ArticleNeuro-oncology advances
Apparent diffusion coefficient for genetic characterization of untreated adult gliomas: A meta-analysis stratified by methods.
Article in Neuro-oncology advances. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Diffusion histogram analysis predicts progression-free survival in contrast enhancing recurrent IDH mutant gliomas treated with bevacizumab.Journal of neuro-oncology · 2026Article
- Imaging biomarkers for detecting IDH mutations and monitoring response to novel targeted therapies: Current insights and future perspectives.Neuro-oncology · 2026Review
- Apparent diffusion coefficient predicts MGMT status in adult-type diffuse gliomas and is correlated with Ki-67 proliferation index.Frontiers in oncology · 2025Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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 noninvasive 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 tumor 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 normalized and raw ADC data. Conclusions: This meta-analysis supports ADC as an imaging biomarker in untreated gliomas, specifically to predict IDH status. ROI measurement, particularly by a single ADC
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