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Patient-oriented simulation based on Monte Carlo algorithm by using MRI data

BACKGROUND: Although Monte Carlo simulations of light propagation in full segmented three-dimensional MRI based anatomical models of the human head have been reported in many articles. To our knowledge, there is no patient-oriented simulation for individualized calibration with NIRS measurement. Thu...

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Autores principales: Chuang, Ching-Cheng, Lee, Yu-Tzu, Chen, Chung-Ming, Hsieh, Yao-Sheng, Liu, Tsan-Chi, Sun, Chia-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3355000/
https://www.ncbi.nlm.nih.gov/pubmed/22510474
http://dx.doi.org/10.1186/1475-925X-11-21
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author Chuang, Ching-Cheng
Lee, Yu-Tzu
Chen, Chung-Ming
Hsieh, Yao-Sheng
Liu, Tsan-Chi
Sun, Chia-Wei
author_facet Chuang, Ching-Cheng
Lee, Yu-Tzu
Chen, Chung-Ming
Hsieh, Yao-Sheng
Liu, Tsan-Chi
Sun, Chia-Wei
author_sort Chuang, Ching-Cheng
collection PubMed
description BACKGROUND: Although Monte Carlo simulations of light propagation in full segmented three-dimensional MRI based anatomical models of the human head have been reported in many articles. To our knowledge, there is no patient-oriented simulation for individualized calibration with NIRS measurement. Thus, we offer an approach for brain modeling based on image segmentation process with in vivo MRI T1 three-dimensional image to investigate the individualized calibration for NIRS measurement with Monte Carlo simulation. METHODS: In this study, an individualized brain is modeled based on in vivo MRI 3D image as five layers structure. The behavior of photon migration was studied for this individualized brain detections based on three-dimensional time-resolved Monte Carlo algorithm. During the Monte Carlo iteration, all photon paths were traced with various source-detector separations for characterization of brain structure to provide helpful information for individualized design of NIRS system. RESULTS: Our results indicate that the patient-oriented simulation can provide significant characteristics on the optimal choice of source-detector separation within 3.3 cm of individualized design in this case. Significant distortions were observed around the cerebral cortex folding. The spatial sensitivity profile penetrated deeper to the brain in the case of expanded CSF. This finding suggests that the optical method may provide not only functional signal from brain activation but also structural information of brain atrophy with the expanded CSF layer. The proposed modeling method also provides multi-wavelength for NIRS simulation to approach the practical NIRS measurement. CONCLUSIONS: In this study, the three-dimensional time-resolved brain modeling method approaches the realistic human brain that provides useful information for NIRS systematic design and calibration for individualized case with prior MRI data.
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spelling pubmed-33550002012-05-18 Patient-oriented simulation based on Monte Carlo algorithm by using MRI data Chuang, Ching-Cheng Lee, Yu-Tzu Chen, Chung-Ming Hsieh, Yao-Sheng Liu, Tsan-Chi Sun, Chia-Wei Biomed Eng Online Research BACKGROUND: Although Monte Carlo simulations of light propagation in full segmented three-dimensional MRI based anatomical models of the human head have been reported in many articles. To our knowledge, there is no patient-oriented simulation for individualized calibration with NIRS measurement. Thus, we offer an approach for brain modeling based on image segmentation process with in vivo MRI T1 three-dimensional image to investigate the individualized calibration for NIRS measurement with Monte Carlo simulation. METHODS: In this study, an individualized brain is modeled based on in vivo MRI 3D image as five layers structure. The behavior of photon migration was studied for this individualized brain detections based on three-dimensional time-resolved Monte Carlo algorithm. During the Monte Carlo iteration, all photon paths were traced with various source-detector separations for characterization of brain structure to provide helpful information for individualized design of NIRS system. RESULTS: Our results indicate that the patient-oriented simulation can provide significant characteristics on the optimal choice of source-detector separation within 3.3 cm of individualized design in this case. Significant distortions were observed around the cerebral cortex folding. The spatial sensitivity profile penetrated deeper to the brain in the case of expanded CSF. This finding suggests that the optical method may provide not only functional signal from brain activation but also structural information of brain atrophy with the expanded CSF layer. The proposed modeling method also provides multi-wavelength for NIRS simulation to approach the practical NIRS measurement. CONCLUSIONS: In this study, the three-dimensional time-resolved brain modeling method approaches the realistic human brain that provides useful information for NIRS systematic design and calibration for individualized case with prior MRI data. BioMed Central 2012-04-17 /pmc/articles/PMC3355000/ /pubmed/22510474 http://dx.doi.org/10.1186/1475-925X-11-21 Text en Copyright ©2012 Chuang et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Chuang, Ching-Cheng
Lee, Yu-Tzu
Chen, Chung-Ming
Hsieh, Yao-Sheng
Liu, Tsan-Chi
Sun, Chia-Wei
Patient-oriented simulation based on Monte Carlo algorithm by using MRI data
title Patient-oriented simulation based on Monte Carlo algorithm by using MRI data
title_full Patient-oriented simulation based on Monte Carlo algorithm by using MRI data
title_fullStr Patient-oriented simulation based on Monte Carlo algorithm by using MRI data
title_full_unstemmed Patient-oriented simulation based on Monte Carlo algorithm by using MRI data
title_short Patient-oriented simulation based on Monte Carlo algorithm by using MRI data
title_sort patient-oriented simulation based on monte carlo algorithm by using mri data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3355000/
https://www.ncbi.nlm.nih.gov/pubmed/22510474
http://dx.doi.org/10.1186/1475-925X-11-21
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