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Related Concept Videos

Aneurysm I: Introduction01:30

Aneurysm I: Introduction

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An aortic aneurysm is a localized outpouching or dilation at a weak point in the artery wall. It may involve different parts of the aorta, such as the abdominal aorta, aortic arch, or thoracic aorta.Etiological factorsSeveral disorders are associated with aortic aneurysms.Congenital causes, such as primary connective tissue disorders like Marfan syndrome, impact the integrity and strength of connective tissues, notably affecting the aorta. Marfan syndrome is a genetic disorder that specifically...
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Aneurysm II: Clinical Manifestations and Diagnostic Studies01:21

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Thoracic, aortic arch and abdominal aneurysms are significant vascular conditions that can present with various clinical manifestations and lead to serious complications. Understanding these manifestations and the appropriate diagnostic studies is essential for effective management and treatment.Thoracic Aortic AneurysmsThoracic aortic aneurysms often remain asymptomatic until they reach a size that impinges on adjacent structures. They typically cause deep, diffuse chest pain that radiates to...
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Aneurysm management involves either conservative medical therapy or surgical intervention, depending on the size and symptoms of the aneurysm. Conservative management is generally reserved for smaller, asymptomatic aneurysms, while larger or symptomatic aneurysms often necessitate surgical repair.Conservative Medical TherapyFor small, asymptomatic aneurysms, particularly abdominal aortic aneurysms (AAA) less than 5.5 centimeters in diameter, conservative medical therapy is recommended. This...
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Related Experiment Video

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Computational fluid dynamics and shape analysis enhance aneurysm rupture risk stratification.

Ivan Benemerito1,2, Frederick Ewbank3, Andrew Narracott4,5

  • 1INSIGNEO Institute for in Silico Medicine, University of Sheffield, Sheffield, UK. i.benemerito@sheffield.ac.uk.

International Journal of Computer Assisted Radiology and Surgery
|November 17, 2024
PubMed
Summary

Integrating computational fluid dynamics and shape analysis with the PHASES score significantly improves the prediction of unruptured intracranial aneurysm (UIA) rupture risk. This enhances classification accuracy for guiding treatment decisions.

Keywords:
AneurysmFluid dynamicsLogistic regressionPHASESRisk factorsShape

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Area of Science:

  • Neurosurgery
  • Medical Imaging
  • Biomedical Engineering

Background:

  • Accurate quantification of unruptured intracranial aneurysm (UIA) rupture risk is critical for treatment decisions.
  • While Computational Fluid Dynamics (CFD) and morphological measurements differ between ruptured and unruptured aneurysms, their added value over clinical data is unclear.
  • This study aims to determine if image-derived features enhance the established PHASES score for classifying aneurysm rupture status.

Purpose of the Study:

  • To investigate the efficacy of incorporating image-derived features from CFD and shape analysis into the PHASES score.
  • To improve the classification accuracy of aneurysm rupture status.
  • To assess the added value of advanced imaging techniques over routine clinical observations.

Main Methods:

  • A cross-sectional dataset of 170 patients (78 ruptured) was analyzed.
  • CFD and shape analysis extracted additional features, which were combined with PHASES variables.
  • Five logistic regression models were developed and validated using cross-validation, with performance measured by AUC.

Main Results:

  • The PHASES score alone yielded an AUC of 0.63.
  • Models incorporating CFD and shape analysis features achieved an improved AUC of 0.71.
  • Non-sphericity index and maximum oscillatory shear index were identified as key predictors of rupture.

Conclusions:

  • Integrating image-based CFD and shape analysis with clinical data significantly improves aneurysm rupture classification accuracy.
  • These findings highlight the potential of advanced imaging techniques to refine risk assessment for UIAs.
  • Further research with longitudinal data is recommended for clinical integration assessment.