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Continuous Manual Exchange Transfusion for Patients with Sickle Cell Disease: An Efficient Method to Avoid Iron Overload
Published on: March 14, 2017
Vascular Geometry Drives Stroke Risk in Sickle Cell Disease
Weiqiang Liu1, Christian Kassasseya2,3, Lazaros Papamanolis1,4
1Inria, Research Center Saclay Île-De-France, Palaiseau, France.
None:
Sickle cell disease (SCD) is the leading cause of stroke in children and young adults, primarily due to cerebral vasculopathy (CV) occurring within the first decade of life. The main risk factor for CV is elevated blood velocity in intracranial arteries, contributing to stenosis formation in very young children. This study addresses three key questions: (i) the relationship between hemoglobin levels and intracranial blood velocities in SCD patients, (ii) additional factors contributing to elevated velocity beyond anemia, and (iii) the presence of flow anomalies. To investigate these aspects, biological and transcranial Doppler data from pediatric and adult SCD patients were analyzed. An image-based in silico modeling approach was also developed to simulate blood flow in the internal carotid, anterior cerebral, and middle cerebral arteries of SCD patients, of different age classes, and prior to any possible stenosis. Analysis revealed that while anemia is a recognized CV risk factor, it does not fully explain elevated velocities, as no significant correlation was found in children under five. In in silico simulations, young patients reached pathological arterial intracranial velocities at physiological flow rates, whereas adults remained below risk thresholds even at high flow rates. Pathological velocities were primarily observed in distal internal carotid arteries, where stenoses often develop. High flow rates, small arterial diameters, and pronounced curvatures led to extreme velocities and complex flow, likely causing endothelial damage and promoting CV progression. These findings enhance understanding of hemodynamic mechanisms underlying SCD-related stroke risk, paving the way for improved predictive models and early interventions. Trial Registration: ClinicalTrials.gov identifier: NCT05199766.
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