Predictive value of primary tumor 18F-FDG PET/CT metabolic parameters for lymph node metastasis in treatment-naïve ALK-positive NSCLC
Year: 2026
Type: article
Study design: Observational Study
Abstract: PURPOSE: F-FDG PET/CT and lymph node metastasis (LNM) in treatment-naïve anaplastic lymphoma kinase (ALK)-positive non-small cell lung cancer (NSCLC), and to evaluate their utility in discriminating the cases with radiographically occult LNM (OLNM). METHODS: F-FDG PET/CT before the treatment between October 2021 and December 2024. Primary tumor metabolic parameters, including SUVmax, SUVpeak, metabolic tumor volume (MTV), and total lesion glycolysis (TLG), were measured. Logistic regression analyses were performed to identify LNM predictors. Receiver operating characteristic curve analysis evaluated predictive performance, with area under the curve (AUC) was calculated. The relation between OLNM status and metabolic parameters of primary tumor was analyzed using Kruskal-Wallis test. RESULTS: Among 157 patients (62 males and 95 females; mean age 56 ± 11 years), 71 patients (45.2%) had pathologically confirmed LNM. Patients with LNM exhibited evidently larger primary tumor size and higher SUVmax, SUVpeak, MTV, and TLG than those without LNM (all P < 0.001). Univariate analysis showed primary tumor size, SUVmax, SUVpeak, MTV, and TLG were remarkedly associated with LNM. Multivariate analysis identified primary tumor size (OR: 1.043, 95%CI: 1.004-1.084; P = 0.032) and SUVmax (OR: 1.322, 95%CI: 1.159-1.532; P < 0.001) as independent predictors. The AUCs for tumor size, SUVmax, and combined factors were 0.76, 0.77, and 0.81, respectively. In addition, false-negative (OLNM-positive) cases showed markedly larger tumor size (P = 0.003) and higher TLG (P = 0.011) than true-negative cases. CONCLUSION: F-FDG PET/CT before treatment, particularly when combined with primary tumor size, may help stratify LNM risk in treatment-naïve ALK-positive NSCLC patients. These parameters may help identify OLNM, potentially guiding personalized lymph node dissection strategies and optimizing treatment plans.
Source: Cancer Imaging
Authors: Tingting Qiao, Jie Gu, Yangchun Chen, Juan Zhao
Institutions: Tongji University, Shanghai Pulmonary Hospital
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,790
OpenAlex ID: W7162785275