Dynamic fluorine-18 fluorodeoxyglucose PET for evaluating different-sized metastatic lymph nodes in patients with non-small cell lung cancers.

BACKGROUND

For patients with non-small cell lung cancer (NSCLC), accurate and detailed lymph node (LN) staging is crucial for treatment planning and prognosis. However, reliably distinguishing metastatic from nonmetastatic LNs remains a clinical challenge, especially in small-sized LNs. A retrospective study was conducted to evaluate the ability of dynamic fluorine-18 fluorodeoxyglucose (F-18 FDG) positron emission tomography (PET), specifically the metabolic parameter of net influx rate (Ki), in distinguishing metastatic from and nonmetastatic LNs of different sizes in patients with NSCLC.

METHODS

In the study, 366 patients with lung nodules or masses detected on chest computed tomography (CT) scan underwent dynamic chest F-18 FDG PET/CT and static whole-body F-18 FDG PET/CT imaging after providing informed consent. A retrospective collection of 369 LNs in 98 patients with NSCLC was pathologically confirmed. CT features [density, maximum short diameter (Dmax), ratio of LN long diameter to short diameter (L/S), and ratio of LN density to muscle density (DR)] and static PET features [maximum standardized uptake value (SUVmax) and ratio of LN SUVmax to mediastinal blood pool SUVmax (SUVR)] of the LNs were measured. The Ki was also obtained through the application of an irreversible two-tissue compartment model. CT features, PET features, and Ki were compared between the metastatic and nonmetastatic LNs via the Wilcoxon rank-sum test. Receiver operating characteristic (ROC) analysis was performed for each parameter. Differences in area under the curve (AUC) were assessed via the DeLong test. Differences in sensitivity and specificity at a given threshold were compared using χ2 test. P<0.05 was considered statistically significant.

RESULTS

Among the 369 LNs, 172 were metastatic, and 197 were nonmetastatic. The CT features, static PET features, and Ki were significantly different between the metastatic and nonmetastatic LNs (P<0.05). The AUCs of Dmax, SUVmax, SUVR, and Ki were 0.852, 0.894, 0.888, and 0.936, respectively, while those of other features were <0.50. The optimal cutoff values were 1.00 cm for Dmax, 7.65 for SUVmax, 4.54 for SUVR, and 0.018 mL/g/min for Ki. The Delong test was carried out on the features with an AUC above 0.8 and showed that Ki had a higher diagnostic efficacy compared to the other features (P<0.05). In the groups of LNs with Dmax ≥1 cm and Dmax <1 cm, the AUCs were 0.884 and 0.836 for SUVmax, 0.878 and 0.813 for SUVR, and 0.910 and 0.894 for Ki, respectively. The Delong test showed that Ki had higher diagnostic efficacy than did SUVmax and SUVR in the Dmax <1 cm group (P<0.05) but not in the Dmax ≥ 1 cm group.

CONCLUSIONS

Compared with static PET features and CT features, the dynamic PET parameter Ki demonstrated superior diagnostic performance in differentiating metastatic from nonmetastatic LNs, particularly in the group of small LNs. After optimization of the cutoff value, the Ki improved the clinical applicability in identifying metastatic LNs.