Prediction of lymph node metastasis in non-small cell lung cancer and its correlation with Ki-67 expression: a comparative study between intravoxel incoherent motion imaging and 18F-FDG PET

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Authors: Wei Wei, Q Chen, Nan Meng, Xinyu Wang, Yue Liu, J W Zhang, Yaping Wu, Jiayin Pan, Zhun Huang, Yang Yang, Zhe Wang, Qiuyu Liu
+2 more Fangfang Fu, Meiyun Wang
Cited by: 0
References: 32

Abstract

BACKGROUND: Integrated positron emission tomography/magnetic resonance (PET/MRI) may have the potential to evaluate lymph node metastasis (LNM) status and Ki-67 proliferation index in patients with non-small cell lung cancer. METHODS: This study enrolled 92 pathologically confirmed NSCLC patients. Quantitative analysis of metabolic parameters, such as maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), and IVIM parameters including apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), and distributed diffusion coefficient (DDC). The predictive performance of each parameter for LNM was assessed using receiver operating characteristic (ROC) curve analysis, and a multivariate logistic regression model was constructed to establish the optimal combined predictive model. Spearman correlation analysis was used to explore the relationship between imaging parameters and Ki-67 expression. RESULTS: LNM prediction: The LNM-positive group exhibited lower ADC, D, and DDC (all P < 0.05) compared to the LNM-negative group. Multivariate analysis identified MTV and DDC as independent predictors of LNM. The combined model (MTV + DDC) achieved an AUC of 0.821 (sensitivity 79.49%, specificity 73.59%), significantly outperforming individual parameters (P < 0.05). Ki-67 correlation: SUVmax, MTV, and TLG showed positive correlations with Ki-67 (r = 0.232 to -0.300, P < 0.05), while ADC and D values exhibited negative correlations (r = − 0.327 to − 0.240, P < 0.05). No significant association was observed between D*, f, and Ki-67 (P > 0.05). CONCLUSION: Integrated PET/MRI, by combining metabolic (MTV) and diffusion (DDC) parameters, significantly improves the predictive accuracy for LNM in NSCLC. Additionally, metabolic and select IVIM parameters correlate with Ki-67 expression.

Fields of Study & Subjects

MRI in cancer diagnosis Lung Cancer Diagnosis and Treatment Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
BMC Medical Imaging
Publisher
Springer Science and Business Media LLC
Volume
26
Issue
1
Pages
64–64
Publication date
3 January 2026
Language
EN