The objective of this study is to establish the feasibility of fiber-optic dual-modality (morphological and mechanical) optical coherence tomography (OCT) for minimally invasive tissue characterization with microscopic resolution in the management of breast cancer. The long term goal is to improve the outcome of diagnosis and treatment of breast cancer through OCT characterization of breast tissue. OCT is a cross-sectional imaging technology with high resolution and high imaging speed. Based on the fact that cancerous breast tissue has altered morphological and mechanical properties in microscale, we hypothesize that dual-modality OCT characterization on breast tissue will provide more accurate differentiation between cancerous and normal breast tissue. We will develop and optimize a novel dual-modality OCT system that performs structural OCT imaging and quantitative optical coherence elastography (qOCE) on the same volume of breast tissue. To test the central hypothesis of this study, we will establish synergistic biomarkers based on dual-modality characterization of breast tissue. We will validate that the biomarker including both morphological features and tissue stiffness will lead to improved accuracy in the classification of breast tissue.
The objective of this study is to establish the feasibility of fiber-optic dual-modality (morphological and mechanical) optical coherence tomography (OCT) for minimally invasive tissue characterization with microscopic resolution in the management of breast cancer. We will develop and optimize a novel dual-modality OCT system that performs structural OCT imaging and quantitative optical coherence elastography (qOCE) on breast tissue, establish and validate synergistic biomarkers to achieve improved accuracy in automatic classification of breast tissue.
| Liu, Xuan; Zaki, Farzana; Renaud, Dylan (2018) Assessment and removal of additive noise in a complex optical coherence tomography signal based on Doppler variation analysis. Appl Opt 57:2873-2880 |
