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Record W4410790584 · doi:10.1016/j.ejrad.2025.112200

Decreased wall shear stress on 4D-flow-MRI is associated with wall instability of unruptured intracranial aneurysm

2025· article· en· W4410790584 on OpenAlexaff
Qichang Fu, Xinmei Ma, Linghao Li, Wanjun Xia, Shanshan Xie, Jumatay Biekan, Mengzhu Wang, Jianfeng Bao, Junying Cheng, Yong Zhang, Sheng Guan, Jingliang Cheng

Bibliographic record

VenueEuropean Journal of Radiology · 2025
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsCircle Cardiovascular Imaging
FundersNational Natural Science Foundation of China
KeywordsMedicineAneurysmShear stressInstabilityRadiologyMechanics

Abstract

fetched live from OpenAlex

Background and purpose The wall instability of unruptured intracranial aneurysms (UIAs) is associated with aneurysm growth or rupture. The wall shear stress (WSS) of 4D-flow-MRI can indicate hemodynamic abnormalities on the aneurysm wall. Aneurysm wall enhancement (AWE) of vessel wall MRI (VWI) and volume transfer constant (K trans ) of dynamic contrast-enhanced MRI (DCE-MRI) can indicate inflammation and permeability changes of the unstable aneurysm wall. We hypothesize that the WSS of UIAs is not only associated with AWE and K trans but also with the risk of growth or rupture derived from the ELAPSS or PHASES scores of the aneurysm. Materials and methods A cross-sectional retrospective analysis was performed on patients with UIAs who underwent 3.0 T VWI, DCE-MRI, and 4D-flow-MRI in our hospital from January 2018 to October 2023. AWE, K trans , and WSS were obtained by VWI, DCE-MRI, and 4D-flow MRI, respectively. AWE pattern (AWEP) and wall enhancement index (WEI) were used to evaluate AWE. 3- and 5-year aneurysm growth risk and 5-year rupture risk were predicted based on ELAPSS and PHASES scores, respectively. Correlations between parameters were assessed using Spearman's correlation coefficient or logistic regression. Results Ninety-six aneurysms in 78 patients (53 women) were included in the study. WSS differed across AWEP subgroups ( p < 0.001). WSS was negatively correlated with AWEP, WEI, and K trans ( rs = -0.35, rs = -0.44, and rs = -0.25; p < 0.001). Multiple logistic regression indicated that decreased WSS was associated with higher odds of AWE (OR: 0.65, 95 % CI: 0.48–0.87). WSS was negatively correlated with the 3- and 5-year growth risk and the 5-year risk of rupture ( rs = −0.47, rs = -0.44, and rs = −0.50; p < 0.001). Conclusion WSS on 4D-flow-MRI of aneurysms is inversely associated with AWEP, WEI, and K trans and growth and rupture risk. The decrease in WSS on 4D-flow-MRI may provide valuable information for assessing aneurysm wall instability.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.279
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.245
Teacher spread0.232 · 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 teacher head, 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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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