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Modified Beer-Lambert algorithm to measure pulsatile blood flow, critical closing pressure, and intracranial hypertension.

Wesley Boehs BakerRodrigo Menezes FortiPascal HeyeKristina HeyeJennifer M LynchArjun G YodhDaniel J LichtBrian R WhiteMisun HwangTiffany S KoTodd J Kilbaugh
Published in: Biomedical optics express (2024)
We introduce a frequency-domain modified Beer-Lambert algorithm for diffuse correlation spectroscopy to non-invasively measure flow pulsatility and thus critical closing pressure (CrCP). Using the same optical measurements, CrCP was obtained with the new algorithm and with traditional nonlinear diffusion fitting. Results were compared to invasive determination of intracranial pressure (ICP) in piglets (n = 18). The new algorithm better predicted ICP elevations; the area under curve (AUC) from logistic regression analysis was 0.85 for ICP ≥ 20 mmHg. The corresponding AUC for traditional analysis was 0.60. Improved diagnostic performance likely results from better filtering of extra-cerebral tissue contamination and measurement noise.
Keyphrases
  • machine learning
  • blood flow
  • deep learning
  • blood pressure
  • high resolution
  • neural network
  • air pollution
  • single molecule
  • low grade
  • drinking water
  • high speed
  • high grade
  • brain injury
  • human health
  • arterial hypertension