Abstract
In order to achieve high-sensitivity time-domain diffuse correlation spectroscopy (TD-DCS) measurement of functional changes in cerebral blood flow, this study applied simulation methods to optimize the TD-DCS system under real experimental conditions (including the consideration of the effects of finite coherence length L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</sub> and non-ideal instrument response function IRF). Under a real experimental condition where the incident power is 75 mW, the source-detector distance is 1.0 cm, and the full width at half maxima of the IRF is 160 ps, we used simulation experiments to investigate the relationship between the contrast of the intensity autocorrelation function (g <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) in two brain functional states (i.e., baseline and activation) and TD-DCS system parameters (including L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</sub> , IRF, source-detector distance, gate opening time and gate width).Our simulation results show that both longer L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</sub> and longer integration time are beneficial to a more sensitive detection. With a fixed L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</sub> and integration time, the optimal parameters of gate opening time is 800 ps (relative to the peak time of IRF), and gate width is equal to or larger than 800 ps. This study may be useful for guiding the sensitive measurement of human brain functions (e.g., changes in cerebral blood flow) using the TD-DCS technology.
Highlights
Diffuse correlation spectroscopy (DCS) is an optical technique that was originally used to measure the dynamic properties of scattering media, such as latex and colloidal suspensions [1,2,3,4,5,6,7]
Under a real experimental condition where the incident power is 75 mW, the source-detector distance is 1.0 cm, and the full width at half maxima of the instrument response function (IRF) is 160 ps, we used simulation experiments to investigate the relationship between the contrast of the intensity autocorrelation function (g2) in two brain functional states and time-domain diffuse correlation spectroscopy (TD-DCS) system parameters.Our simulation results show that both longer LC and longer integration time are beneficial to a more sensitive detection
We studied the effect of IRF, LC, gate opening time and gate width on the TD-DCS intensity autocorrelation function (g2)
Summary
Diffuse correlation spectroscopy (DCS) is an optical technique that was originally used to measure the dynamic properties of scattering media, such as latex and colloidal suspensions [1,2,3,4,5,6,7]. DCS measures the temporal intensity autocorrelation function ( g2 ) of a single speckle to characterize the dynamic properties of the sample. DCS has been successfully used for measuring the blood flow (e.g., blood flow index, BFi) including the cerebral blood flow (CBF), and it is becoming an important optical imaging modality for studying human tissues and brain. The biomedical applications of DCS include but are not limited to characterizing tumor micro-vessels, monitoring chemotherapy [3,7] and monitoring or estimating cerebral blood flow and oxygenation in human brain [4,6]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
