840 radiomic features were extracted from the CT and PET images, respectively. Three radiomic scores (rad-scores) were calculated using the least absolute shrinkage and selection operator (LASSO) Cox regression based on subsets of CT, PET, and PET/CT radiomic features subsets. A multivariate Cox regression analysis was performed for each rad-score combined with the clinicopathological factors to determine the independent risk factors. The OS nomogram was constructed based on the PET/CT rad-score and the independent clinicopathological factors. Validation and calibration were conducted to evaluate the performance of the model in the training and validation cohorts, respectively. Results Results: A total of 144 (45.71%) women and 171 (54.29%) men with NSCLC were enrolled in this study. The PET/CT rad-score combined with the clinical model had the best C-index (0.789). Ageage (hazard ratio [HR], 1.03), distant metastasis (HR, 2.24) , stage (HR, 2.99) , CEA (HR, 1.10), and targeted therapy (HR, 0.36) were the independent risk factors for patients with NSCLC. The validation curve showed that the OS nomogram had a strong predictive power in patients’ survival. The calibration curve showed that the predicted survival time was significantly close to the observed one. Conclusion: A radiomicradiomics nomogram based on 18F-FDG PET/CT rad-score and clinicopathological factors had a good predictive performance for the survival outcome, offering feasible and practical guidance for the individualized management of patients with NSCLC.
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