This review examines radiomics for diagnosing and predicting outcomes in head and neck cancer, indicating its potential benefits.
Head and neck squamous cell carcinoma (HNSCC) is the most prevalent histopathological subtype of head and neck malignancies. Owing to the lack of early specific symptoms, the majority of patients are diagnosed at intermediate or advanced stages, which is associated with an unfavorable prognosis and a substantial decline in quality of life. Radiomics, which leverages large-scale medical imaging data, enables the extraction of high-dimensional quantitative features through advanced image analysis, thereby providing deeper insights into tumor biology. In this review, we summarize recent advances in radiomics for the diagnosis, prognostic prediction, and evaluation of treatment-related toxicity in HNSCC. Furthermore, we highlight emerging applications of radiomics in genomics and proteomics, illustrating the associations between tumor molecular phenotypes and imaging-derived features. Finally, we discuss the challenges related to feature standardization and reproducibility, and outline the key limitations of current radiomics studies.
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Wu et al. (2026) studied this question.
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