Cerebral hemodynamics during atrial fibrillation: computational fluid dynamics (CFD) analysis of lenticulostriate arteries using 7T high-resolution magnetic resonance imaging

Atrial fibrillation (AF) is the most common cardiac arrhythmia, inducing irregular and faster heart beating. Aside from disabling symptoms - such as palpitations, chest discomfort, and reduced exercise capacity - there is growing evidence that AF increases the risk of dementia and cognitive decline, even in the absence of clinical strokes. Among the possible mechanisms, the alteration of deep cerebral hemodynamics during AF is one of the most fascinating and least investigated hypotheses. Lenticulostriate arteries (LSAs) - small perforating arteries perpendicularly departing from the anterior and middle cerebral arteries and supplying blood flow to basal ganglia - are especially involved in silent strokes and cerebral small vessel diseases, which are considered among the main vascular drivers of dementia. We propose for the first time a computational fluid dynamics analysis to investigate the AF effects on the LSAs hemodynamics by using 7 T high-resolution magnetic resonance imaging (MRI). We explored different heart rates (HRs) - from 50 to 130 bpm - in sinus rhythm and AF, exploiting MRI data from a healthy young male and internal carotid artery data from validated 0D cardiovascular-cerebral modeling as inflow condition. Our results reveal that AF induces a marked reduction of wall shear stress and flow velocity fields. This study suggests that AF at higher HR leads to a more hazardous hemodynamic scenario by increasing the atheromatosis and thrombogenesis risks in the LSAs region

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23 февраля 2011 года исполнилось 75 лет со дня рождения главного инженера Днепродзержинской ГЭС — Кучерявого Владислава Семеновича.15 июня 2011 г. исполняется 70 лет ученому — гидроэнергетику, доктору технических наук, начальнику отдела расчетного обоснования ПАО "Укргидропроект", профессору, заведующему кафедрой гидротехнического строительства Харьковского государственного технического университета строительства и архитектуры Александру Исааковичу Вайнбергу

Zooming in on cerebral small vessel function in small vessel diseases with 7T MRI: Rationale and design of the “ZOOM@SVDs” study

Background: Cerebral small vessel diseases (SVDs) are a major cause of stroke and dementia. Yet, specific treatment strategies are lacking in part because of a limited understanding of the underlying disease processes. There is therefore an urgent need to study SVDs at their core, the small vessels themselves. Objective: This paper presents the rationale and design of the ZOOM@SVDs study, which aims to establish measures of cerebral small vessel dysfunction on 7T MRI as novel disease markers of SVDs. Methods: ZOOM@SVDs is a prospective observational cohort study with two years follow-up. ZOOM@SVDs recruits participants with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL, N = 20), sporadic SVDs (N = 60), and healthy controls (N = 40). Participants undergo 7T brain MRI to assess different aspects of small vessel function including small vessel reactivity, cerebral perforating artery flow, and pulsatility. Extensive work-up at baseline and follow-up further includes clinical and neuropsychological assessment as well as 3T brain MRI to assess conventional SVD imaging markers. Measures of small vessel dysfunction are compared between patients and controls, and related to the severity of clinical and conventional MRI manifestations of SVDs. Discussion: ZOOM@SVDs will deliver novel markers of cerebral small vessel function in patients with monogenic and sporadic forms of SVDs, and establish their relation with disease burden and progression. These small vessel markers can support etiological studies in SVDs and may serve as surrogate outcome measures in future clinical trials to show target engagement of drugs directed at the small vessels

Cardiac and respiration-induced brain deformations in humans quantified with high-field MRI

Microvascular blood volume pulsations due to the cardiac and respiratory cycles induce brain tissue deformation and, as such, are considered to drive the brain's waste clearance system. We have developed a high-field magnetic resonance imaging (MRI) technique to quantify both cardiac and respiration-induced tissue deformations, which could not be assessed noninvasively before. The technique acquires motion encoded snapshot images in which various forms of motion and confounders are entangled. First, we optimized the motion sensitivity for application in the human brain. Next, we isolated the heartbeat and respiration-related deformations, by introducing a linear model that fits the snapshot series to the recorded physiological information. As a result, we obtained maps of the physiological tissue deformation with 3 mm isotropic spatial resolution. Heartbeat- and respiration induced volumetric strain were significantly different from zero in the basal ganglia (median (25-75% interquartile range): 0.85·10-3 (0.39·10-3-1.05·10-3), p = 0.0008 and -0.28·10-3 (-0.41·10-3-0.06·10-3), p = 0.047, respectively). Smaller volumetric strains were observed in the white matter of the centrum semi ovale (0.28·10-3 (0-0.59·10-3) and -0.06·10-3 (-0.17·10-3-0.20·10-3)), which was only significant for the heart beat (p = 0.02 and p = 0.7, respectively). Furthermore, heartbeat induced volumetric strain was about three times larger than respiration induced volumetric strain. This technique opens a window on the driving forces of the human brain clearance system

Cardiac and respiration-induced brain deformations in humans quantified with high-field MRI

Microvascular blood volume pulsations due to the cardiac and respiratory cycles induce brain tissue deformation and, as such, are considered to drive the brain's waste clearance system. We have developed a high-field magnetic resonance imaging (MRI) technique to quantify both cardiac and respiration-induced tissue deformations, which could not be assessed noninvasively before. The technique acquires motion encoded snapshot images in which various forms of motion and confounders are entangled. First, we optimized the motion sensitivity for application in the human brain. Next, we isolated the heartbeat and respiration-related deformations, by introducing a linear model that fits the snapshot series to the recorded physiological information. As a result, we obtained maps of the physiological tissue deformation with 3 mm isotropic spatial resolution. Heartbeat- and respiration induced volumetric strain were significantly different from zero in the basal ganglia (median (25-75% interquartile range): 0.85·10-3 (0.39·10-3-1.05·10-3), p = 0.0008 and -0.28·10-3 (-0.41·10-3-0.06·10-3), p = 0.047, respectively). Smaller volumetric strains were observed in the white matter of the centrum semi ovale (0.28·10-3 (0-0.59·10-3) and -0.06·10-3 (-0.17·10-3-0.20·10-3)), which was only significant for the heart beat (p = 0.02 and p = 0.7, respectively). Furthermore, heartbeat induced volumetric strain was about three times larger than respiration induced volumetric strain. This technique opens a window on the driving forces of the human brain clearance system