SEMINARIO: From Concept to Clinic: Magnetic Resonance Elastography for Parotid Tumor Characterization

Abstract:
Parotid glands are among the most frequent sites of salivary gland tumors, yet their non-invasive characterization remains a diagnostic challenge. Conventional imaging methods provide limited quantitative information, often failing to distinguish healthy tissue from neoplastic lesions or to differentiate between benign and malignant tumors. Magnetic resonance elastography (MRE), a technique
that maps the biomechanical properties of soft tissues, offers a promising solution to these limitations. Widely established in liver and brain imaging, MRE enables quantitative assessment of tissue stiffness, which can reect underlying pathological changes. However, its application to the parotid glands has been hampered by anatomical constraints and the need for high-resolution elastography.
To address these challenges, a novel passive driver system tailored to the anatomy of the human face was developed to deliver high-frequency shear waves directly to the parotid region, thereby reducing wave attenuation and improving image quality. Using this approach, MRE of parotid tumors has been successfully demonstrated in a clinical setting. Initial studies indicate that different tumor types exhibit distinct stiffness profiles, and that tumor stiness consistently exceeds that of healthy parotid tissue. These findings highlight the potential of MRE as a complementary imaging tool for tumor characterization and differential diagnosis.

Figure (1). Custom passive driver built for this study (A), and exemplary images from a patient with a Warthin tumor in the left parotid gland: axial T2w scan (B), 0-8 kPa stiffness map (C), and wave propagation image (D). The tumor area is indicated with white arrows.

From concept development and hardware innovation to preliminary clinical evaluation, MRE of the parotid glands is transitioning from a technical feasibility study to a method with potential clinical utility. With further validation in larger patient cohorts, this technique could provide a non-invasive biomarker for tumor classification, contributing to improved diagnostic condence and potentially influencing treatment planning in salivary gland oncology.

About the speaker:
Vitaliy Atamaniuk is a researcher at the Rzeszów University of Technology and University of Rzeszów, pursuing a PhD in Physical Sciences with a focus on medical imaging. His research centers on the development and optimization of magnetic resonance elastography (MRE) techniques, particularly for abdominal and head and neck applications. He is a recipient of the prestigious NCN PRELUDIUM research grant, which supports my work on advanced driver systems for MRE. He is actively collaborate on projects involving image reconstruction, motion correction using deep learning, and quantitative imaging biomarkers. Together with clinical teams he works on translating research into practical diagnostic tools. My work bridges the fields of medical physics, artificial intelligence, and radiology.