Multiparametric Ex Vivo Evaluation of Parotid Tumors: Feasibility and Preliminary Results

Parotid tumors exhibit diverse biomechanical and microstructural characteristics that remain challenging to characterize noninvasively. This study aimed to investigate these properties using ex vivo tabletop magnetic resonance elastography (MRE) combined with multiparametric MRI, including relaxometry, diffusion-weighted imaging, and fat quantification. Twelve patients (six males, six females; mean age 60.3 ± 11.2 years) undergoing parotid tumor resection were included. Resected specimens were assessed histopathologically according to the WHO Classification of Head and Neck Tumors (5th edition, 2022) and imaged within 36 h postresection using two-dimensional Bessel-MRE alongside T1 and T2 relaxometry, diffusion imaging, and fat fraction mapping. MRE-derived parameters included shear wave speed (SWS), penetration rate (PR), elasticity (μ), and viscosity (η). Compared with adjacent normal tissue, pathological tissue demonstrated significantly higher SWS (p = 0.014), elasticity (p = 0.027), viscosity (p = 0.037), and T1 relaxation time (p < 0.001), along with reduced fat fraction (p < 0.001). Penetration rate showed a near-significant increase (p = 0.065), whereas T2 exhibited no overall difference. Subtype analysis revealed that pleomorphic adenomas had significantly higher apparent diffusion coefficient (ADC) (p = 0.008), T1 (p = 0.008), and T2 (p = 0.008) values than Warthin tumors, with greater deviation from normal tissue. Correlation analysis showed that in normal tissue, fat fraction strongly influenced variability in SWS, T1, and ADC, with ADC demonstrating a strong negative correlation with fat fraction (r = -0.95, p < 0.001), limiting its interpretability without fat correction. In contrast, pathological tissue demonstrated a tightly coupled cluster of ADC, T1, and T2 (r = 0.95-0.96, all p < 0.001) reflecting water content, independent of mechanical parameters. These findings indicate that ex vivo MRE combined with multiparametric MRI enables quantitative assessment of parotid tumor properties through complementary biomarkers reflecting distinct physical mechanisms. Although viscoelastic parameters alone were insufficient to differentiate all tumor subtypes, their integration with diffusion and relaxometry metrics provides a more comprehensive characterization of tumor microstructure. This multiparametric approach shows promise for translation to in vivo applications, potentially enabling improved noninvasive tumor characterization and informing surgical planning.