Faheem Bhatti
Apparent diffusion coefficient for genetic characterisation of untreated adult gliomas: a meta-analysis stratified by methods
Bhatti, Faheem; Strobel, Joachim; Tench, Christopher; Grech-Sollars, Matthew; Dineen, Robert A; Sollmann, Nico; Thust, Stefanie
Authors
Joachim Strobel
Christopher Tench
Matthew Grech-Sollars
Professor Rob Dineen rob.dineen@nottingham.ac.uk
PROFESSOR OF NEURORADIOLOGY
Nico Sollmann
Stefanie Thust
Abstract
Background
Isocitrate dehydrogenase (IDH) mutation and chromosome 1p19q genotyping have become fundamental to the prognostic grouping of adult diffuse gliomas. Apparent diffusion coefficient (ADC) values may enable non-invasive prediction of glioma molecular status. The purpose of this systematic review and meta-analysis was to investigate the diagnostic accuracy of ADC for IDH and 1p19q genotyping, considering measurement techniques and tumour grade.
Methods
A systematic search of PubMed and Cochrane Library databases was performed in December 2024. Studies were grouped according to the ADC parameter measured and the measurement techniques used. A meta-analysis was performed, supplemented by Egger’s regression testing. The quality of studies was assessed with the QUADAS-2 tool.
Results
Thirty-three studies including a total of 4297 patients fulfilled the inclusion criteria. IDH mutation and 1p19q deletion status were assessed by 30 and 14 studies respectively. Pooled area under the curve (AUC) values for the prediction of an IDH mutation and 1p19q codeletion ranged from 0.743 (0.680-0.805) to 0.804 (0.689-0.919), and 0.678 (0.614-0.741) to 0.692 (0.600-0.783). No significant differences were identified between regional and volumetric measurements, between ADCmean and ADCmin values, or comparing normalised and raw ADC data.
Conclusion
This meta-analysis supports ADC as an imaging biomarker in untreated gliomas, specifically to predict IDH status. ROI measurement, particularly by a single ADCmean, is rapid, reproducible and appears statistically equivalent to volumetric read outs. We found no evidence for superior diagnostic accuracy by ADC normalisation. Published ADC thresholds have been summarised for consideration of prospective testing across institutions.
Citation
Bhatti, F., Strobel, J., Tench, C., Grech-Sollars, M., Dineen, R. A., Sollmann, N., & Thust, S. (2025). Apparent diffusion coefficient for genetic characterisation of untreated adult gliomas: a meta-analysis stratified by methods. Neuro-Oncology Advances, 7(1), Article vdaf103. https://doi.org/10.1093/noajnl/vdaf103
Journal Article Type | Article |
---|---|
Acceptance Date | Feb 14, 2025 |
Online Publication Date | May 22, 2025 |
Publication Date | 2025 |
Deposit Date | May 30, 2025 |
Publicly Available Date | Jun 5, 2025 |
Journal | Neuro-Oncology Advances |
Electronic ISSN | 2632-2498 |
Publisher | Oxford University Press (OUP) |
Peer Reviewed | Peer Reviewed |
Volume | 7 |
Issue | 1 |
Article Number | vdaf103 |
DOI | https://doi.org/10.1093/noajnl/vdaf103 |
Public URL | https://nottingham-repository.worktribe.com/output/49118948 |
Publisher URL | https://academic.oup.com/noa/advance-article/doi/10.1093/noajnl/vdaf103/8140424 |
Files
vdaf103
(1.5 Mb)
PDF
Licence
https://creativecommons.org/licenses/by/4.0/
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
Copyright Statement
© The Author(s) 2025. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
You might also like
Bleeding with intensive versus guideline antiplatelet therapy in acute cerebral ischaemia
(2023)
Journal Article
Diffusion-based structural connectivity patterns of multiple sclerosis phenotypes
(2023)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search