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Numerical Model for Cerebrovascular Hemodynamics with Indocyanine Green Fluorescence Videoangiography
OBJECTIVE: The use of indocyanine green videoangiography (ICG-VA) to assess blood flow in the brain during cerebrovascular surgery has been increasing. Clinical studies on ICG-VA have predominantly focused on qualitative analysis. However, quantitative analysis numerical modelling for time profiling...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Neurosurgical Society
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10323270/ https://www.ncbi.nlm.nih.gov/pubmed/36153874 http://dx.doi.org/10.3340/jkns.2022.0180 |
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author | Cheon, Hwayeong Son, Young-Je Park, Sung Bae Shim, Pyoung-Seop Son, Joo-Hiuk Yang, Hee-Jin |
author_facet | Cheon, Hwayeong Son, Young-Je Park, Sung Bae Shim, Pyoung-Seop Son, Joo-Hiuk Yang, Hee-Jin |
author_sort | Cheon, Hwayeong |
collection | PubMed |
description | OBJECTIVE: The use of indocyanine green videoangiography (ICG-VA) to assess blood flow in the brain during cerebrovascular surgery has been increasing. Clinical studies on ICG-VA have predominantly focused on qualitative analysis. However, quantitative analysis numerical modelling for time profiling enables a more accurate evaluation of blood flow kinetics. In this study, we established a multiple exponential modified Gaussian (multi-EMG) model for quantitative ICG-VA to understand accurately the status of cerebral hemodynamics. METHODS: We obtained clinical data of cerebral blood flow acquired the quantitative analysis ICG-VA during cerebrovascular surgery. Varied asymmetric peak functions were compared to find the most matching function form with clinical data by using a nonlinear regression algorithm. To verify the result of the nonlinear regression, the mode function was applied to various types of data. RESULTS: The proposed multi-EMG model is well fitted to the clinical data. Because the primary parameters—growth and decay rates, and peak center and heights—of the model are characteristics of model function, they provide accurate reference values for assessing cerebral hemodynamics in various conditions. In addition, the primary parameters can be estimated on the curves with partially missed data. The accuracy of the model estimation was verified by a repeated curve fitting method using manipulation of missing data. CONCLUSION: The multi-EMG model can possibly serve as a universal model for cerebral hemodynamics in a comparison with other asymmetric peak functions. According to the results, the model can be helpful for clinical research assessment of cerebrovascular hemodynamics in a clinical setting. |
format | Online Article Text |
id | pubmed-10323270 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Korean Neurosurgical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-103232702023-07-07 Numerical Model for Cerebrovascular Hemodynamics with Indocyanine Green Fluorescence Videoangiography Cheon, Hwayeong Son, Young-Je Park, Sung Bae Shim, Pyoung-Seop Son, Joo-Hiuk Yang, Hee-Jin J Korean Neurosurg Soc Laboratory Research OBJECTIVE: The use of indocyanine green videoangiography (ICG-VA) to assess blood flow in the brain during cerebrovascular surgery has been increasing. Clinical studies on ICG-VA have predominantly focused on qualitative analysis. However, quantitative analysis numerical modelling for time profiling enables a more accurate evaluation of blood flow kinetics. In this study, we established a multiple exponential modified Gaussian (multi-EMG) model for quantitative ICG-VA to understand accurately the status of cerebral hemodynamics. METHODS: We obtained clinical data of cerebral blood flow acquired the quantitative analysis ICG-VA during cerebrovascular surgery. Varied asymmetric peak functions were compared to find the most matching function form with clinical data by using a nonlinear regression algorithm. To verify the result of the nonlinear regression, the mode function was applied to various types of data. RESULTS: The proposed multi-EMG model is well fitted to the clinical data. Because the primary parameters—growth and decay rates, and peak center and heights—of the model are characteristics of model function, they provide accurate reference values for assessing cerebral hemodynamics in various conditions. In addition, the primary parameters can be estimated on the curves with partially missed data. The accuracy of the model estimation was verified by a repeated curve fitting method using manipulation of missing data. CONCLUSION: The multi-EMG model can possibly serve as a universal model for cerebral hemodynamics in a comparison with other asymmetric peak functions. According to the results, the model can be helpful for clinical research assessment of cerebrovascular hemodynamics in a clinical setting. Korean Neurosurgical Society 2023-07 2022-09-26 /pmc/articles/PMC10323270/ /pubmed/36153874 http://dx.doi.org/10.3340/jkns.2022.0180 Text en Copyright © 2023 The Korean Neurosurgical Society https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Laboratory Research Cheon, Hwayeong Son, Young-Je Park, Sung Bae Shim, Pyoung-Seop Son, Joo-Hiuk Yang, Hee-Jin Numerical Model for Cerebrovascular Hemodynamics with Indocyanine Green Fluorescence Videoangiography |
title | Numerical Model for Cerebrovascular Hemodynamics with Indocyanine Green Fluorescence Videoangiography |
title_full | Numerical Model for Cerebrovascular Hemodynamics with Indocyanine Green Fluorescence Videoangiography |
title_fullStr | Numerical Model for Cerebrovascular Hemodynamics with Indocyanine Green Fluorescence Videoangiography |
title_full_unstemmed | Numerical Model for Cerebrovascular Hemodynamics with Indocyanine Green Fluorescence Videoangiography |
title_short | Numerical Model for Cerebrovascular Hemodynamics with Indocyanine Green Fluorescence Videoangiography |
title_sort | numerical model for cerebrovascular hemodynamics with indocyanine green fluorescence videoangiography |
topic | Laboratory Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10323270/ https://www.ncbi.nlm.nih.gov/pubmed/36153874 http://dx.doi.org/10.3340/jkns.2022.0180 |
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