Predictive Value of Positron Emission Tomography/CT Imaging in Distant Metastasis in Early and Locally Advanced Lung Cancer

The imaging features of advanced non-small cell lung cancer identified by imaging approaches are particularly critical for the clinical prognosis and treatment. Our study explores the predictive value of Positron Emission Tomography–Computed Tomography (PET/CT) imaging in distant metastasis in early and locally advanced lung cancer. From September 2017 to September 2019, 121 patients with PET images were enrolled. 80 patient’s data were used to simulate the cohort and the data on 41 patients were used to validate the cohort. Quantitative PET image features were assessed. A Cox model was used to predict the distant metastasis. A combination of imaging and histology type prognostic models was also evaluated. The best prognostic model includes two features, which can quantify intratumoral heterogeneity. In independent validation cohort, the consistency index of model was 0.71. This prognostic model allows high-risk and low-risk group with distant metastases (hazard ratio 4.8, P < 0.05). The ROC curve revealed a separation of the combined imaging and histology type among high-and low-risk group. The consistency index was also improved to 0.80. PET features related to distant metastases have been identified and these features may help develop appropriate treatment options for early and locally advanced lung cancer patients.