Radiomics refers to converting medical images into high-quality quantitative data. This review examines applications of radiomics in vestibular schwannomas and future considerations for translation into clinical practice.

The review was pre-registered on Prospero (ID: CRD42024579319). A comprehensive systematic review-informed search of the Ovid Medline, Embase and Global Health online databases was undertaken using the keywords ‘acoustic neuroma’ or ‘vestibular schwannoma’ or ‘cerebellopontine angle tumour’ or ‘cerebellopontine tumour’ or ‘head and neck cancer’ were combined with ‘radiomic’ or ‘signature’ or ‘machine learning’ or ‘artificial intelligence’.

The studies (n = 6) were categorised into two groups: radiomics for pre-operative decision-making (n = 1) and radiomics for treatment outcomes (n = 5). Radiomic features were significantly associated with clinical outcomes. Radiomics-based predictive models were superior to expert vision.

Radiomics has potential for improving multiple aspects of vestibular schwannoma care, but lack of studies inhibited firm conclusions. Prospective studies are required to progress this field.

Our centre (Freeman Hospital, Newcatle Upon Tyne NHS Trust) has favoured primary surgery over chemoradiotherapy for specific advanced laryngeal cancer patients (e.g. large-volume tumours, airway compromise, significant dysphagia, T4 disease). This study reports the survival outcomes for a modern, high-volume head and neck centre favouring surgical management to determine whether this approach improves survival.

Retrospective analysis of patient data over a seven-year period from a tertiary cancer centre.

In total, 121 patients were identified with T3 (n = 76) or T4 (n = 45) laryngeal cancer (mean follow up 2.9 years). In the cohort treated with curative intent (n = 104, 86.0 per cent), the 2- and 5-year estimated disease-specific survival rates were 77.9 and 64.1 per cent. chemoradiotherapy had the highest 2-year disease-specific survival (92.5 per cent), followed by surgery with adjuvant therapy (81.8 per cent), radiotherapy alone (75 per cent) and surgery alone (72.4 per cent).

For a centre favouring primary surgery for certain advanced laryngeal cancers, the disease-specific survival appears no higher than that found in the published literature. To enhance survival, future research should focus on precision medicine to define treatment pathways in this disease.

Advanced laryngeal cancers are clinically complex; there is a paucity of modern decision-making models to guide tumour-specific management. This pilot study aims to identify computed tomography-based radiomic features that may predict survival and enhance prognostication.

Pre-biopsy, contrast-enhanced computed tomography scans were assembled from a retrospective cohort (n = 72) with advanced laryngeal cancers (T3 and T4). The LIFEx software was used for radiomic feature extraction. Two features: shape compacity (irregularity of tumour volume) and grey-level zone length matrix – grey-level non-uniformity (tumour heterogeneity) were selected via least absolute shrinkage and selection operator-based Cox regression and explored for prognostic potential.

A greater shape compacity (hazard ratio 2.89) and grey-level zone length matrix – grey-level non-uniformity (hazard ratio 1.64) were significantly associated with worse 5-year disease-specific survival (p < 0.05). Cox regression models yielded a superior C-index when incorporating radiomic features (0.759) versus clinicopathological variables alone (0.655).

Two radiomic features were identified as independent prognostic biomarkers. A multi-centre prospective study is necessary for further exploration. Integrated radiomic models may refine the treatment of advanced laryngeal cancers.