# Radiomics from Routine CT and PET/CT Imaging in Laryngeal Squamous Cell Carcinoma: A Systematic Review with Radiomics Quality Score Assessment

## TL;DR

This paper reviews how radiomics from CT and PET/CT scans can help predict outcomes in laryngeal cancer, but more standardization is needed.

## Contribution

A systematic review and quality assessment of radiomics studies in laryngeal cancer, highlighting key features and methodological gaps.

## Key findings

- Radiomic features like entropy and texture metrics show promise in predicting cancer outcomes.
- Most studies used CT, with limited external validation and small sample sizes.
- Methodological variability remains a challenge for clinical implementation.

## Abstract

This review presents a timely and thorough synthesis of the rapidly evolving field of radiomics as applied to laryngeal squamous cell carcinoma. Radiomics holds real potential as a powerful non-invasive tool for extracting quantitative imaging biomarkers from routine CT and PET/CT scans. These biomarkers offer novel opportunities to improve tumour staging, risk stratification, prognosis, recurrence prediction, and treatment response assessment in laryngeal cancer—areas where current clinical tools are limited. Our analysis of 20 relevant studies reveals consistent radiomic features such as entropy, skewness, and texture-based metrics that demonstrate promising prognostic value across multiple clinical outcomes. We also undertake a formal assessment of methodological quality using the Radiomics Quality Score (RQS). This assessment highlights substantial variability across studies, reflecting common challenges including small sample sizes, heterogeneous patient cohorts, and insufficient external validation. Together, these findings indicate that while radiomics shows promise in laryngeal cancer, improved standardisation, reproducibility, and validation are required before widespread clinical implementation.

Background/Objectives: Radiomics, the high-throughput extraction of quantitative features from medical imaging, offers a promising method for identifying laryngeal cancer imaging biomarkers. We aim to systematically review the literature on radiomics in laryngeal squamous cell carcinoma, assessing applications in tumour staging, prognosis, recurrence prediction, and treatment response evaluation. PROSPERO ID: CRD420251117983. Methods: MEDLINE and EMBASE databases were searched in May 2025. Inclusion criteria: studies published between 1 January 2010 and 31 January 2024, extracted radiomic features from CT, PET/CT, or MRI, and analysed outcomes related to diagnosis, staging, survival, recurrence, or treatment response in laryngeal cancer. Exclusion criteria: case reports, abstracts, editorials, reviews, or conference proceedings, exclusive focus on preclinical or animal models, lack of a clear radiomics methodology, or did not include imaging-based feature extraction. Results were synthesised narratively by modelling objective, alongside formal assessment of methodological quality using the Radiomics Quality Score (RQS). Results: Twenty studies met the inclusion criteria, with most using CT-based radiomics. Seven incorporated PET/CT. Radiomic models demonstrated moderate-to-high accuracy across tasks including T-staging, thyroid cartilage invasion, survival prediction, and local failure. Key predictive features included first-order entropy, skewness, and texture metrics such as size zone non-uniformity and GLCM correlation. Methodological variability, limited external validation, and small samples were frequent limitations. Conclusions: Radiomics holds strong promise as a non-invasive biomarker for laryngeal cancer. However, methodological heterogeneity identified through formal quality assessment indicates that improved standardisation, reproducibility, and multicentre validation are required before widespread clinical implementation.