4.6 Article

High spatial and temporal resolution cerebrovascular reactivity for humans and large mammals: A technological description of integrated fNIRS and niABP mapping system

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FRONTIERS IN PHYSIOLOGY
卷 14, 期 -, 页码 -

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FRONTIERS MEDIA SA
DOI: 10.3389/fphys.2023.1124268

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cerebrovascular reactivity mapping system; cerebral autoregulation; near-infrared spectroscopy; neuroimaging system; cerebral heat maps; high temporal resolution; high spatial resolution; NIRS-based indices

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Cerebral autoregulation (CA) is the process of maintaining constant cerebral blood flow through constriction and dilation of cerebral vessels. Dynamic autoregulation assessment using multi-channel functional near-infrared spectroscopy and non-invasive arterial blood pressure devices can provide detailed information on CA over long periods of time. We developed a system that visualizes CA metrics by converting them to heat maps on a template of human brain.
Introduction: The process of cerebral vessels maintaining cerebral blood flow (CBF) fairly constant over a wide range of arterial blood pressure is referred to as cerebral autoregulation (CA). Cerebrovascular reactivity is the mechanism behind this process, which maintains CBF through constriction and dilation of cerebral vessels. Traditionally CA has been assessed statistically, limited by large, immobile, and costly neuroimaging platforms. However, with recent technology advancement, dynamic autoregulation assessment is able to provide more detailed information on the evolution of CA over long periods of time with continuous assessment. Yet, to date, such continuous assessments have been hampered by low temporal and spatial resolution systems, that are typically reliant on invasive point estimations of pulsatile CBF or cerebral blood volume using commercially available technology.Methods: Using a combination of multi-channel functional near-infrared spectroscopy and non-invasive arterial blood pressure devices, we were able to create a system that visualizes CA metrics by converting them to heat maps drawn on a template of human brain.Results: The custom Python heat map module works in offline mode to visually portray the CA index per channel with the use of colourmap. The module was tested on two different mapping grids, 8 channel and 24 channel, using data from two separate recordings and the Python heat map module was able read the CA indices file and represent the data visually at a preselected rate of 10 s.Conclusion: The generation of the heat maps are entirely non-invasive, with high temporal and spatial resolution by leveraging the recent advances in NIRS technology along with niABP. The CA mapping system is in its initial stage and development plans are ready to transform it from offline to real-time heat map generation.

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