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

前庭神经鞘瘤(VS)是一种良性、非癌性肿瘤，起源于连接大脑和内耳的平衡神经之一。按照目前的速度，在他们的一生中，大约每1000人中就有1人被诊断出患有VS。对于肿瘤较小的患者，建议通过重复扫描进行终身观察，但对于肿瘤不断增长的患者，及时治疗至关重要。我们之前已经开发了一个全自动化的人工智能框架来使用MRI分割VS，获得了最先进的结果。调查目的：陈述主要研究问题，以及在适当的情况下正在测试的主要假设。该项目旨在开发一个深度学习模型，以预测哪些肿瘤可能生长并需要治疗。这将使临床医生能够向个别患者提供个性化和标准化的管理计划，并有可能显著减少所需的监测扫描次数。

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.