The Application of Radiomics in Laryngeal Cancer Management: A Scoping Review of the Literature

Laryngeal cancer is a significant head and neck malignancy, whose prevalence is increasing. Radiomics consists of high-dimensional and reproducible quantitative data which can serve as biomarkers with strong correlations to tumor staging, prognosis, and survival outcomes. The aim of this scoping review is to summarize the knowledge from the existing literature regarding the value of radiomics in laryngeal cancer management.

Eligible articles were identified by a search of the Medline and PubMed bibliographical databases for the period up to May 2025.

This scoping review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The methodological quality of the included studies was assessed using the Radiomics Quality Score (RQS) framework.

Thirty studies were deemed eligible, including a total of 3503 patients with laryngeal cancer. Primary objectives were the development of predictive models for overall survival, progression-free survival, local control, treatment response, and staging. Across studies, radiomics-based models consistently outperformed clinical or conventional imaging-based models in predicting key outcomes. Models combining radiomic features with clinicopathological variables achieved the highest accuracy. Recent advances include the use of deep learning, which further improved predictive performance compared to traditional radiomics. However, common limitations include heterogeneity in imaging protocols, feature extraction software, and model development algorithms, as well as a lack of external validation.

Despite several limitations that currently hinder routine clinical adoption of radiomics, this rapidly evolving field demonstrates significant potential to improve staging accuracy, prognostication, and personalized management in laryngeal cancer.