Data-driven composite biomarker development for the personalised management of vestibular schwannoma

Vestibular schwannoma (VS) is a benign, non-cancerous tumour arising from one of the balance nerves connecting the brain and inner ear. At current rates, approximately 1 in 1000 people will be diagnosed with a VS in their lifetime. For patients with smaller tumours, lifelong observation with repeated scans is advised but timely treatment is crucial in patients with growing tumours.

We have previously developed a fully-automated AI framework to segment VS using MRI achieving state-of-the-art results.

Aim of the investigation:

State primary research question and where appropriate the primary hypotheses being tested

This project aims to develop a deep learning model to predict which tumours are likely to grow and require treatment. This will enable clinicians to deliver personalised and standardised management plans to individual patients and has the potential to significantly reduce the number of required surveillance scans.