Clinical Investigation
Value of 18F-FDG PET/CT metabolic parameters of primary lesions for predicting occult lymph node metastasis in non-small cell lung cancer
Shi Yunmei, Niu Rong, Wang Yuetao, Shao Xiaoliang, Zhang Feifei, Shao Xiaonan, Wang Jianfeng, Wang Xiaosong, Liu Bao, Yu Wenji
Published 2021-06-25
Cite as Chin J Nucl Med Mol Imaging, 2021, 41(6): 327-333. DOI: 10.3760/cma.j.cn321828-20200221-00061
Abstract
ObjectiveTo investigate the predictive value of 18F-fluorodeoxyglucose (FDG) PET/CT metabolic parameters for occult lymph node metastasis (OLM) in non-small cell lung cancer (NSCLC).
MethodsA total of 183 patients (72 males, 111 females; age (61.5±8.4) years) who underwent 18F-FDG PET/CT and preoperatively diagnosed with clinical N0 stage (cN0) in Third Affiliated Hospital of Soochow University from January 2013 to December 2018 were retrospectively enrolled. All patients underwent anatomical pulmonary resection with systematic lymph node dissections within 3 weeks after 18F-FDG PET/CT examinations. According to the presence or absence of lymph node metastasis, patients were divided into OLM positive (OLM+ ) group and OLM negative (OLM-) group. Parameters of primary lesions, such as the maximum diameter (Dmax), tumor sites, morphological features, maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic total volume (MTV), total lesion glycolysis (TLG), tumor SUVmax to liver SUVmean (TLRmax), tumor TLG to liver SUVmean (TLRTLG) were analyzed. Mann-Whitney U test and χ2 test were used to compare the parameters between groups. Multivariable logistic regression was used to analyze the independent risk factors for OLM. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic value of different parameters.
ResultsAmong 183 patients, 25 (13.7%, 25/183) of them were diagnosed as OLM. In OLM+ group, 46 lymph nodes were pathologically positive for metastasis, including 15 N1 disease and 31 N2 disease. Dmax (2.9(2.3, 3.7) vs 2.3(1.7, 2.8) cm), lobulation ((76.0%(19/25) vs 37.3%(59/158)), SUVmax (11.1(7.9, 17.7) vs 4.7(2.3, 9.2)), TLG (41.5(10.2, 91.1) vs 15.6(6.5, 23.8) ml), TLRmax (4.7(3.5, 7.6) vs 2.1(0.9, 4.0)) and TLRTLG (18.1(5.0, 44.3) vs 6.1(3.0, 11.4) ml) of the primary lesions in OLM+ group were significantly higher than those in OLM-group (z values: from -4.709 to -3.247, χ2=13.190, all P<0.05). Multivariable logistic regression analysis showed that TLRmax (odds ratio (OR)=15.145, 95% CI: 3.381-67.830, P<0.001) and Dmax (OR=3.220, 95% CI: 1.192-8.701, P=0.021) were independent risk factors for OLM. TLRmax yielded the highest area under curve (AUC; AUC=0.794) with the threshold of 3.12, and the sensitivity, specificity, accuracy, positive predictive value and negative predictive value for predicting OLM were 92.0%(23/25), 63.3%(100/158), 67.2%(123/183), 28.4%(23/81) and 98.0%(100/102), respectively.
ConclusionsTLRmax of tumor is the independent risk factor for OLM in NSCLC patients. TLRmax can sensitively predict OLM preoperatively in patients with NSCLC.
Key words:
Carcinoma, non-small-cell lung; Neoplasm metastasis; Lymph nodes; Positron-emission tomography; Tomography, X-ray computed; Deoxyglucose; Forecasting
Contributor Information
Shi Yunmei
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Niu Rong
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Wang Yuetao
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Shao Xiaoliang
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Zhang Feifei
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Shao Xiaonan
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Wang Jianfeng
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Wang Xiaosong
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Liu Bao
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
Yu Wenji
Department of Nuclear Medicine, the Third Affiliated Hospital of Soochow University, the First People′s Hospital of Changzhou, Changzhou Key Laboratory of Molecular Imaging, Changzhou 213003, China
