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Proceedings Paper

Interferometric near-infrared spectroscopy (iNIRS) at short source-detector separations (Conference Presentation)
Author(s): Oybek Kholiqov; Wenjun Zhou; Vivek J. Srinivasan

Paper Abstract

Interferometric near-infrared spectroscopy (iNIRS) is a recently introduced time-of-flight- (TOF-) resolved sensing method for quantifying optical and dynamical properties of turbid media non-invasively. iNIRS measures the interference spectrum of light traversing a turbid medium using a rapidly tunable, or frequency swept, light source. While the modality was successfully demonstrated in vivo in the nude mouse brain for monitoring absorption, reduced scattering, and blood flow index, translation towards human measurements requires improving light collection efficiency. Particularly, interrogating cortical tissue beneath the adult human scalp and skull remains challenging due to the limited core size and throughput of the single mode fiber currently used for detection. To tackle this problem, we implement a short to null source-detector separation geometry setup to significantly improve the number of detected diffuse photons. We discuss both hardware and post-processing improvements to isolate the desired diffuse signal from the large, non-diffuse and specular signals. Furthermore, key improvements in the iNIRS optical system, including higher TOF resolution (22-60 ps), optimized dynamic range (36-47 dB), faster sweep rate (50-500 kHz), and a technique for combining the forward and backward sweeps to double the effective optical field autocorrelation sampling rate, are presented. These allow for more precise and quantitative extraction of in vivo optical properties and TOF-resolved dynamics at long path lengths. Collectively, these key advances in the technology pave the way for translating iNIRS towards non-invasive, real-time, and quantitative measurements of oxygen metabolism and blood perfusion in deep human tissues.

Paper Details

Date Published: 14 March 2018
Proc. SPIE 10481, Neural Imaging and Sensing 2018, 104810X (14 March 2018);
Show Author Affiliations
Oybek Kholiqov, Univ. of California, Davis (United States)
Wenjun Zhou, Univ. of California, Davis (United States)
Vivek J. Srinivasan, Univ. of California, Davis (United States)

Published in SPIE Proceedings Vol. 10481:
Neural Imaging and Sensing 2018
Qingming Luo; Jun Ding, Editor(s)

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