Multiparametric MRI for Assessing the Tumor Microenvironment in Head and Neck Cancer: A Narrative Review

Background and Objectives: Head and neck cancers are heterogeneous malignancies with variable biological behavior and treatment response, contributing to high morbidity and mortality. Conventional imaging techniques are limited in their ability to capture tumor biology, highlighting the need for advanced functional imaging. This review aims to evaluate the role of multiparametric magnetic resonance imaging (MRI) in characterizing the tumor microenvironment. Materials and Methods: A narrative review was conducted based on a targeted literature search of databases, including PubMed and Google Scholar. Studies addressing advanced MRI techniques for assessing tumor cellularity, vascularity, molecular features, and oxygenation were selected and analyzed. Results: Perfusion techniques, such as dynamic contrast-enhanced MRI (DCE-MRI) and arterial spin labeling (ASL), provide a quantitative assessment of tumor vascularity and show value in predicting treatment response. Diffusion-based methods, including diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), enable evaluation of tissue cellularity and heterogeneity. Molecular approaches, such as chemical exchange saturation transfer (CEST) and amide proton transfer (APT), offer insights into protein content and proliferation. Oxygenation-sensitive techniques, such as blood oxygenation level dependent MRI (BOLD MRI) and oxygen-enhanced MRI (OE-MRI), allow non-invasive assessment of tumor hypoxia. Conclusions: Multiparametric MRI provides a comprehensive and biologically relevant evaluation of the tumor microenvironment in head and neck cancer, with potential to improve treatment prediction and support personalized therapeutic strategies.