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Article Abstract

Purpose: Intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) enhances tissue diffusion assessment by differentiating true molecular diffusion from microvascular perfusion, surpassing conventional DWI. This prospective study assessed the prognostic utility of F-FDG PET/MRI with IVIM imaging in patients with primary nasopharyngeal carcinoma (NPC).

Methods: We prospectively enrolled 148 patients with primary NPC who underwent pretreatment PET/MRI. Quantitative parameters derived from IVIM-DWI, dynamic contrast-enhanced MRI (DCE-MRI), and F-FDG PET were analyzed for their associations with overall survival (OS) and recurrence-free survival (RFS).

Results: IVIM-derived minimal true diffusion coefficient (D) and perfusion-related diffusion coefficient (D*) were correlated with RFS (p = 0.018 and 0.043, respectively), outperforming the apparent diffusion coefficient (ADC; p = 0.946). Univariate analysis identified age, tumour stage, T classification, primary tumour standardized uptake value (SUVt), nodal SUV (SUVn), and total lesion glycolysis (TLG) as significant OS predictors. Significant predictors of RFS included Epstein-Barr virus DNA titer, SUVn, DCE-MRI parameters (K and V), and IVIM parameters (D* and D). In multivariate analysis, age, SUVt, and TLG were independent OS prognostic factors, whereas SUVn, K, D (p = 0.009), and V (p = 0.012) independently predicted RFS. Prognostic models incorporating the PET/MRI imaging biomarkers showed a significantly higher integrated AUC and Harrell's C-index than the TNM staging system alone.

Conclusion: Integrated PET/MRI with IVIM imaging enables simultaneous quantification of water molecule diffusion, tumor microvascular perfusion, and glucose metabolism in NPC, yielding complementary imaging biomarkers that demonstrate superior prognostic value compared to conventional TNM staging.

Trial Registration: ClinicalTrials.gov (NCT03429868), retrospectively registered on February 6, 2018.

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http://dx.doi.org/10.1007/s00259-025-07425-6DOI Listing

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