Recurrence patterns are significantly associated with the ¹⁸F‑FDG PET/CT radiomic features of patients with locally advanced non‑small cell lung cancer treated with chemoradiotherapy

Abstract

A model for predicting the recurrence pattern of patients with locally advanced non-small cell lung cancer (LA-NSCLC) treated with chemoradiotherapy is of great importance for precision treatment. The present study analyzed whether the comprehensive quantitative values (CVs) of the fluorine-18( 18 F)-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) radiomic features and metastasis tumor volume (MTV) combined with clinical characteristics could predict the recurrence pattern of patients with LA-NSCLC treated with chemoradiotherapy. Patients with LA-NSCLC treated with chemoradiotherapy were divided into training and validation sets. The recurrence profile of each patient, including locoregional recurrence (LR), distant metastasis (DM) and both LR/DM were recorded. In the training set of patients, the primary tumor prior radiotherapy with 18 F-FDG PET/CT and both primary tumors and lymph node metastasis were considered as the regions of interest (ROIs). The CVs of ROIs were calculated using principal component analysis. Additionally, MTVs were obtained from ROIs. The CVs, MTVs and the clinical characteristics of patients were subjected to aforementioned analysis. Furthermore, for the validation set of patients, the CVs and clinical characteristics of patients with LA-NSCLC were also subjected to logistic regression analysis and the area under the curve (AUC) values calculated. A total of 86 patients with LA-NSCLC were included in the analysis, including 59 and 27 patients in the training and validation sets of patients, respectively. The analysis revealed 22 and 12 cases with LR, 24 and 6 cases with DM and 13 and 9 cases with LR/DM in the training and validation sets of patients, respectively. Histological subtype, CV2-5 and CV3-4 were identified as independent variables in the logistic regression analysis (P<0.05). In addition, the AUC values for diagnosing LR, DM and LR/DM were 0.873, 0.711 and 0.826, and 0.675, 0.772 and 0.708 in the training and validation sets of patients, respectively. Overall, the results demonstrated that the spatial and metabolic heterogeneity quantitative values from the primary tumor combined with the histological subtype could predict the recurrence pattern of patients with LA-NSCLC treated with chemoradiotherapy.