The value of dual time-point fluorine-18 fluorodeoxyglucose PET/computed tomography imaging in predicting lymph node metastasis in non-small cell lung cancer patients.

Objective: The purpose of this study was to analyze the correlation between specified dual time-point fluorine-18 fluorodeoxyglucose ( 18 F-FDG) PET/computed tomography (CT) imaging parameters and pathological characteristics in non-small cell lung cancer (NSCLC) patients.

Methods: This study retrospectively analyzed 47 patients with NSCLC. All patients underwent dual time-point 18 F-FDG PET/CT imaging. We obtained the metabolic parameters, standardized uptake value (SUV) maximum, SUV mean , delayed standardized uptake value (DSUV) maximum, DSUV mean , delay index standardized uptake value (DISUV) maximum, and DISUV mean , of the primary tumor. The tumor size was measured by CT. All lymph nodes had a definite pathological diagnosis. We next evaluated the status of the lymph node metastases (LNM) and the correlations between metabolic parameters and clinical characteristics. Receiver operating characteristic curves were drawn for the prediction of LNM.

Results: We found that the DSUV max , DISUV max , DSUV mean , and tumor size were significantly related to LNM ( P  = 0.036, 0.009, and 0.049, respectively). Multivariate analysis revealed that tumor size and DISUV max were independent risk factors for LNM in lung cancer patients. According to the receiver operating characteristic curve analysis, the optimal cutoff values for DISUV max and tumor size were 0.33 and 2.8 cm, respectively. When these two parameters were combined, the area under the curve for predicting LNM in NSCLC was 0.768, and the sensitivity was 95.7% for predicting LNM in lung cancer patients. We further allocated the patients to three groups: the high-risk group (tumor size ≥ 2.8 cm, DISUV max  ≥ 0.33), the moderate-risk group (tumor size ≥ 2.8 cm, DISUV max  < 0.33, or tumor size < 2.8 cm, DISUV max  ≥ 0.33), and the low-risk group (tumor size < 2.8 cm, DISUV max  < 0.33). The rates of LNM were 70, 50, and 0%, respectively.

Conclusion: Tumor size and DISUV max are risk factors for predicting LNM, and they are more useful in combination. Compared with standard PET/CT imaging, dual time-point PET/CT imaging has added value in predicting LNM in NSCLC patients.