Open Access Presentation
21 November 2018 Optical assessment of cerebral autoregulation
Author Affiliations +
Proceedings Volume 10481, Neural Imaging and Sensing 2018; 1048105 (2018) https://doi.org/10.1117/12.2319246
Event: SPIE BiOS, 2018, San Francisco, California, United States
Abstract
Cerebral autoregulation (CA) is a homeostatic mechanism that maintains a relatively constant cerebral blood flow (CBF) in the presence of changes in the cerebral perfusion pressure (CCP), defined as the difference between mean arterial pressure (MAP) and intracranial pressure (ICP). Given the importance of adequate and consistent brain perfusion, CA is critical for brain viability and is known to be impaired in a number of neurological disorders. Global brain measurements of dynamic CA have been performed with transcranial Doppler ultrasound (to sense the blood flow velocity in the middle cerebral artery) and finger plethysmography (to measure systemic MAP as a surrogate for CCP). Optical methods offer the advantage of providing local measurements of cerebral blood flow and CA, thus allowing for local assessment and spatial mapping of CA. Optical techniques for the non-invasive assessment of CA include near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS). I will describe our approach to CA assessment with NIRS, complemented by the novel technique of coherent hemodynamics spectroscopy (CHS), and our findings of the expected enhancement in CA during hyperventilation-induced hypocapnia. I will also report dynamic traces of local CBF measured with NIRS-CHS and DCS during transient changes in MAP. Optical techniques offer the potential to address the challenge of continuous monitoring of local cerebral autoregulation at the bedside and in a critical care environment.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sergio Fantini "Optical assessment of cerebral autoregulation", Proc. SPIE 10481, Neural Imaging and Sensing 2018, 1048105 (21 November 2018); https://doi.org/10.1117/12.2319246
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