Proceedings Article | 17 March 2016
Chih-Hao Liu, Yong Du, Manmohan Singh, Jiasong Li, Chen Wu, Zhaolong Han, Raksha Raghunathan, Thomas Hsu, Shezaan Noorani, M. John Hicks, Chandra Mohan, Kirill Larin
KEYWORDS: Skin, Tissue optics, Coherence (optics), Elastography, Optical coherence tomography, Natural surfaces, Connective tissue, Collagen, Spatial resolution, In vitro testing, Wave propagation, Tissues, Signal attenuation, In vivo imaging
Systemic sclerosis (SSc) is a connective tissue disease that results in excessive accumulation of collagen in the skin and internal organs. Overall, SSc is a rare disorder, but has a high mortality, particularly in last decade of life. To improve the survival rate, an accurate and early diagnosis is crucial. Currently, the modified Rodnan skin score (mRSS) is the gold standard for evaluating SSc progression based on clinical palpation at 17 sites on the body. However, this procedure can be time consuming, and the assessed score may be biased by the experience of the clinician, causing inter- and intraobserver variabilities. Moreover, the instrinsic elasticity of skin may further bias the mRSS assessment in the early stages of SSc, such as oedematous. To overcome these limitations, there is a need for a rapid, accurate, and objective assessment technique. Optical coherence elastography (OCE) is a novel, rapidly emerging technique, which can assess mechanical contrast in tissues with micrometer spatial resolution. In this work, we demonstrate the first use of OCE to assess the mechanical properties of control and SSc-like diseased skin non-invasively. A focused air-pulse induced an elastic wave in the skin, which was detected by a home-built OCE system. The elastic wave propagated significantly faster in SSc skin compared to healthy skin. The Young’s modulus of the SSc skin was significantly higher than that of normal skin (P<0.05). Thus, OCE was able to objectively differentiate healthy and fibrotic skin completely noninvasively and is a promising and potentially useful new technology for quantifying skin involvement in SSc.
