Thu
29
Jan
Seminars and Conferences
Computational models to study the perfusion of the brain under healthy conditions and in neurological disorders
The Department of Mathematical Sciences "Giuseppe Luigi Lagrange"-DISMA is organising the event Computational models to study the perfusion of the brain under healthy conditions and in neurological disorders, which will take place on 29 January 2026 at 2:30 pm.
A seminar with Franca Schmid, ARTORG Center for Biomedical Engineering Research, University of Bern, Switzerland.
Abstract
As the energy storage capacity of the brain is limited, a robust blood and oxygen supply is indispensable for its well-functioning. This aspect is further underlined because microvascular alterations play an important role during pathologies. However, experimentally quantifying the isolated impact of specific vascular alterations is challenging but well-suited for in silico modeling. In this context, three exemplary projects will be presented, including the underlying numerical models, which will show how in silico modeling goes beyond what is accessible to in vivo experiments. The basis for these projects is a 1D blood flow model applicable to realistic microvascular networks. The model’s unique feature is a discrete RBC tracking algorithm, that allows us to study the impact of the blood’s bi-phasic characteristics in a computationally efficient manner. Within the first project, this model is employed to quantify the impact of vascular alterations as observed during aging. In the second project, our blood flow model is combined with an inverse model to predict diameter changes necessary to locally up-regulate flow. The inverse model employs a hierarchical regularization strategy to identify the most suitable from an otherwise ambiguous solution. By constraining the vessel type that can change its diameter we generate insights on the role of capillary dilations in regulating flow in the brain. A slightly altered version of this inverse model has been used to align our in silico simulations to in vivo blood velocity measurements. Additionally, the 1D blood flow model has been extended to describe vessel diameter changes in response to changes in inflow pressure. This process is called cerebral autoregulation and aims at maintaining cerebral blood flow constant despite variations in inflow pressure. This framework is employed in the context of ischemic stroke to quantify the role of vascular anastomoses, i.e., vascular loops, and to study the loss of autoregulatory capacity.
A seminar with Franca Schmid, ARTORG Center for Biomedical Engineering Research, University of Bern, Switzerland.
Abstract
As the energy storage capacity of the brain is limited, a robust blood and oxygen supply is indispensable for its well-functioning. This aspect is further underlined because microvascular alterations play an important role during pathologies. However, experimentally quantifying the isolated impact of specific vascular alterations is challenging but well-suited for in silico modeling. In this context, three exemplary projects will be presented, including the underlying numerical models, which will show how in silico modeling goes beyond what is accessible to in vivo experiments. The basis for these projects is a 1D blood flow model applicable to realistic microvascular networks. The model’s unique feature is a discrete RBC tracking algorithm, that allows us to study the impact of the blood’s bi-phasic characteristics in a computationally efficient manner. Within the first project, this model is employed to quantify the impact of vascular alterations as observed during aging. In the second project, our blood flow model is combined with an inverse model to predict diameter changes necessary to locally up-regulate flow. The inverse model employs a hierarchical regularization strategy to identify the most suitable from an otherwise ambiguous solution. By constraining the vessel type that can change its diameter we generate insights on the role of capillary dilations in regulating flow in the brain. A slightly altered version of this inverse model has been used to align our in silico simulations to in vivo blood velocity measurements. Additionally, the 1D blood flow model has been extended to describe vessel diameter changes in response to changes in inflow pressure. This process is called cerebral autoregulation and aims at maintaining cerebral blood flow constant despite variations in inflow pressure. This framework is employed in the context of ischemic stroke to quantify the role of vascular anastomoses, i.e., vascular loops, and to study the loss of autoregulatory capacity.