Current evidence in application of habitat imaging analysis in head and neck cancer: a systematic review

Purposes Habitat imaging analysis has recently been applied to head and neck cancer (HNC) imaging research for various clinical applications. This review systematically evaluated current evidence on its performance in various HNC applications, highlighting its advantages and limitations. Methods A systematic search of PubMed, Web of Science, and Scopus was conducted for articles from database inception to 30 January 2026, using terms related to habitat analysis, HNC, and medical imaging. Patient numbers, tumour origin, imaging modality, clustering features, habitat methods, subregion numbers, clinical applications, and performance of the models were extracted from the included articles. Results Twenty-five original articles published between 2019 and 2026 were eligible for analysis, of which 10 had external validation datasets. Nasopharyngeal carcinoma was the most studied HNC ( n = 9); CT was the most used modality ( n = 9); and K-means clustering was the predominant habitat method ( n = 20). Habitat imaging analysis performed consistently well and outperformed conventional radiomics or clinical models in predicting pathological/immunohistochemical (IHC) biomarkers, cancer characterisation and nodal status, with areas under the curve (AUCs) of > 0.8, but showed variable results for treatment response prediction. Combining the multiple models slightly improved performances in most studies. Conclusion Habitat imaging analysis showed potentials in various applications in HNC, performing consistently well in predicting pathological/IHC biomarker, tumour characterisation and nodal status, but not in treatment response prediction. Combining multiple models slightly improved performance, raising questions about whether such complex integrations offer clinical value. Current evidence remains heterogeneous, and so prospectively conducted and externally validated studies are required to clarify their practical utility.