Dynamic imaging and quantification of subcellular motion with eigen‐decomposition optical coherence tomography‐based variance analysis. Issue 10 (9th July 2019) - Wei, Wei; Tang, Peijun; Xie, Zhiying; Li, Yuandong; Wang, Ruikang K.
Abstract: The dynamic properties of subcellular organism are important biomarkers of the health. Imaging subcellular level dynamics provides effective solutions for evaluating cell metabolism and testing the responses of cells to pathogens and drugs in pharmaceutical engineering. In this paper, we demonstrate an innovative approach to contrast the subcellular motion by using eigen decomposition (ED)‐based variance analysis of time‐dependent complex optical coherence tomography signals. This method reveals a superior advantage of contrast to noise ratio when compared with the approach that employs intensity decorrelation. Furthermore, the eigen values derived from ED processing are calculated and applied to assess the power ratios of complex signal invariance that decreases exponentially along time dimension. The validation experiments are performed on the patterned samples of yeast powder mixed with gelatin/TiO2 water solution. Additionally, the proposed method is used to image mouse cerebral cortex in normal and pathological conditions, suggesting the practicality of variance power mapping in analyzing cortical neural activities. The technique promises efficient measurement of subcellular motions with high sensitivity and high throughput for in vivo and in situ applications. Abstract : Highly sensitive optical coherence tomography (OCT) angiography, implemented through eigen decompensation of the captured OCT signals, is capable of imaging subcellular level dynamics, providing effective solutions for evaluating cell metabolism and testing the responses of cells to pathogens and drugs in pharmaceutical engineering.