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Theoretical Compartment Modeling of DCE-MRI Data Based on the Transport across Physiological Barriers in the Brain
Neurological disorders represent major causes of lost years of healthy life and mortality worldwide. Development of their quantitative interdisciplinary in vivo evaluation is required. Compartment modeling (CM) of brain data acquired in vivo using magnetic resonance imaging techniques with clinicall...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3359798/ https://www.ncbi.nlm.nih.gov/pubmed/22666304 http://dx.doi.org/10.1155/2012/482565 |
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author | Fanea, Laura David, Leontin I. Lebovici, Andrei Carbone, Francesca Sfrangeu, Silviu A. |
author_facet | Fanea, Laura David, Leontin I. Lebovici, Andrei Carbone, Francesca Sfrangeu, Silviu A. |
author_sort | Fanea, Laura |
collection | PubMed |
description | Neurological disorders represent major causes of lost years of healthy life and mortality worldwide. Development of their quantitative interdisciplinary in vivo evaluation is required. Compartment modeling (CM) of brain data acquired in vivo using magnetic resonance imaging techniques with clinically available contrast agents can be performed to quantitatively assess brain perfusion. Transport of (1)H spins in water molecules across physiological compartmental brain barriers in three different pools was mathematically modeled and theoretically evaluated in this paper and the corresponding theoretical compartment modeling of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data was analyzed. The pools considered were blood, tissue, and cerebrospinal fluid (CSF). The blood and CSF data were mathematically modeled assuming continuous flow of the (1)H spins in these pools. Tissue data was modeled using three CMs. Results in this paper show that transport across physiological brain barriers such as the blood to brain barrier, the extracellular space to the intracellular space barrier, or the blood to CSF barrier can be evaluated quantitatively. Statistical evaluations of this quantitative information may be performed to assess tissue perfusion, barriers' integrity, and CSF flow in vivo in the normal or disease-affected brain or to assess response to therapy. |
format | Online Article Text |
id | pubmed-3359798 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-33597982012-06-04 Theoretical Compartment Modeling of DCE-MRI Data Based on the Transport across Physiological Barriers in the Brain Fanea, Laura David, Leontin I. Lebovici, Andrei Carbone, Francesca Sfrangeu, Silviu A. Comput Math Methods Med Research Article Neurological disorders represent major causes of lost years of healthy life and mortality worldwide. Development of their quantitative interdisciplinary in vivo evaluation is required. Compartment modeling (CM) of brain data acquired in vivo using magnetic resonance imaging techniques with clinically available contrast agents can be performed to quantitatively assess brain perfusion. Transport of (1)H spins in water molecules across physiological compartmental brain barriers in three different pools was mathematically modeled and theoretically evaluated in this paper and the corresponding theoretical compartment modeling of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) data was analyzed. The pools considered were blood, tissue, and cerebrospinal fluid (CSF). The blood and CSF data were mathematically modeled assuming continuous flow of the (1)H spins in these pools. Tissue data was modeled using three CMs. Results in this paper show that transport across physiological brain barriers such as the blood to brain barrier, the extracellular space to the intracellular space barrier, or the blood to CSF barrier can be evaluated quantitatively. Statistical evaluations of this quantitative information may be performed to assess tissue perfusion, barriers' integrity, and CSF flow in vivo in the normal or disease-affected brain or to assess response to therapy. Hindawi Publishing Corporation 2012 2012-05-14 /pmc/articles/PMC3359798/ /pubmed/22666304 http://dx.doi.org/10.1155/2012/482565 Text en Copyright © 2012 Laura Fanea et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Fanea, Laura David, Leontin I. Lebovici, Andrei Carbone, Francesca Sfrangeu, Silviu A. Theoretical Compartment Modeling of DCE-MRI Data Based on the Transport across Physiological Barriers in the Brain |
title | Theoretical Compartment Modeling of DCE-MRI Data Based on the Transport across Physiological Barriers in the Brain |
title_full | Theoretical Compartment Modeling of DCE-MRI Data Based on the Transport across Physiological Barriers in the Brain |
title_fullStr | Theoretical Compartment Modeling of DCE-MRI Data Based on the Transport across Physiological Barriers in the Brain |
title_full_unstemmed | Theoretical Compartment Modeling of DCE-MRI Data Based on the Transport across Physiological Barriers in the Brain |
title_short | Theoretical Compartment Modeling of DCE-MRI Data Based on the Transport across Physiological Barriers in the Brain |
title_sort | theoretical compartment modeling of dce-mri data based on the transport across physiological barriers in the brain |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3359798/ https://www.ncbi.nlm.nih.gov/pubmed/22666304 http://dx.doi.org/10.1155/2012/482565 |
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