Cargando…
Two-layer analytical model for estimation of layer thickness and flow using Diffuse Correlation Spectroscopy
Diffuse correlation spectroscopy (DCS) has been widely explored for its ability to measure cerebral blood flow (CBF), however, mostly under the assumption that the human head is homogenous. In addition to CBF, knowledge of extracerebral layers, such as skull thickness, can be informative and crucial...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481000/ https://www.ncbi.nlm.nih.gov/pubmed/36112634 http://dx.doi.org/10.1371/journal.pone.0274258 |
_version_ | 1784791164442902528 |
---|---|
author | Wu, Jingyi Tabassum, Syeda Brown, William L. Wood, Sossena Yang, Jason Kainerstorfer, Jana M. |
author_facet | Wu, Jingyi Tabassum, Syeda Brown, William L. Wood, Sossena Yang, Jason Kainerstorfer, Jana M. |
author_sort | Wu, Jingyi |
collection | PubMed |
description | Diffuse correlation spectroscopy (DCS) has been widely explored for its ability to measure cerebral blood flow (CBF), however, mostly under the assumption that the human head is homogenous. In addition to CBF, knowledge of extracerebral layers, such as skull thickness, can be informative and crucial for patient with brain complications such as traumatic brain injuries. To bridge the gap, this study explored the feasibility of simultaneously extracting skull thickness and flow in the cortex layer using DCS. We validated a two-layer analytical model that assumed the skull as top layer with a finite thickness and the brain cortex as bottom layer with semi-infinite geometry. The model fitted for thickness of the top layer and flow of the bottom layer, while assumed other parameters as constant. The accuracy of the two-layer model was tested against the conventional single-layer model using measurements from custom made two-layer phantoms mimicking skull and brain. We found that the fitted top layer thickness at each source detector (SD) distance is correlated with the expected thickness. For the fitted bottom layer flow, the two-layer model fits relatively consistent flow across all top layer thicknesses. In comparison, the conventional one-layer model increasingly underestimates the bottom layer flow as top layer thickness increases. The overall accuracy of estimating first layer thickness and flow depends on the SD distance in relationship to first layer thickness. Lastly, we quantified the influence of uncertainties in the optical properties of each layer. We found that uncertainties in the optical properties only mildly influence the fitted thickness and flow. In this work we demonstrate the feasibility of simultaneously extracting of layer thickness and flow using a two-layer DCS model. Findings from this work may introduce a robust and cost-effective approach towards simultaneous bedside assessment of skull thickness and cerebral blood flow. |
format | Online Article Text |
id | pubmed-9481000 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-94810002022-09-17 Two-layer analytical model for estimation of layer thickness and flow using Diffuse Correlation Spectroscopy Wu, Jingyi Tabassum, Syeda Brown, William L. Wood, Sossena Yang, Jason Kainerstorfer, Jana M. PLoS One Research Article Diffuse correlation spectroscopy (DCS) has been widely explored for its ability to measure cerebral blood flow (CBF), however, mostly under the assumption that the human head is homogenous. In addition to CBF, knowledge of extracerebral layers, such as skull thickness, can be informative and crucial for patient with brain complications such as traumatic brain injuries. To bridge the gap, this study explored the feasibility of simultaneously extracting skull thickness and flow in the cortex layer using DCS. We validated a two-layer analytical model that assumed the skull as top layer with a finite thickness and the brain cortex as bottom layer with semi-infinite geometry. The model fitted for thickness of the top layer and flow of the bottom layer, while assumed other parameters as constant. The accuracy of the two-layer model was tested against the conventional single-layer model using measurements from custom made two-layer phantoms mimicking skull and brain. We found that the fitted top layer thickness at each source detector (SD) distance is correlated with the expected thickness. For the fitted bottom layer flow, the two-layer model fits relatively consistent flow across all top layer thicknesses. In comparison, the conventional one-layer model increasingly underestimates the bottom layer flow as top layer thickness increases. The overall accuracy of estimating first layer thickness and flow depends on the SD distance in relationship to first layer thickness. Lastly, we quantified the influence of uncertainties in the optical properties of each layer. We found that uncertainties in the optical properties only mildly influence the fitted thickness and flow. In this work we demonstrate the feasibility of simultaneously extracting of layer thickness and flow using a two-layer DCS model. Findings from this work may introduce a robust and cost-effective approach towards simultaneous bedside assessment of skull thickness and cerebral blood flow. Public Library of Science 2022-09-16 /pmc/articles/PMC9481000/ /pubmed/36112634 http://dx.doi.org/10.1371/journal.pone.0274258 Text en © 2022 Wu et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Wu, Jingyi Tabassum, Syeda Brown, William L. Wood, Sossena Yang, Jason Kainerstorfer, Jana M. Two-layer analytical model for estimation of layer thickness and flow using Diffuse Correlation Spectroscopy |
title | Two-layer analytical model for estimation of layer thickness and flow using Diffuse Correlation Spectroscopy |
title_full | Two-layer analytical model for estimation of layer thickness and flow using Diffuse Correlation Spectroscopy |
title_fullStr | Two-layer analytical model for estimation of layer thickness and flow using Diffuse Correlation Spectroscopy |
title_full_unstemmed | Two-layer analytical model for estimation of layer thickness and flow using Diffuse Correlation Spectroscopy |
title_short | Two-layer analytical model for estimation of layer thickness and flow using Diffuse Correlation Spectroscopy |
title_sort | two-layer analytical model for estimation of layer thickness and flow using diffuse correlation spectroscopy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9481000/ https://www.ncbi.nlm.nih.gov/pubmed/36112634 http://dx.doi.org/10.1371/journal.pone.0274258 |
work_keys_str_mv | AT wujingyi twolayeranalyticalmodelforestimationoflayerthicknessandflowusingdiffusecorrelationspectroscopy AT tabassumsyeda twolayeranalyticalmodelforestimationoflayerthicknessandflowusingdiffusecorrelationspectroscopy AT brownwilliaml twolayeranalyticalmodelforestimationoflayerthicknessandflowusingdiffusecorrelationspectroscopy AT woodsossena twolayeranalyticalmodelforestimationoflayerthicknessandflowusingdiffusecorrelationspectroscopy AT yangjason twolayeranalyticalmodelforestimationoflayerthicknessandflowusingdiffusecorrelationspectroscopy AT kainerstorferjanam twolayeranalyticalmodelforestimationoflayerthicknessandflowusingdiffusecorrelationspectroscopy |