Influx rate constant of 18F-FDG increases in metastatic lymph nodes of non-small cell lung cancer patients

Purpose 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 F-18-FDG PET dynamic modeling approach for non-small cell lung cancer (NSCLC). Methods Dynamic F-18-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. Results For PT, both K-i(PT) (0.050 +/- 0.005 vs 0.026 +/- 0.004 min(-1), p < 0.001) and SUVPT (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(-1), p < 0.01), while no significant differences were found for SUVMLN 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 SUVPT 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). Conclusion 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.