Gill Terrenjit, Hamilton David, Rajgor Amarkumar
GKT School of Medical Education, Faculty of Life Sciences and Medicine, King's College London, London, UK.
Newcastle University, Newcastle upon Tyne, UK.
J Laryngol Otol. 2025 Aug;139(8):647-654. doi: 10.1017/S0022215125000258.
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 ( = 6) were categorised into two groups: radiomics for pre-operative decision-making ( = 1) and radiomics for treatment outcomes ( = 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.
放射组学是指将医学图像转化为高质量定量数据。本综述探讨放射组学在前庭神经鞘瘤中的应用以及转化为临床实践的未来考量。
该综述已在国际系统评价前瞻性注册库（Prospero）上预注册（ID：CRD42024579319）。使用关键词“听神经瘤”或“前庭神经鞘瘤”或“桥小脑角肿瘤”或“桥小脑肿瘤”或“头颈癌”与“放射组学”或“特征”或“机器学习”或“人工智能”相结合，对Ovid Medline、Embase和Global Health在线数据库进行了全面的系统评价知情检索。
纳入的研究（n = 6）分为两组：用于术前决策的放射组学（n = 1）和用于治疗结果的放射组学（n = 5）。放射组学特征与临床结果显著相关。基于放射组学的预测模型优于专家判断。
放射组学在改善前庭神经鞘瘤治疗的多个方面具有潜力，但研究的缺乏阻碍了得出确凿结论。需要开展前瞻性研究以推动该领域发展。
