Evidence map›Paper›PMID 40913730›Full record

ArticleActa neurochirurgica2025

Haemodynamic characteristics of thin-walled regions in intracranial aneurysms: intraoperative imaging and CFD analysis.

Haveena Anbananthan, Phani Kumari Paritala, Jessica Benitez Mendieta, Han Yu, Tiago Guerzet Sardenberg Lima, Zoe Dettrick, Ee Shern Liang, Alan Coulthard, Zhi-Yong Li, Craig Winter

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In one paragraph

Article in Acta neurochirurgica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

10 authors.

Haveena AnbananthanSchool of Mechanical, Medical and Process Engineering, Queensland University of Technology (QUT), Brisbane, QLD, 4000, Australia.ORCID http://orcid.org/0000-0003-4193-948X
Phani Kumari ParitalaSchool of Mechanical, Medical and Process Engineering, Queensland University of Technology (QUT), Brisbane, QLD, 4000, Australia.
Jessica Benitez MendietaSchool of Mechanical, Medical and Process Engineering, Queensland University of Technology (QUT), Brisbane, QLD, 4000, Australia.ORCID http://orcid.org/0000-0001-9778-6158
Han YuSchool of Mechanical, Medical and Process Engineering, Queensland University of Technology (QUT), Brisbane, QLD, 4000, Australia.ORCID http://orcid.org/0009-0002-9896-9639
Tiago Guerzet Sardenberg LimaSchool of Mechanical, Medical and Process Engineering, Queensland University of Technology (QUT), Brisbane, QLD, 4000, Australia.ORCID http://orcid.org/0000-0001-9342-8804
Zoe DettrickFaculty of Health, Queensland University of Technology (QUT), Kelvin Grove, QLD, 4059, Australia.ORCID http://orcid.org/0000-0003-1091-1820
Ee Shern LiangDepartment of Medical Imaging, Royal Brisbane and Womens Hospital (RBWH), Herston, QLD, 4006, Australia.
Alan CoulthardDepartment of Medical Imaging, Royal Brisbane and Womens Hospital (RBWH), Herston, QLD, 4006, Australia.ORCID http://orcid.org/0000-0003-1110-9207
Zhi-Yong LiSchool of Mechanical, Medical and Process Engineering, Queensland University of Technology (QUT), Brisbane, QLD, 4000, Australia. zhiyong.li@qut.edu.au.ORCID http://orcid.org/0000-0002-6814-9165
Craig WinterFaculty of Medicine, The University of Queensland, Herston, QLD, 4006, Australia.ORCID http://orcid.org/0000-0003-4626-7280

Funding

Australian Research Council DP200103492
6 · The paper itself

Abstract

backgroundIdentifying haemodynamic factors associated with thin-walled regions (TWRs) of intracranial aneurysms is critical for improving pre-surgical rupture risk assessment. Intraoperatively, these regions are visually distinguished by a red, translucent appearance and are considered highly rupture prone. However, current imaging modalities lack the resolution to detect such vulnerable areas preoperatively. This study aimed to determine whether thin-walled regions exhibit distinct local haemodynamic profiles compared to adjacent normal-appearing wall regions.

methodsSixteen patient-specific models of unruptured middle cerebral artery aneurysms were reconstructed from digital subtraction angiography images. Intraoperative TWRs were identified using a colour segmentation method based on Delta E metrics. Computational fluid dynamics (CFD) simulations were used to compute six haemodynamic parameters: wall shear stress (WSS), time-averaged WSS (TaWSS), oscillatory shear index (OSI), relative residence time (RRT), WSS divergence (WSSD), and pressure. Haemodynamic data were extracted from spatially localised surface patches within confirmed thin and normal regions. Linear mixed-effects models were applied to compare parameters while accounting for patient-level and intra-patient variability, using normalised values to improve model fit.

resultsThin regions exhibited significantly higher WSS, TaWSS, WSSD, and pressure, and reduced RRT. WSS and TaWSS were approximately 3.3% and 2.8% higher in TWRs, respectively. WSSD was 5.4% higher and RRT was 0.3% lower, suggesting faster, more divergent flow in thin regions. Pressure was modestly but significantly elevated at + 1.3%. No significant difference was observed in OSI between regions.

conclusionsThin-walled regions in intracranial aneurysms demonstrate a distinctive haemodynamic profile characterised by stronger, sustained shear forces, greater shear divergence, and reduced residence time, suggesting a dynamic mechanical environment that promotes focal wall thinning. Our findings suggest that persistent shear-driven stress, rather than oscillatory flow, is a key haemodynamic feature of thin-walled regions and may contribute to localised aneurysm wall vulnerability.

Indexed as

HemodynamicsIntracranial AneurysmAdultAgedAngiography, Digital SubtractionCerebral AngiographyComputer SimulationFemaleHumansHydrodynamicsMaleMiddle AgedComputational fluid dynamicsHaemodynamicsIntracranial aneurysmThin-walled region

Identifiers

PMID40913730
PMCPMC12414043

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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.