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

Abstract

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 ¹⁸F-FDG PET dynamic modeling approach for non-small cell lung cancer (NSCLC). Dynamic ¹⁸F-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^-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^-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. The clinical trial registration number is NCT03679936 (http://www.clinicaltrials.gov/).