Evidence map›Paper›PMID 39976739›Full record

SynthesisEuropean radiology2025

Intracranial atherosclerotic plaque features on vessel wall imaging predict first ever and recurrence of stroke: a meta-analysis.

Jinhuan Zhang, Beibei Sun, Huayu Wang, Hanrui Shi, Qiuting Wen, Mahmud Mossa-Basha, Chengcheng Zhu

Abstract readMeta-AnalysisReview
In one paragraph

Synthesis in European radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
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  4. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jinhuan ZhangShenzhen Traditional Chinese Medicine Hospital/The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.
Beibei SunDepartment of Radiology, University of Washington School of Medicine, Seattle, WA, USA. alisabeibei@163.com.
Huayu WangDepartment of Radiology, University of Washington School of Medicine, Seattle, WA, USA.
Hanrui ShiDepartment of Radiology, University of Washington School of Medicine, Seattle, WA, USA.
Qiuting WenDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
Mahmud Mossa-BashaDepartment of Radiology, University of Washington School of Medicine, Seattle, WA, USA.
Chengcheng ZhuDepartment of Radiology, University of Washington School of Medicine, Seattle, WA, USA. zhucheng@uw.edu.ORCID http://orcid.org/0000-0001-6898-549X

Funding

Investigation of the quantitative intracranial aneurysm wall enhancement and geometric features associated with aneurysm volume growthR01HL162743 · NHLBI · UNIVERSITY OF WASHINGTON · PI Chengcheng Zhu · 2022 to 2026
$2.4M
Characterization of intracranial vessel wall morphology and inflammation using 3D high resolution MRIR00HL136883 · NHLBI · UNIVERSITY OF WASHINGTON · PI ZHU, CHENGCHENG · 2020 to 2022
$747k
NHLBI NIH HHS R00 HL136883NHLBI NIH HHS R01 HL162743United States National Institute of Health R01HL162743
6 · The paper itself

Abstract

objectivesIntracranial atherosclerotic disease (ICAD) features on vessel wall magnetic resonance imaging (VW-MRI) are associated with first-ever or recurrent ischemic stroke (IS) or transient ischemic attack (TIA). There are multiple longitudinal ICAD VW-MRI studies, but they are limited by small sample size, non-standardized imaging acquisition and analysis, and some controversial results. Hence, we conducted the current meta-analysis of intracranial plaque features predicting recurrence of IS. MATERIALS AND

methodsPubMed, Web of Science, and EMBASE databases were searched through March 2024. Two independent reviewers extracted data on study design, VW-MRI techniques, and patient outcome. Quality assessment was used by the NOS tool. Subgroup analyses, sensitivity analysis, and evaluation of publication bias were also performed.

resultsFor recurrent IS, eighteen studies were included for meta-analysis, comprising 2240 participants, and 472 participants had recurrent IS during an average of 16-month follow-up. All studies were of high quality with an NOS score ≥ 7. Plaque enhancement (OR 2.18, [95% CI 1.70-4.65]), plaque enhancement ratio (SMD 0.46, [95% CI 0.15-0.77]), plaque thickness, (SMD 0.271, [95% CI 0.047-0.496]), T1-weighted (T1W) hyperintensity, (OR 2.58, [95% CI 1.56-4.26]), and degree of stenosis (SMD 0.41, [95% CI 0.03-0.79]) significantly predicted IS recurrence. Subgroup analyses found plaque enhancement was significantly higher in the IS and TIA recurrence group as compared to the non-recurrence group (OR 3.39, 95% CI 1.84-6.22).

conclusionPlaque enhancement, plaque enhancement ratio, plaque thickness, T1W hyperintensity and degree of stenosis emerged as strong imaging biomarkers of recurrence of stroke. CLINICAL

trial registrationClinical trial registration no: CRD42023479678. KEY POINTS: Questions Several studies suggest that vessel wall MRI (VWMRI) features of intracranial atherosclerotic disease (ICAD) may be associated with first-time or recurrent ischemic strokes, though this remains a debated topic. Findings Our study demonstrates that plaque enhancement, plaque enhancement ratio, plaque thickness, T1W hyperintensity, and degree of stenosis are strong imaging biomarkers for predicting stroke recurrence. Clinical relevance Incorporating these features into post-stroke evaluations using VWMRI could help guide patient management more effectively, enabling more targeted treatments for secondary stroke prevention.

Indexed as

Intracranial ArteriosclerosisMagnetic Resonance ImagingPlaque, AtheroscleroticStrokeHumansIschemic Attack, TransientRecurrenceAtherosclerosisBiomarkerMagnetic resonance imagingRecurrenceStroke

Identifiers

PMID39976739
PMCPMC12226209

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.