DEVELOPMENT OF DIFFUSE OPTICS FOR BED-SIDE MONITORING

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Diffuse optics holds promise for implementation as a bedside monitor of blood flow, blood oxygen saturation and oxygen metabolism in the brain. Diffuse optical spectroscopy (DOS), for measuring blood oxygen saturation and total hemoglobin concentration, has been under development for some time and significant progress has been made. Our laboratory has played a leading role at the forefront of this activity. Recently, we have introduced a new technology called diffuse correlation spectroscopy (DCS) that permits optical measurement deep tissue blood flow. By combining these two methodologies (DOS/DCS) in a single hybrid device, we can obtain a better picture of the underlying brain physiology and can even estimate brain oxygen metabolism as a surrogate marker of cerebral well-being. The key feature of the diffuse optical approach is its potential as a continuous, non-invasive, quantitative monitor at the bedside. We expect that future applications pertaining to other brain disorders will be realized, but because of the clear rationale and immense public health significance of stroke, we have elected to focus substantial effort on the management of acute, cortical strokes. With this bedside monitor, patient management that often focuses on optimization of cerebral blood flow can be individualized based on the underlying patho-physiology of each patient. Thus far, use in functional activation studies of intact human brain and in patients with acute stroke has been demonstrated. Further algorithmic and technological developments are necessary to improve the fidelity of the data.