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Record W4410453243 · doi:10.1002/jmri.29813

Stroke Mechanism Subtypes and Prognosis in Patients With Symptomatic Intracranial Atherosclerosis Based on Multiparametric <scp>MRI</scp>

2025· article· en· W4410453243 on OpenAlexaboutno aff
Wenqiao Zheng, Hua Wei, Fan Bai, Yuan Qu, Zhichang Fan, Yan Li, Bin Wang, Yongfang Wang, Le Wang, Xiaochun Wang

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2025
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMedicineStroke (engine)StenosisPerfusion scanningRadiologyMagnetic resonance imagingInternal medicinePerfusionCardiology

Abstract

fetched live from OpenAlex

BACKGROUND: Different stroke mechanisms present with distinct imaging characteristics and prognosis. Multiparametric MRI can characterize these variations and may contribute to stroke secondary prevention. PURPOSE: To investigate the stroke mechanism subtypes and prognosis in patients with symptomatic intracranial atherosclerosis using multiparametric MRI. STUDY TYPE: Retrospective. POPULATION: Two hundred and seventeen ischemic stroke patients (147 males; age 55.5 ± 11.7 years) with intracranial atherosclerosis. FIELD STRENGTH/SEQUENCE: 3-T, dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI); High-resolution vessel wall imaging (HR-VWI): three-dimensional (3D) T1-weighted Sampling Perfection with Application optimized Contrast using different flip angle Evolution (SPACE) and contrast-enhanced T1-SPACE. ASSESSMENT: All patients underwent multiparametric MRI within 7 days of stroke symptom onset. The stroke mechanisms included branch occlusive disease (BOD), artery-to-artery embolism, hypoperfusion, and mixed mechanisms. The following imaging characteristics were assessed by three radiologists independently. HR-VWI plaque characteristics included plaque area, lipid area, lipid ratio, occlusive thrombus, degree of stenosis, plaque burden, enhancement ratio, remodeling index, and intraplaque hemorrhage (IPH). The mean transit time-Alberta Stroke Program Early Computed Tomography score (MTT-ASPECTS) based on DSC-PWI was used to evaluate perfusion impairment. During a median follow-up period of 15 months, the correlation between different stroke mechanisms and prognosis was analyzed. STATISTICAL TESTS: Chi-squared or Fisher's exact, Kruskal-Wallis H-tests, multivariate logistic regression, and Kaplan-Meier curves. All p-values were corrected by Bonferroni correction, and p-values < 0.05 were considered statistically significant. RESULTS: Mixed mechanism was the most common subtype (32.7%). Significant differences were observed in perfusion impairment, degree of stenosis, plaque burden, enhancement ratio, IPH, and remodeling among stroke mechanisms. Of these characteristics, MTT-ASPECTS (odds ratio [OR] 0.70, 95% CI 0.562-0.863) and IPH (OR 2.30, 95% CI 1.042-5.051) were significantly associated with non-BOD mechanisms. Hypoperfusion mechanism was associated with a higher risk of stroke recurrence during a median follow-up of 15 months (hazard ratio 3.97, 95% CI 1.43-11.03). DATA CONCLUSION: Multiparametric MRI may reveal differences in imaging characteristics among stroke mechanisms. Hypoperfusion may be associated with an increased risk of stroke recurrence. EVIDENCE LEVEL: 3. Technical Efficacy: Stage 3.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.204
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2025
Admission routes1
Has abstractyes

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