[en] Primary tumor (PT) and metastatic lymph node (MLN) status have a great influence on diagnosis and treatment of lung cancer. Our main purpose was to investigate the imaging characteristics of PT or MLN by applying the ${}^{18}$F-FDG PET dynamic modeling approach for non-small cell lung cancer (NSCLC). Dynamic ${}^{18}$F-FDG PET scans were performed for 76 lung cancer patients, and 62 NSCLC cases were finally included in this study: 37 with newly diagnosed early and locally advanced lung cancer without distant metastases (group M0) and 25 metastatic lung cancer (group M1). Patlak graphic analysis (K${}_i$ calculation) based on the dynamic modeling and SUV analysis from conventional static data were performed. For PT, both K${}_i$${}^{PT}$ (0.050 ± 0.005 vs 0.026 ± 0.004 min${}^{\text{â<!-- ?? -->}\text{ˆ<!-- ?? -->}\text{’<!-- ??? -->}1}$, p < 0.001) and SUV${}^{PT}$ (8.41 ± 0.64 vs 5.23 ± 0.73, p < 0.01) showed significant higher values in group M1 than M0. For MLN, K${}_i$${}^{MLN}$ showed significant higher values in M1 than M0 (0.033 ± 0.005 vs 0.016 ± 0.003 min${}^{\text{â<!-- ?? -->}\text{ˆ<!-- ?? -->}\text{’<!-- ??? -->}1}$, p < 0.01), while no significant differences were found for SUV${}^{MLN}$ between M0 and M1 (4.22 ± 0.49 vs 5.57 ± 0.59, p > 0.05). Both SUV PT and K${}_i$${}^{PT}$ showed significant high values in squamous cell carcinoma than adenocarcinoma, but neither SUV${}^{PT}$ nor K${}_i$${}^{PT}$ showed significant differences between EGFR mutants versus wild types. The overall Spearman analysis for SUV and K${}_i$ from different groups showed variable correlation (r = 0.46–0.94). The dynamic modeling for MLN (K${}_i$${}^{MLN}$) showed more sensitive than the static analysis (SUV) to detect metastatic lymph nodes in NSCLC, although both methods were sensitive for PT. This methodology of non-invasive imaging may become an important tool to evaluate MLN and PT status for patients who cannot undergo histological examination.