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Computational fluid dynamics for severity assessment of arterial occlusive diseases
Weihao Li1, Yiheng Tan1, Hubert P J van der Doef2
1Department of Radiology, Medical Imaging Centre, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
Insights
Computational fluid dynamics (CFD) provides detailed hemodynamic insights into arterial occlusive diseases, correlating with diagnostic accuracy and patient outcomes. Further research is needed to standardize CFD methods and enhance clinical validation for broader application.
Area of Science:
- Biomedical Engineering
- Medical Imaging
- Cardiovascular Research
Background:
- Arterial occlusive diseases affect major blood vessels, impacting patient health and treatment strategies.
- Accurate hemodynamic assessment is crucial for understanding disease progression and guiding interventions.
- Computational Fluid Dynamics (CFD) offers a powerful tool for simulating blood flow dynamics.
Purpose of the Study:
- To review the methodological considerations of CFD in arterial occlusive diseases.
- To explore the clinical applications of CFD across carotid, peripheral, renal, and aortic segments.
- To identify current trends and future directions in CFD research for these conditions.
Main Methods:
- A systematic literature search was conducted across MEDLINE, CENTRAL, and Embase.
- Studies included those with >5 patients and clinical outcome data, excluding coronary and intracranial segments.
- Data extracted included CFD techniques, hemodynamic parameters, and clinical correlations.
Main Results:
- 34 studies were included, utilizing Doppler ultrasound and phase-contrast MRI for flow measurements.
- Commonly used inlet velocity profiles included parabolic and Womersley, with transient flow modeling prevalent.
- CFD parameters like wall shear stress (WSS) and oscillatory shear index (OSI) correlated with plaque vulnerability, restenosis, and diagnostic accuracy in various arterial segments.
Conclusions:
- CFD provides valuable hemodynamic data correlating with disease diagnosis, progression, and treatment outcomes.
- Standardization of CFD protocols, improved data acquisition, and clinical validation are essential for future advancements.
- CFD holds significant potential for improving the management of arterial occlusive diseases.
Objectives:
This scoping review aims to examine the methodological considerations and clinical applications of computational fluid dynamics (CFD) in arterial occlusive diseases spanning the carotid, peripheral, renal, and aortic segments.
Methods:
MEDLINE, CENTRAL, and Embase were searched for studies applying CFD to arterial occlusive diseases (except for coronary and intracranial segments). Studies with more than 5 patients and clinical outcome data were included. Data on CFD techniques, hemodynamic parameters, and clinical correlations were extracted.
Results:
From 1,925 identified studies, 34 were included. Blood flow measurements were obtained primarily using Doppler ultrasound (n = 17) and phase-contrast MRI (n = 10). Twenty-four studies specified inlet velocity profiles, with parabolic (n = 11), Womersley (n = 10), and plug (n = 3) patterns. Transient (pulsatile) flow (n = 18) was more frequently modeled than steady flow (n = 9). In carotid artery disease (n = 23), high wall shear stress (WSS) and oscillatory shear index (OSI) predicted plaque vulnerability and restenosis, with high WSS linked to ulceration and low WSS to plaque growth. In peripheral artery disease (n = 6), low time-averaged WSS (TAWSS) and high OSI predicted restenosis, particularly in curved segments. CFD-derived pressure gradients achieved up to 95% diagnostic accuracy for iliac stenosis. For renal artery stenosis (n = 3), high peak WSS and velocity indicated critical cases, and in aortic diseases (n = 2), elevated TAWSS and OSI highlighted post-repair risks.
Conclusions:
CFD offers detailed hemodynamic assessment that correlates with diagnostic accuracy, disease progression, treatment strategies and outcomes. Future research should prioritize standardization of CFD protocols, improved inlet data acquisition, reduced computational burden, and robust clinical validation.
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