ArticleBMC medical imaging2025
Intravoxel incoherent motion and diffusion kurtosis imaging for subtype differentiation in salivary gland tumors: a diagnostic performance study.
Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveSalivary gland tumors (SGTs) have complex anatomy and diverse pathological types in the head and neck. Our study evaluates the diagnostic efficacy of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) models in differentiating benign from malignant salivary gland tumors (SGTs) and characterizing tumor subtypes.
methodsFifty histopathologically confirmed SGT patients undergoing multiparametric MRI (DKI and IVIM sequences) were stratified into four cohorts: malignant tumors (MTs, n = 18), pleomorphic adenomas (PAs, n = 15), Warthin tumors (WTs, n = 12), and other benign tumors (BTs, n = 5). Quantitative parameters including IVIM-derived true diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), and DKI-derived mean kurtosis (MK) and mean diffusivity (MD) were systematically analyzed using the receiver operating characteristic (ROC) curves in SPSS 22.0/MedCalc13.0 (significance threshold p < 0.05).
resultsBenign tumors exhibited significantly higher D (1.318 ± 0.467 × 10− 3mm2/s, P = 0.049) and MD (1.581 ± 0.577 × 10− 3 mm²/s, P = 0.027), but lower MK (0.747 ± 0.302, P = 0.008) compared to malignant tumors. Among subtypes, pleomorphic adenomas (PAs) demonstrated the highest D (1.595 ± 0.427 × 10− 3 mm²/s) and MD (1.923 ± 0.525 × 10− 3 mm²/s), while Warthin tumors (WTs) showed the highest D* (59.134 ± 11.454 × 10− 3 mm²/s, all P < 0.001). Combining D and D* achieved an AUC of 0.967 for differentiating WTs from malignancies, whereas combining D, D*, and MD improved the AUC to 0.983. MK alone perfectly discriminated PAs from malignancies (AUC = 1.000).
conclusionIVIM and DKI synergistically enhance the preoperative differentiation of SGT subtypes by quantifying tumor microstructure and perfusion. Combined parameters outperform individual metrics, offering a non-invasive tool to guide clinical decision-making.
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