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Integrated PET-IVIM-DKI MRI for predicting lymphovascular invasion in NSCLC
Qianqian Chen1, Nan Meng1, Dujuan Li2
1Department of Radiology, Zhengzhou University People's Hospital & Henan Provincial People's Hospital, Zhengzhou, Henan, 450003, China.
Insights Into Imaging
|October 31, 2025
Summary
Combining metabolic tumor volume (MTV) and true diffusion coefficient (D) from PET-MRI scans shows high accuracy in predicting lymphovascular invasion (LVI) in non-small cell lung cancer (NSCLC). This multimodal approach offers a valuable tool for clinical management of NSCLC patients.
Area of Science:
- Radiology and Imaging Science
- Oncology
- Medical Physics
Background:
- Lymphovascular invasion (LVI) is a critical prognostic factor in non-small cell lung cancer (NSCLC).
- Accurate prediction of LVI is essential for guiding treatment decisions and improving patient outcomes.
- Current methods for LVI assessment have limitations, necessitating advanced imaging techniques.
Purpose of the Study:
- To evaluate the diagnostic performance of 18F-FDG Positron Emission Tomography (PET) and multiparametric Magnetic Resonance Imaging (MRI), including Intravoxel Incoherent Motion (IVIM) and Diffusion Kurtosis Imaging (DKI).
- To assess the combined value of PET and advanced MRI parameters in predicting LVI in NSCLC.
- To identify optimal imaging biomarkers for LVI detection in NSCLC.
Main Methods:
- A cohort of 73 NSCLC patients undergoing integrated 18F-FDG PET/MRI was analyzed.
- Quantitative PET parameters (SUVmax, MTV, TLG) and IVIM/DKI MRI parameters (ADCstand, D, MK, MD) were measured.
- Diagnostic efficacy was evaluated using Receiver Operating Characteristic (ROC) curve analysis, and logistic regression models identified independent predictors and optimal combinations.
Main Results:
- Significant differences in PET-derived (SUVmax, MTV, TLG) and MRI-derived (ADCstand, D, MK, MD) parameters were observed between patients with and without LVI (p < 0.05).
- Multivariate analysis identified metabolic tumor volume (MTV) and true diffusion coefficient (D) as independent predictors of LVI.
- The combined model of MTV and D demonstrated the highest predictive value, with an Area Under the Curve (AUC) of 0.841, sensitivity of 63.83%, and specificity of 92.31%.
Conclusions:
- Integrated 18F-FDG PET/MRI, utilizing advanced multiparametric techniques like IVIM and DKI, can effectively evaluate LVI status in NSCLC.
- Metabolic and diffusion parameters show comparable efficacy in predicting LVI, but their combination offers enhanced diagnostic performance.
- The combined model of MTV and D provides a highly valuable, non-invasive tool for LVI assessment, potentially guiding clinical management strategies for NSCLC.

