Evidence map›Paper›PMID 41463676›Full record

ArticleBioengineering (Basel, Switzerland)2025

Using Patient-Based Computational Fluid Dynamics for Abdominal Aortic Aneurysm Assessment.

Natthaporn Kaewchoothong, Sorracha Rookkapan, Chayut Nuntadusit, Surapong Chatpun

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
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

4 authors.

Natthaporn KaewchoothongDepartment of Mechanical and Mechatronics Engineering, Faculty of Engineering, Prince of Songkla University, Hat Yai 90112, Songkhla, Thailand.ORCID 0000-0002-1646-1077
Sorracha RookkapanDepartment of Radiology, Faculty of Medicine, Prince of Songkla University, Hat Yai 90110, Songkhla, Thailand.
Chayut NuntadusitDepartment of Mechanical and Mechatronics Engineering, Faculty of Engineering, Prince of Songkla University, Hat Yai 90112, Songkhla, Thailand.
Surapong ChatpunDepartment of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Hat Yai 90110, Songkhla, Thailand.ORCID 0000-0002-6888-5170

Funding

Health Systems Research Institute HSRI 63-147
6 · The paper itself

Abstract

Abdominal aortic aneurysm (AAA) is a dangerous disease and can cause sudden death if it ruptures. This study investigated blood flow behaviors and hemodynamic changes in three categories (small, medium and large diameters) of AAAs using computational fluid dynamics (CFD) based on patient geometry. Computed tomography images of patients with abdominal aortic aneurysms were used to construct a patient-specific AAA model. This study included one healthy subject and seven patients who had AAAs with a diameter larger than 3 cm. The results showed that the aortic aneurysms were highly turbulent in the diastolic phase, and there was an increase in turbulence as the aneurysm size increased. The time-averaged wall shear stress (TAWSS) in the artery was high at peak systole and decreased during diastole. The oscillating shear index (OSI) was higher at the middle and distal aortic aneurysm sac than in other areas. Low TAWSS and a high OSI in the aneurysm region may indicate a risk of wall rupture in AAA. This study suggests that CFD provides further insights by visualizing blood flow behaviors and quantitatively analyzing hemodynamic parameters.

Indexed as

abdominal aortic aneurysmcomputational fluid dynamichemodynamic changespersonalized modelrupture risk

Identifiers

PMID41463676
PMCPMC12730124

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.