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Starling forces drive intracranial water exchange during normal and pathological states
AIM: To quantify the exchange of water between cerebral compartments, specifically blood, tissue, perivascular pathways, and cerebrospinal fluid-filled spaces, on the basis of experimental data and to propose a dynamic global model of water flux through the entire brain to elucidate functionally rel...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Croatian Medical Schools
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5778682/ https://www.ncbi.nlm.nih.gov/pubmed/29308830 http://dx.doi.org/10.3325/cmj.2017.58.384 |
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author | Linninger, Andreas A. Xu, Colin Tangen, Kevin Hartung, Grant |
author_facet | Linninger, Andreas A. Xu, Colin Tangen, Kevin Hartung, Grant |
author_sort | Linninger, Andreas A. |
collection | PubMed |
description | AIM: To quantify the exchange of water between cerebral compartments, specifically blood, tissue, perivascular pathways, and cerebrospinal fluid-filled spaces, on the basis of experimental data and to propose a dynamic global model of water flux through the entire brain to elucidate functionally relevant fluid exchange phenomena. METHODS: The mechanistic computer model to predict brain water shifts is discretized by cerebral compartments into nodes. Water and species flux is calculated between these nodes across a network of arcs driven by Hagen-Poiseuille flow (blood), Darcy flow (interstitial fluid transport), and Starling’s Law (transmembrane fluid exchange). Compartment compliance is accounted for using a pressure-volume relationship to enforce the Monro-Kellie doctrine. This nonlinear system of differential equations is solved implicitly using MATLAB software. RESULTS: The model predictions of intraventricular osmotic injection caused a pressure rise from 10 to 22 mmHg, followed by a taper to 14 mmHg over 100 minutes. The computational results are compared to experimental data with R(2) = 0.929. Moreover, simulated osmotic therapy of systemic (blood) injection reduced intracranial pressure from 25 to 10 mmHg. The modeled volume and intracranial pressure changes following cerebral edema agree with experimental trends observed in animal models with R(2) = 0.997. CONCLUSION: The model successfully predicted time course and the efficacy of osmotic therapy for clearing cerebral edema. Furthermore, the mathematical model implicated the perivascular pathways as a possible conduit for water and solute exchange. This was a first step to quantify fluid exchange throughout the brain. |
format | Online Article Text |
id | pubmed-5778682 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Croatian Medical Schools |
record_format | MEDLINE/PubMed |
spelling | pubmed-57786822018-01-26 Starling forces drive intracranial water exchange during normal and pathological states Linninger, Andreas A. Xu, Colin Tangen, Kevin Hartung, Grant Croat Med J Basic Science AIM: To quantify the exchange of water between cerebral compartments, specifically blood, tissue, perivascular pathways, and cerebrospinal fluid-filled spaces, on the basis of experimental data and to propose a dynamic global model of water flux through the entire brain to elucidate functionally relevant fluid exchange phenomena. METHODS: The mechanistic computer model to predict brain water shifts is discretized by cerebral compartments into nodes. Water and species flux is calculated between these nodes across a network of arcs driven by Hagen-Poiseuille flow (blood), Darcy flow (interstitial fluid transport), and Starling’s Law (transmembrane fluid exchange). Compartment compliance is accounted for using a pressure-volume relationship to enforce the Monro-Kellie doctrine. This nonlinear system of differential equations is solved implicitly using MATLAB software. RESULTS: The model predictions of intraventricular osmotic injection caused a pressure rise from 10 to 22 mmHg, followed by a taper to 14 mmHg over 100 minutes. The computational results are compared to experimental data with R(2) = 0.929. Moreover, simulated osmotic therapy of systemic (blood) injection reduced intracranial pressure from 25 to 10 mmHg. The modeled volume and intracranial pressure changes following cerebral edema agree with experimental trends observed in animal models with R(2) = 0.997. CONCLUSION: The model successfully predicted time course and the efficacy of osmotic therapy for clearing cerebral edema. Furthermore, the mathematical model implicated the perivascular pathways as a possible conduit for water and solute exchange. This was a first step to quantify fluid exchange throughout the brain. Croatian Medical Schools 2017-12 /pmc/articles/PMC5778682/ /pubmed/29308830 http://dx.doi.org/10.3325/cmj.2017.58.384 Text en Copyright © 2017 by the Croatian Medical Journal. All rights reserved. http://creativecommons.org/licenses/by/2.5/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Basic Science Linninger, Andreas A. Xu, Colin Tangen, Kevin Hartung, Grant Starling forces drive intracranial water exchange during normal and pathological states |
title | Starling forces drive intracranial water exchange during normal and pathological states |
title_full | Starling forces drive intracranial water exchange during normal and pathological states |
title_fullStr | Starling forces drive intracranial water exchange during normal and pathological states |
title_full_unstemmed | Starling forces drive intracranial water exchange during normal and pathological states |
title_short | Starling forces drive intracranial water exchange during normal and pathological states |
title_sort | starling forces drive intracranial water exchange during normal and pathological states |
topic | Basic Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5778682/ https://www.ncbi.nlm.nih.gov/pubmed/29308830 http://dx.doi.org/10.3325/cmj.2017.58.384 |
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