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A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease
BACKGROUND: Cerebrovascular disease, in particular stroke, is a major public health challenge. An important biomarker is cerebral hemodynamics. To measure and quantify cerebral hemodynamics, however, only invasive, potentially harmful or time-to-treatment prolonging methods are available. RESULTS: W...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8088619/ https://www.ncbi.nlm.nih.gov/pubmed/33933080 http://dx.doi.org/10.1186/s12938-021-00880-w |
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author | Frey, Dietmar Livne, Michelle Leppin, Heiko Akay, Ela M. Aydin, Orhun U. Behland, Jonas Sobesky, Jan Vajkoczy, Peter Madai, Vince I. |
author_facet | Frey, Dietmar Livne, Michelle Leppin, Heiko Akay, Ela M. Aydin, Orhun U. Behland, Jonas Sobesky, Jan Vajkoczy, Peter Madai, Vince I. |
author_sort | Frey, Dietmar |
collection | PubMed |
description | BACKGROUND: Cerebrovascular disease, in particular stroke, is a major public health challenge. An important biomarker is cerebral hemodynamics. To measure and quantify cerebral hemodynamics, however, only invasive, potentially harmful or time-to-treatment prolonging methods are available. RESULTS: We present a simulation-based approach which allows calculation of cerebral hemodynamics based on the patient-individual vessel configuration derived from structural vessel imaging. For this, we implemented a framework allowing segmentation and annotation of brain vessels from structural imaging followed by 0-dimensional lumped simulation modeling of cerebral hemodynamics. For annotation, a 3D-graphical user interface was implemented. For 0D-simulation, we used a modified nodal analysis, which was adapted for easy implementation by code. The simulation enables identification of areas vulnerable to stroke and simulation of changes due to different systemic blood pressures. Moreover, sensitivity analysis was implemented allowing the live simulation of changes to simulate procedures and disease progression. Beyond presentation of the framework, we demonstrated in an exploratory analysis in 67 patients that the simulation has a high specificity and low-to-moderate sensitivity to detect perfusion changes in classic perfusion imaging. CONCLUSIONS: The presented precision medicine approach using novel biomarkers has the potential to make the application of harmful and complex perfusion methods obsolete. |
format | Online Article Text |
id | pubmed-8088619 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-80886192021-05-03 A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease Frey, Dietmar Livne, Michelle Leppin, Heiko Akay, Ela M. Aydin, Orhun U. Behland, Jonas Sobesky, Jan Vajkoczy, Peter Madai, Vince I. Biomed Eng Online Research BACKGROUND: Cerebrovascular disease, in particular stroke, is a major public health challenge. An important biomarker is cerebral hemodynamics. To measure and quantify cerebral hemodynamics, however, only invasive, potentially harmful or time-to-treatment prolonging methods are available. RESULTS: We present a simulation-based approach which allows calculation of cerebral hemodynamics based on the patient-individual vessel configuration derived from structural vessel imaging. For this, we implemented a framework allowing segmentation and annotation of brain vessels from structural imaging followed by 0-dimensional lumped simulation modeling of cerebral hemodynamics. For annotation, a 3D-graphical user interface was implemented. For 0D-simulation, we used a modified nodal analysis, which was adapted for easy implementation by code. The simulation enables identification of areas vulnerable to stroke and simulation of changes due to different systemic blood pressures. Moreover, sensitivity analysis was implemented allowing the live simulation of changes to simulate procedures and disease progression. Beyond presentation of the framework, we demonstrated in an exploratory analysis in 67 patients that the simulation has a high specificity and low-to-moderate sensitivity to detect perfusion changes in classic perfusion imaging. CONCLUSIONS: The presented precision medicine approach using novel biomarkers has the potential to make the application of harmful and complex perfusion methods obsolete. BioMed Central 2021-05-01 /pmc/articles/PMC8088619/ /pubmed/33933080 http://dx.doi.org/10.1186/s12938-021-00880-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Frey, Dietmar Livne, Michelle Leppin, Heiko Akay, Ela M. Aydin, Orhun U. Behland, Jonas Sobesky, Jan Vajkoczy, Peter Madai, Vince I. A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease |
title | A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease |
title_full | A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease |
title_fullStr | A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease |
title_full_unstemmed | A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease |
title_short | A precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease |
title_sort | precision medicine framework for personalized simulation of hemodynamics in cerebrovascular disease |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8088619/ https://www.ncbi.nlm.nih.gov/pubmed/33933080 http://dx.doi.org/10.1186/s12938-021-00880-w |
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