Journal
BIOMEDICAL OPTICS EXPRESS
Volume 11, Issue 3, Pages 1462-1476Publisher
Optica Publishing Group
DOI: 10.1364/BOE.386612
Keywords
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Funding
- Center for Machine Learning and Health at Carnegie Mellon University
- American Heart Association [17SDG33700047]
- National Institutes of Health [R21-EB024675]
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Measuring intracranial pressure (ICP) is necessary for the treatment of severe head injury but measurement systems are highly invasive and introduce risk of infection and complications. We developed a non-invasive alternative for quantifying ICP using measurements of cerebral blood flow (CBF) by diffuse correlation spectroscopy. The recorded cardiac pulsation waveform in CBF undergoes morphological changes in response to ICP changes. We used the pulse shape to train a randomized regression forest to estimate the underlying ICP and demonstrate in five non-human primates that DCS-based estimation can explain over 90% of the variance in invasively measured ICP. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
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