Structured reporting of gliomas based on VASARI criteria to improve report content and consistency

Olivia Goodkin, Jiaming Wu, Hugh Pemberton, Ferran Prados, Sjoerd B Vos, Stefanie Thust, John Thornton, Tarek Yousry, Sotirios Bisdas, Frederik Barkhof

Research output: Contribution to journalArticlepeer-review

Abstract

PURPOSE: Gliomas are the commonest malignant brain tumours. Baseline characteristics on structural MRI, such as size, enhancement proportion and eloquent brain involvement inform grading and treatment planning. Currently, free-text imaging reports depend on the individual style and experience of the radiologist. Standardisation may increase consistency of feature reporting.

METHODS: We compared 100 baseline free-text reports for glioma MRI scans with a structured feature list based on VASARI criteria and performed a full second read to document which VASARI features were in the baseline report.

RESULTS: We found that quantitative features including tumour size and proportion of necrosis and oedema/infiltration were commonly not included in free-text reports. Thirty-three percent of reports gave a description of size only, and 38% of reports did not refer to tumour size at all. Detailed information about tumour location including involvement of eloquent areas and infiltration of deep white matter was also missing from the majority of free-text reports. Overall, we graded 6% of reports as having omitted some key VASARI features that would alter patient management.

CONCLUSIONS: 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.

Original languageEnglish
Article number99
Pages (from-to)99
JournalBMC Medical Imaging
Volume25
Issue number1
Early online date24 Mar 2025
DOIs
Publication statusE-pub ahead of print - 24 Mar 2025

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