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Cerebral pulsatility is a potential marker of cerebrovascular health, yet little is understood about sex differences in cerebral pulsatility with age, especially within different cerebral arteries. Additionally, cerebral damping can blunt cerebral pulsatility and might decline with age. Therefore, we aimed to identify sex differences in cerebral pulsatility and damping across the adult lifespan. Forty-three young, 67 middle-aged and 54 older adults had cerebral haemodynamics measured in the internal carotid arteries (ICAs), middle cerebral arteries (MCAs) and basilar artery using 4D flow MRI. Cerebral pulsatility index (PI) and damping factor (DF) were calculated. Young females had lower PI than young males in the ICAs (p < 0.05 for both), and middle-aged females had lower PI than middle-aged males in the right ICA (p < 0.01). In contrast, older females had greater PI than older males in the right ICA (p < 0.01) and in the right MCA (p < 0.05). Only the DF between the right ICA and MCA was lower in young females than in young males (p < 0.001). Taken together, females experience greater age-related elevations in cerebral pulsatility in comparison to males, especially within the proximal arteries of the anterior circulation. Damping was not different between males and females within the proximal arteries of anterior circulation, suggesting a different underlying mechanism. Overall, our findings suggest sex-specific trends in cerebral pulsatility with age, although the mechanisms driving this require further exploration.
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http://dx.doi.org/10.1113/EP092630 | DOI Listing |
PLoS Comput Biol
September 2025
Department of Mathematical and Computational Methods, National Laboratory for Scientific Computing, Petrópolis, Brazil.
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View Article and Find Full Text PDFPLoS One
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Department of Otorhinolaryngology-Head and Neck Surgery, Ansan Hospital, Korea University College of Medicine, Ansan, Republic of Korea.
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View Article and Find Full Text PDFImaging Neurosci (Camb)
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Physics for Medicine Paris, Inserm, ESPCI Paris-PSL, CNRS, Paris, France.
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View Article and Find Full Text PDFCureus
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Service of Neurology, Hospital Universitário Clementino Fraga Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, BRA.
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View Article and Find Full Text PDFSci Rep
September 2025
Department of Mechanical Engineering, College of Engineering, University of Ha'il, Ha'il City, 81451, Saudi Arabia.
Accurate assessment of intracranial aneurysm rupture risk, particularly in Middle Cerebral Artery (MCA) aneurysms, relies on a detailed understanding of patient-specific hemodynamic behavior. In this study, we present an integrated framework that combines Computational Fluid Dynamics (CFD) with Proper Orthogonal Decomposition (POD) and machine learning (ML) to efficiently model pulsatile blood flow using a Casson non-Newtonian fluid model, without incorporating fluid-structure interaction (FSI). Patient-specific vascular geometries were reconstructed from DICOM imaging data and simulated using ANSYS Fluent to capture key hemodynamic factors, including velocity components, pressure, wall shear stress (WSS), and oscillatory shear index (OSI).
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