Diagnostic utility of metabolic parameters on FDG PET/CT for lymph node metastasis in patients with cN2 non-small cell lung cancer

The aim of this study was to assess the diagnostic utility of metabolic parameters on fluorine-18-fluoro-2-deoxy-D-glucose-positron emission tomography (FDG-PET)/computed tomography (CT) for predicting lymph node (LN) metastasis in patients with cN2 non-small cell lung cancer (NSCLC).

We retrospectively reviewed patients who underwent surgery for cN2 NSCLC between 2007 and 2020. Those who had clinically diagnosed positive hilar and mediastinal LNs by routine CT and PET/CT imaging were investigated. To measure the metabolic parameters of LNs, the data according to maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and LN-to-primary tumor ratio of SUVmax (LPR) were examined. The diagnosis of each retrieved LN was confirmed based on histopathological examination of surgical tissue specimens. Receiver operating characteristics (ROC) curves with area under the curve (AUC) calculations and multivariate analysis by logistic regression were performed.

Forty-five patients with 84 clinically diagnosed positive hilar or mediastinal LNs were enrolled in the present study. Of the 84 LNs, 63 LNs were pathologically proven as positive (75%). The SUVmax, MTV, TLG, and LPR of LN metastasis were significantly higher than those of benign nodes. In the ROC analysis, the AUC value of LPR [AUC, 0.776; 95% confidence interval (CI), 0.640–0.913] was higher than that of LN SUVmax (AUC, 0.753; 95% CI, 0.626–0.880) or LN TLG3.5 (AUC, 0.746; 95% CI, 0.607–0.885). Using the optimal LPR cutoff value of 0.47, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 84.1, 66.7, 88.3, 58.3, and 79.8%, respectively. Multivariate analysis by logistic regression showed that LPR was an independent predictor for LN metastasis (odds ratio, 6.45; 95% CI, 1.785–23.301; P = 0.004). In the subgroup analysis of adenocarcinoma patients (n = 18; 32 LNs), TLG3.5 was a better predictor (AUC, 0.816; 95% CI, 0.639–0.985) than LPR (AUC, 0.792; 95% CI, 0.599–0.986) or LN SUVmax (AUC, 0.792; 95% CI, 0.625–0.959).

Our findings suggest that LPR on FDG-PET is a useful predictor for LN metastasis in patients with cN2 NSCLC. TLG can be a good predictor for LN metastasis in patients with adenocarcinoma.