Quantitative assessment of elasticity properties of skin using surface acoustic wave (SAW) method

  • Chunhui Li

    Student thesis: Doctoral ThesisDoctor of Philosophy

    Abstract

    Mechanical properties are important tissue parameters of skin that are useful for understanding skin patho-physiology, and aiding disease diagnosis and treatment. They are indicators of functional changes and pathological variations in the micro-structure.

    This research thesis studies the intersection of acoustics, optics and biomechanics for skin mechanical properties measurement. Surface acoustic wave (SAW) is induced and applied to a range of different tissue mimicking phantom models, Thiel cadavers and in vivo human skin. Different optical systems, i.e. low coherence interferometer and phase sensitive optical coherence tomography (PhS-OCT), are employed to detect the SAW. The Young’s moduli and thicknesses of model layers are assessed by the analysis of the wave phase velocity curves. The PhS-OCT detection system can also provide the real time high resolution depth-resolved cross-sectional microstructure imaging of the interrogated sample to assist the elasticity evaluation of the heterogeneous tissue.

    Results prove that the novel combination of optical imaging technology with SAW method is able to assess the elasticity change in both axial and transverse directions in soft material. It can be used to evaluate the mechanical properties of single, double-layer soft tissue mimicking phantoms and different sites of human skin ex vivo and in vivo non-invasively. This study also demonstrates that the SAW method can be successfully utilized to map the elasticity of soft heterogeneous tissues quantitatively. The results represent an important step towards the development of SAW method as a clinical diagnosis tool in dermatology, and may offer potential in diagnostic and therapeutic clinical applications.
    Date of Award2014
    Original languageEnglish
    Awarding Institution
    • University of Dundee
    SupervisorZhihong Huang (Supervisor)

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