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Title: Detecting tissue optical and mechanical properties with an ultrasound-modulated optical imaging system
Author: Cheng, Yi
ISNI:       0000 0004 5349 5609
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2015
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Tissue optical and mechanical properties are related to tissue pathological changes. The ability to measure both tissue elasticity and its optical properties using the same hardware offers a significant advantage over existing techniques in, e.g. imaging of cancer. Therefore this thesis aims to develop a dual mode imaging system capable of noninvasively sensing local optical and mechanical properties at centimetre depths in samples. The proposed method is based on the detection of photons modulated by ultrasound and shear waves with a modified acoustic radiation force assisted ultrasound modulated optical tomography (ARF-UOT) system. Firstly the detection of the shear wave and ultrasound modulation with UOT was demonstrated at the surface of tissue mimicking phantoms. The ultrasound field or shear wave wavefront could be imaged by a single CCD exposure and analysis of local laser speckle contrast. Secondly, within tissue mimicking phantoms, while the shear waves cannot be imaged directly due to optical scattering, the propagation of a transient shear wave was tracked with global laser speckle contrast analysis. A differential method was developed to measure the local shear wave speed and quantify the elasticity of the tissue mimicking phantoms at ~cm depths. The method (SW-LASCA) was based on a modified ARF-UOT system. By generating continuous shear waves at different frequencies, the dispersion of shear wave speed was also investigated. The feasibility of the viscosity measurement was demonstrated by fitting the measured attenuation dispersion using the Voigt model. Finally, the dual mode system was explored by combining the SW-LASCA and ARF-UOT. The system was demonstrated in an optical reflection detection geometry and the scanning results of heterogeneous phantoms demonstrated the potential of the system to distinguish optical contrast, mechanical contrast and optical/mechanical contrast in a reflection detection geometry.
Supervisor: Meng-Xing, Tang; Daniel, Elson Sponsor: China Scholarship Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral