An anatomical model of the cerebral vasculature and blood flow
<p>The brain accounts for around 2 % of human adult bodyweight but consumes 20 % of the resting oxygen available to the whole body. The brain is dependent on a constant supply of oxygen to tissue, transported from the heart via the vasculature and carried in blood. An interruption to flow can...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
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2013
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| _version_ | 1797109819019100160 |
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| author | Lucas, C |
| author2 | Payne, S |
| author_facet | Payne, S Lucas, C |
| author_sort | Lucas, C |
| collection | OXFORD |
| description | <p>The brain accounts for around 2 % of human adult bodyweight but consumes 20 % of the resting oxygen available to the whole body. The brain is dependent on a constant supply of oxygen to tissue, transported from the heart via the vasculature and carried in blood. An interruption to flow can lead to ischaemia (a reduced oxygen supply) and prolonged interruption may result in tissue death, and permanent brain damage.</p> <p>The cerebral vasculature consists of many, densely packed, micro-vessels with a very large total surface area. Oxygen dissolved in blood enters tissue by passive diffusion through the micro-vessel walls. Imaging shows bursts of metabolic activity and flow in localised brain areas coordinated with brain activity (such as raising a hand). An appropriate level of oxygenation, according to physiological demand, is maintained via autoregulation; a set of response pathways in the brain which cause upstream or downstream vessels to expand or contract in diameter as necessary to provide sufficient oxygen to every region of the brain. Further, autoregulation is also evident in the response to pressure changes in the vasculature: the perfusing pressure can vary over a wide range from the basal-state with only a small effect on flow due to the constriction or dilation of vessels.</p> <p>Presented here is a new vasculature model where diameter and length are calculated in order to match the data available for flow velocity and blood pressure in different sized vessels. These vessels are arranged in a network of 6 generations each of bifurcating arterioles and venules, and a set of capillary beds. The input pressure and number of generations are the only specifications required to describe the network. The number of vessels, and therefore vessel geometry, is governed by how many generations are chosen and this can be altered in order to create more simple or complex networks. The flow, geometry and oxygen concentrations are calculated based on the vessel resistance due to flow from geometry based on Kirchoff circuit laws.</p> <p>The passive and active length-tension characteristics of the vasculature are established using an approximation of the network at upper and lower autoregulation limits. An activation model is described with an activation factor which governs the contributions of elastic andmuscle tension to the total vessel tension. This tension balances with the circumferential tension due to pressure and diameter and the change in activation sets the vessel diameter.</p> <p>The mass transport equation for oxygen is used to calculate the concentration of oxygen at every point in the network using data for oxygen saturation to establish a relationship between the permeability of the vessel wall to oxygen and the geometry and flow in individual vessels. A tissue compartment is introduced which enables the modelling of metabolic control. There is evidence for a coordinated response by surrounding vessels to local changes. A signal is proposed based on oxygen demand which can be conducted upstream. This signal decays exponentially with vessel length but also accumulates with the signal added from other vessels.</p> <p>The activation factor is therefore set by weighted signals proportional to changes in tissue concentration, circumferential tension, shear stress and conducted oxygen demand. The model is able to reproduce the autoregulation curve whereby a change in pressure has only a small effect on flow. The model is also able to replicate experimental results of diameter and tissue concentration following an increase in oxygen demand.</p> |
| first_indexed | 2024-03-07T07:46:37Z |
| format | Thesis |
| id | oxford-uuid:37d408b6-b804-4085-b420-a9704aeb97eb |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:46:37Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | oxford-uuid:37d408b6-b804-4085-b420-a9704aeb97eb2023-06-20T12:17:16ZAn anatomical model of the cerebral vasculature and blood flowThesishttp://purl.org/coar/resource_type/c_db06uuid:37d408b6-b804-4085-b420-a9704aeb97ebBiomedical engineeringEngineering & allied sciencesMathematical modeling (engineering)EnglishOxford University Research Archive - Valet2013Lucas, CPayne, S<p>The brain accounts for around 2 % of human adult bodyweight but consumes 20 % of the resting oxygen available to the whole body. The brain is dependent on a constant supply of oxygen to tissue, transported from the heart via the vasculature and carried in blood. An interruption to flow can lead to ischaemia (a reduced oxygen supply) and prolonged interruption may result in tissue death, and permanent brain damage.</p> <p>The cerebral vasculature consists of many, densely packed, micro-vessels with a very large total surface area. Oxygen dissolved in blood enters tissue by passive diffusion through the micro-vessel walls. Imaging shows bursts of metabolic activity and flow in localised brain areas coordinated with brain activity (such as raising a hand). An appropriate level of oxygenation, according to physiological demand, is maintained via autoregulation; a set of response pathways in the brain which cause upstream or downstream vessels to expand or contract in diameter as necessary to provide sufficient oxygen to every region of the brain. Further, autoregulation is also evident in the response to pressure changes in the vasculature: the perfusing pressure can vary over a wide range from the basal-state with only a small effect on flow due to the constriction or dilation of vessels.</p> <p>Presented here is a new vasculature model where diameter and length are calculated in order to match the data available for flow velocity and blood pressure in different sized vessels. These vessels are arranged in a network of 6 generations each of bifurcating arterioles and venules, and a set of capillary beds. The input pressure and number of generations are the only specifications required to describe the network. The number of vessels, and therefore vessel geometry, is governed by how many generations are chosen and this can be altered in order to create more simple or complex networks. The flow, geometry and oxygen concentrations are calculated based on the vessel resistance due to flow from geometry based on Kirchoff circuit laws.</p> <p>The passive and active length-tension characteristics of the vasculature are established using an approximation of the network at upper and lower autoregulation limits. An activation model is described with an activation factor which governs the contributions of elastic andmuscle tension to the total vessel tension. This tension balances with the circumferential tension due to pressure and diameter and the change in activation sets the vessel diameter.</p> <p>The mass transport equation for oxygen is used to calculate the concentration of oxygen at every point in the network using data for oxygen saturation to establish a relationship between the permeability of the vessel wall to oxygen and the geometry and flow in individual vessels. A tissue compartment is introduced which enables the modelling of metabolic control. There is evidence for a coordinated response by surrounding vessels to local changes. A signal is proposed based on oxygen demand which can be conducted upstream. This signal decays exponentially with vessel length but also accumulates with the signal added from other vessels.</p> <p>The activation factor is therefore set by weighted signals proportional to changes in tissue concentration, circumferential tension, shear stress and conducted oxygen demand. The model is able to reproduce the autoregulation curve whereby a change in pressure has only a small effect on flow. The model is also able to replicate experimental results of diameter and tissue concentration following an increase in oxygen demand.</p> |
| spellingShingle | Biomedical engineering Engineering & allied sciences Mathematical modeling (engineering) Lucas, C An anatomical model of the cerebral vasculature and blood flow |
| title | An anatomical model of the cerebral vasculature and blood flow |
| title_full | An anatomical model of the cerebral vasculature and blood flow |
| title_fullStr | An anatomical model of the cerebral vasculature and blood flow |
| title_full_unstemmed | An anatomical model of the cerebral vasculature and blood flow |
| title_short | An anatomical model of the cerebral vasculature and blood flow |
| title_sort | anatomical model of the cerebral vasculature and blood flow |
| topic | Biomedical engineering Engineering & allied sciences Mathematical modeling (engineering) |
| work_keys_str_mv | AT lucasc ananatomicalmodelofthecerebralvasculatureandbloodflow AT lucasc anatomicalmodelofthecerebralvasculatureandbloodflow |