SynthesisEuropean radiology2026
Diagnostic value of MR black-blood thrombus imaging, contrast-enhanced MRI, and noncontrast-enhanced MR venography in cerebral vein thrombosis: a systematic review and meta-analysis.
Synthesis in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Intracranial venous thrombosis imaging by anatomical location: an educational review with mimics and diagnostic pitfalls.Insights into imaging · 2026Article
- Venous thromboembolism in China: epidemiology, management strategies, and future directions.Research and practice in thrombosis and haemostasis · 2026Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe diagnosis of cerebral venous thrombosis (CVT) remains challenging due to limited consensus on the optimal imaging modality. MR black-blood thrombus imaging (MRBTI), contrast-enhanced MR imaging (CE-MRI), and noncontrast-enhanced MR venography (NCE-MRV) are promising modalities. This study aims to evaluate the performance of these modalities in diagnosing CVT. MATERIALS AND
methodsPubMed, Web of Science, and Embase databases were systematically searched from inception to March 2025. Studies evaluating the diagnostic accuracy of MRBTI, CE-MRI, and NCE-MRV for CVT were included. A bivariate random-effects model was used to calculate the summary accuracy metrics with 95% confidence intervals (CIs). Sources of heterogeneity were explored through meta-regression, subgroup analysis, and sensitivity analysis. Publication bias was assessed using Deeks' funnel plot.
resultsFifteen studies involving 49 cohorts (1401 patients and 4846 venous segments) were included. MRBTI achieved significantly higher sensitivity, 98% (95% CI: 95-99%), and specificity, 99% (95% CI: 97-100%) than CE-MRI and NCE-MRV (p < 0.05 for both). NCE-MRV (89%; 95% CI: 78-95%) demonstrated higher sensitivity than CE-MRI (76%; 95% CI: 67-83%) (p = 0.045), at the expense of specificity (NCE-MRV: 89%, 95% CI: 79-94%; CE-MRI: 97%, 95% CI: 93-98%; p = 0.04). Study design influenced heterogeneity in both MRBTI and CE-MRI studies, with diagnostic level and scanning mode affecting heterogeneity in MRBTI and CE-MRI, respectively.
conclusionMRBTI demonstrated superior diagnostic accuracy for CVT compared to CE-MRI and NCE-MRV. Prospective multi-center studies are required to standardize MRBTI protocols and validate its reliability as a standalone diagnostic modality for CVT. KEY POINTS: Question The diagnostic accuracy for CVT of MRBTI, CE-MRI, and NCE-MRV remains unclear. Findings Pooled data demonstrate that MRBTI exhibits superior diagnostic performance for CVT in comparison with CE-MRI and NCE-MRV. Clinical relevance MRBTI demonstrates high diagnostic accuracy for CVT, facilitating earlier diagnosis and improving patient outcomes. Further studies should standardize MRBTI protocols and validate its reliability as a standalone diagnostic tool for CVT, thereby optimizing workflow, reducing scan time, and improving cost-effectiveness.
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Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.