Browse by author
Lookup NU author(s): David Hamilton, Amar RajgorORCiD
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
© The Author(s), 2025.Objectives: 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. Methods: The review was pre-registered on PROSPERO (ID: CRD42024579319). A comprehensive systematic review-informed search of OVID MEDLINE, EMBASE and Global Health online databases was undertaken. 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". Results: The studies (n=6) are categorised into two groups: Radiomics for Preoperative Decision-making (n=1) and Radiomics for Treatment Outcomes (n=5). Radiomic features are significantly associated with clinical outcomes. Radiomics-based predictive models are superior to expert vision. Conclusion: Radiomics has potential for improving multiple aspects of vestibular schwannoma care; however, lack of studies inhibits firm conclusions. Prospective studies are required to progress this field.
Author(s): Gill T, Hamilton DW, Rajgor AD
Publication type: Review
Publication status: Published
Journal: Journal of Laryngology and Otology
Year: 2025
Pages: epub ahead of print
Online publication date: 27/03/2025
Acceptance date: 02/04/2018
ISSN (print): 0022-2151
ISSN (electronic): 1748-5460
Publisher: Cambridge University Press
URL: https://doi.org/10.1017/S0022215125000258
DOI: 10.1017/S0022215125000258
