Near-Infrared Spectroscopy (NIRS), a technique that employs near-infrared light to assess brain oxygenation, is widely used in fields including muscle physiology, cognitive psychology, neurology, and tumor biology. It is currently marketed as a brain oximeter, with numerous clinical and research applications. However, while conventional NIRS is portable, non-invasive, and inexpensive, measurement reliability is questionable due to its inherent limitations. First, conventional NIRS brain oxygenation measurements are obtained via proprietary algorithms that use a number of assumptions, resulting in sensitivity to probe positioning. Second, NIRS does not measure cerebral blood flow, which is required to relate brain oxygenation to metabolism and overall health. Our laboratory has demonstrated the basis for a new near-infrared light-based monitoring tool, called interferometric Near-Infrared Spectroscopy (iNIRS), which addresses these issues. iNIRS enhances quantitative capabilities of NIRS through interferometry. Critically, the iNIRS technique measures light?s time-of- flight (TOF), enabling more specific quantification of brain oxygenation than NIRS. Additionally, iNIRS quantifies blood flow, using the very same light photons that are used for oximetry. As a result, multi-wavelength iNIRS can potentially perform non-invasive monitoring of brain oxygen metabolism. This proposal will develop iNIRS technology, already demonstrated in vivo in our preliminary results, into a real-time multi-wavelength monitoring instrument, and thoroughly validate this instrument for quantifying blood flow, oxygenation, volume, and metabolism in the brain.
This proposal will develop and validate a novel, integrated, and robust optical instrument based on interferometric Near-infrared Spectroscopy (iNIRS) for brain monitoring. Measures of oxygenation, perfusion, and oxygen metabolism promise to enable risk-stratification for surgeries and improve follow-up care after brain injury. Moreover, these quantitative brain measures may eventually lead to new and improved early biomarkers for cerebral deficits.
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