dc.contributor.authorDong, Jing
dc.date.accessioned2013-09-11T05:49:27Z
dc.date.accessioned2017-07-23T08:26:03Z
dc.date.available2013-09-11T05:49:27Z
dc.date.available2017-07-23T08:26:03Z
dc.date.copyright2013en_US
dc.date.issued2013
dc.identifier.citationDong, J. (2013). Development of near infrared diffuse optics-based flowmetry for non-invasive deep tissue perfusion assessment. Doctoral thesis, Nanyang Technological University, Singapore.
dc.identifier.urihttp://hdl.handle.net/10356/54850
dc.description.abstractThe continuous running of blood in the cardiovascular system is very important since it carries oxygen as well as other nutrition to support the metabolic activity of the other organs of the body. Consequently, the monitoring of blood flow becomes critical in clinical cases. For the past decades, plenty of wellknown and notable methodology had been developed for non-invasive measurement of blood flow. For example, laser Doppler flowmetry and laser speckle flowmetry are developed for shallow blood flow measurement, and diffuse correlation spectroscopy (DCS) has been recognized as a standard technique for deep tissue perfusion monitoring. In DCS, the autocorrelation of speckle fluctuations of the scattered light from a coherent source is measured to obtain the information of the motion of red blood cells. So far, instrument for measuring relative blood flow in deep tissue has been already built, involving usage of hardware autocorrelator and other optical components. However, on one hand, there was no real-time device available for non-invasive deep tissue perfusion assessment; on the other hand, the expense was always the issue along with the increasing number of channel especially when applying the technology to clinical settings. Therefore, this project is focused towards development of near infrared diffuse optics-based flowmetry for non-invasively assessing deep tissue blood perfusion. The capability of non-invasively assessing blood flow information in deep tissue in real-time will benefit the diagnosis as well as medical treatment directly. The series of studies in this thesis has unfolded as follows. It initially began with a motivation of building a flexible software autocorrelator-based single channel real-time diffuse correlation spectroscopy system. The system was then utilized in monitoring the tumor response during photodynamic therapy treatment in animal model. As real-time DCS system was able to record the raw photon count signal, complexity measures such as sample entropy analysis was subsequently used on this raw signal as a possible alternative of autocorrelation-based DCS. Furthermore, with the help of laser speckle contrast imaging (LSCI) we explored the diffuse speckle contrast analysis for deep tissue blood flow measurement which has great potential for multi-channel system. More detailed description of each study is following. Firstly, in order to balance the cost and performance, the software autocorrelator-based diffuse correlation spectroscopy system was developed using Fast Fourier Transform (FFT), followed by applying the system to monitor the tumor response in photodynamic therapy (PDT) that was conducted on mice model. Instrumentation-wise, besides the basic optical components, only a reasonably fast counter is sufficient so that the cost can be reduced. The whole system, being controlled by LabVIEW, can be operated in real-time to obtain the relative blood flow (rBF). In addition, as the raw photon count signal is recorded, it provides more room to explore other methods to obtain blood perfusion information in deep tissue. Sample entropy (SampEn), which gains increasing popularity in physiological time series, is a novel approach we applied to the photon count signals that are obtained from software autocorrelator based DCS system. It has been well known that the complexity of the system can be characterized by entropy. Since the detected photons which undergo scattering events in the sample carry the information of moving scatterers, this project applied sample entropy analysis to diffuse reflectance signals. To our knowledge, this is the first time to correlate the sample entropy to tissue blood perfusion information. Compared to DCS, SampEn is simple in concept because it is not based on model fitting which is commonly utilized in DCS. Moreover, SampEn holds the merits of being computationally light weight, thus it is also suitable for real-time analysis. As an alternative approach, this model-free method for quantifying the relative flow will be useful in clinical setting where real-time flow assessment is necessary. In an effort to exploit deep tissue flowmetry with multiple channels based on the concept of LSCI, a CCD-based diffuse speckle contrast analysis (DSCA) method was ingeniously developed. This method not only alleviates the requirement of instrumentation, but also paves the way for depth-sensitive blood flow measurement in the future work.en_US
dc.format.extent168 p.en_US
dc.language.isoenen_US
dc.subjectDRNTU::Engineering::Bioengineeringen_US
dc.titleDevelopment of near infrared diffuse optics-based flowmetry for non-invasive deep tissue perfusion assessmenten_US
dc.typeThesis
dc.contributor.schoolSchool of Chemical and Biomedical Engineeringen_US
dc.contributor.supervisorLee Kijoonen_US
dc.description.degreeDOCTOR OF PHILOSOPHY (SCBE)en_US
dc.identifier.doihttps://doi.org/10.32657/10356/54850
dc.contributor.organizationNational Cancer Centre Singaporeen_US


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