Heterogeneity Analysis of (18)F-FDG Uptake in Differentiating Between Metastatic and Inflammatory Lymph Nodes in Adenocarcinoma of the Lung: Comparison with Other Parameters and its Application in a Clinical Setting.

Abstract

Lymph node (LN) characterization is crucial in determining the stage and treatment decisions in patient with lung cancer. Although (18)F-fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) has a higher diagnostic accuracy in LN characterization than anatomical imaging, differentiating between metastatic and inflammatory LNs is still challenging because both could show high (18)F-FDG uptake. The purpose of this study was to assess if the heterogeneity of the (18)F-FDG uptake could help in differentiating between inflammatory and metastatic LNs in lung cancer, and to compare with other parameters. A total of 44 patients with adenocarcinoma of the lung, who underwent preoperative (18)F-FDG PET/CT without having any previous treatments and were revealed to have (18)F-FDG-avid LNs, were enrolled. There were 52 pathology-proven metastatic lymph nodes in 26 subjects. The pathology-proven metastatic LNs were compared with 42 pathology-proven inflammatory/benign LNs in 18 subjects. The coefficient of variation (CV) was used to assess the heterogeneity of (18)F-FDG uptake by dividing the standard deviation of standardized uptake value (SUV) by mean SUV. The volume of interest was manually drawn based on the combined CT images of (18)F-FDG PET/CT (no threshold is used). Comparisons were made with the maximum standardized uptake values (SUVmax), visual assessment of (18)F-FDG uptake, longest diameter, and maximum Hounsfield units (HUmax). Metastatic lymph nodes tended to have higher CVs than the inflammatory LNs. The mean CV of metastatic LNs (0.30 ± 0.08; range: 0.08-0.55) was higher than that of inflammatory LNs (0.17 + 0.06; range, 0.07-0.32; P < 0.0001). On receiver operating characteristic (ROC) curve analysis, the area under curve was 0.901, and using 0.20 as cut-off value, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were 88.5%, 76.2%, 82.2%, 84.3, and 83.0% respectively. Accuracy of CV was slightly higher than SUVmax and diameter, but significantly higher than visual assessment and HUmax. In patients with adenocarcinoma of the lung having no prior treatments, metastatic LNs showed more heterogeneous (18)F-FDG uptake than inflammatory LNs. Measuring the CV of the SUV derived from a manual volume of interest (VOI) can be helpful in determining metastatic LN of adenocarcinoma of the lung. Including diagnostic criteria of CV into the diagnostic approach can increase the accuracy of mediastinal node status.