Radiomics has been widely explored as a non-invasive biomarker in head and neck squamous cell carcinoma (HNSCC). Despite extensive investigation, its definitive clinical role remains unclear. The review frames radiomics not as a replacement for established tissue-based markers, but as a method to provide spatial context that complements those biomarkers. Prior work on radiomics, image-biomarker standardization, and computational radiomics systems is cited as the foundation for translating image-derived quantitative features into phenotypic information.
Tissue biomarkers differ in how susceptible they are to spatial sampling. Markers such as PD-L1 expression, immune-cell infiltration, necrosis, and immune exclusion often have substantial spatial heterogeneity across a tumor. In contrast, HPV/p16 status and certain genomic alterations are generally more stable across different tumor regions. Because clinical decisions are sometimes based on limited, localized biopsy samples, there is a risk that biopsy-derived biomarkers may not reflect the full intratumoral landscape in situations where heterogeneity matters.
The review synthesizes evidence linking radiomic features to biological processes that are spatially heterogeneous. Radiomic signatures have been associated with patterns consistent with hypoxia, necrotic regions, stromal architecture, and immune exclusion phenotypes. By quantifying intra- and peritumoral imaging characteristics, radiomics can reveal heterogeneity that localized tissue sampling may miss. The article emphasizes that radiomic features can function as spatial surrogates for microenvironmental states rather than direct replacements for molecular assays.
The authors map radiomic phenotypes to specific clinical decision scenarios. Examples discussed include:
Larynx preservation decisions, where knowledge of spatial heterogeneity (for instance, necrotic or hypoxic subregions) could influence the choice between organ-preserving therapy and more definitive interventions.
Immunotherapy stratification, where radiomic indicators of immune exclusion or heterogeneous immune infiltration may highlight cases in which PD-L1 or other biopsy-based immune biomarkers could be non-representative.
Recurrence assessment and surveillance, in which radiomic patterns in primary or surrounding tissue might inform the interpretation of risk and guide follow-up intensity.
Across these scenarios, the review argues that radiomics is valuable as complementary spatial information that helps identify when biopsy-derived markers should be interpreted with caution.
The review acknowledges methodological issues relevant to radiomics research. It references initiatives and literature addressing standardization and reproducibility, including the Image Biomarker Standardization Initiative and systematic reviews of repeatability and reproducibility of radiomic features. Much of the existing evidence in HNSCC is retrospective. The authors note that delta radiomics, serial multiparametric imaging, and combined intratumoral and peritumoral habitat analyses have been reported in related studies, but prospective validation in clinical workflows remains limited according to the review.
The article presents conceptual figures describing radiomic phenotypes that reflect spatial heterogeneity in HNSCC and a context-specific framework for interpreting these phenotypes across major clinical scenarios. These conceptual models illustrate how clusters of radiomic features may correspond to biologically meaningful habitats—such as hypoxic, necrotic, or immune-excluded regions—and how those phenotypes could be applied to decision-making points like larynx preservation and immunotherapy selection.
The review stresses that radiomics should not be presented as a standalone predictor supplanting established biomarkers. Rather, it is a pragmatic framework to integrate spatial information into biomarker-guided clinical workflows. The authors highlight that the bulk of current evidence is retrospective and that further work is needed to standardize methods, ensure reproducibility, and prospectively evaluate how spatial radiomic information impacts clinical decisions and outcomes.
No new data were generated or analyzed for the review; therefore, data sharing is not applicable. The article references standardization efforts and reproducibility reviews in the field, underscoring the importance of methodological rigor when translating radiomic phenotypes into clinical practice.