Monte Carlo simulation of fluorescence imaging of microvasculature

Little numerical analysis has been done on fluorescence lifetime imaging \emph{in-vivo}. Here, a 3D fluorescence Monte Carlo model is used to evaluate a microvasculature geometry obtained via two-photon microscopy. I found that a bulk-vascularization assumption does not provide an accurate picture o...

Full description

Bibliographic Details
Main Author: Davis, Mitchell Alan
Format: Others
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/2152/ETD-UT-2011-08-4191
id ndltd-UTEXAS-oai-repositories.lib.utexas.edu-2152-ETD-UT-2011-08-4191
record_format oai_dc
spelling ndltd-UTEXAS-oai-repositories.lib.utexas.edu-2152-ETD-UT-2011-08-41912015-09-20T17:12:48ZMonte Carlo simulation of fluorescence imaging of microvasculatureDavis, Mitchell AlanLight propagation in tissuesLittle numerical analysis has been done on fluorescence lifetime imaging \emph{in-vivo}. Here, a 3D fluorescence Monte Carlo model is used to evaluate a microvasculature geometry obtained via two-photon microscopy. I found that a bulk-vascularization assumption does not provide an accurate picture of penetration depth of the collected fluorescence signal. Instead the degree of absorption difference between extravascular and intravascular space, as well as the absorption difference between excitation and emission wavelengths must be taken into account to determine the depth distribution. Additionally, I found that using targeted illumination can provide for superior surface vessel sensitivity over wide-field illumination, with small area detection offering an even greater amount of sensitivity to surface vasculature. Depth sensitivity can be enhanced by either increasing the detector area or increasing the illumination area. Finally, it is shown that the excitation wavelength and vessel size can affect intra-vessel sampling distribution, as well as the amount of signal that originates from inside the vessel under targeted illumination conditions.text2013-01-03T21:05:02Z2013-01-03T21:05:02Z2011-082013-01-03August 20112013-01-03T21:05:10Zthesisapplication/pdfhttp://hdl.handle.net/2152/ETD-UT-2011-08-41912152/ETD-UT-2011-08-4191eng
collection NDLTD
language English
format Others
sources NDLTD
topic Light propagation in tissues
spellingShingle Light propagation in tissues
Davis, Mitchell Alan
Monte Carlo simulation of fluorescence imaging of microvasculature
description Little numerical analysis has been done on fluorescence lifetime imaging \emph{in-vivo}. Here, a 3D fluorescence Monte Carlo model is used to evaluate a microvasculature geometry obtained via two-photon microscopy. I found that a bulk-vascularization assumption does not provide an accurate picture of penetration depth of the collected fluorescence signal. Instead the degree of absorption difference between extravascular and intravascular space, as well as the absorption difference between excitation and emission wavelengths must be taken into account to determine the depth distribution. Additionally, I found that using targeted illumination can provide for superior surface vessel sensitivity over wide-field illumination, with small area detection offering an even greater amount of sensitivity to surface vasculature. Depth sensitivity can be enhanced by either increasing the detector area or increasing the illumination area. Finally, it is shown that the excitation wavelength and vessel size can affect intra-vessel sampling distribution, as well as the amount of signal that originates from inside the vessel under targeted illumination conditions. === text
author Davis, Mitchell Alan
author_facet Davis, Mitchell Alan
author_sort Davis, Mitchell Alan
title Monte Carlo simulation of fluorescence imaging of microvasculature
title_short Monte Carlo simulation of fluorescence imaging of microvasculature
title_full Monte Carlo simulation of fluorescence imaging of microvasculature
title_fullStr Monte Carlo simulation of fluorescence imaging of microvasculature
title_full_unstemmed Monte Carlo simulation of fluorescence imaging of microvasculature
title_sort monte carlo simulation of fluorescence imaging of microvasculature
publishDate 2013
url http://hdl.handle.net/2152/ETD-UT-2011-08-4191
work_keys_str_mv AT davismitchellalan montecarlosimulationoffluorescenceimagingofmicrovasculature
_version_ 1716822808323948544