Structured reporting of gliomas based on VASARI criteria to improve report content and consistency
Tumour size and anatomical information is often omitted by neuroradiologists. Comparison with a structured report identified key features that would benefit from standardisation and/or quantification. Structured reporting may improve glioma reporting consistency, clinical communication, and treatment decisions.
Authors
- Stefanie Thust (ORCID: https://orcid.org/0000-0001-5136-6000)
- Olivia Goodkin (ORCID: https://orcid.org/0000-0001-9283-9716)
- John A. Thornton (ORCID: https://orcid.org/0000-0001-9976-9714)
- Jiaming Wu (ORCID: https://orcid.org/0000-0001-6533-8780)
- Ferrán Prados (ORCID: https://orcid.org/0000-0002-7872-0142)
- Sotirios Bisdas (ORCID: https://orcid.org/0000-0001-9930-5549)
- Frederik Barkhof (ORCID: https://orcid.org/0000-0003-3543-3706)
- Hugh Pemberton (ORCID: https://orcid.org/0000-0001-8419-6423)
- Sjoerd B. Vos (ORCID: https://orcid.org/0000-0002-8502-4487)
- Tarek Yousry (ORCID: https://orcid.org/0000-0003-3295-0628)
Institutions
- Universitat Oberta de Catalunya (ES)
- University of Nottingham (GB)
- Queen Mary University of London (GB)
- The University of Western Australia (AU)
- Amersham Hospital (GB)
- National Institute for Health and Care Research (GB)
- Institute of Mental Health (GB)
- Nottingham Biomedical Research Centre (GB)
- National Hospital for Neurology and Neurosurgery (GB)
- University College London (GB)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2025-03-24
- DOI
- https://doi.org/10.1186/s12880-025-01603-6
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute for Health and Care Research
- University College London Hospitals NHS Foundation Trust