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Cerebral Blood Flow Monitored During Circulatory Shock Using Hemodynamic Trend Indices: A Diffuse Correlation Spectroscopy Study
Journal article - Includes Student Work   Open access   Peer reviewed

Cerebral Blood Flow Monitored During Circulatory Shock Using Hemodynamic Trend Indices: A Diffuse Correlation Spectroscopy Study

Randolph Sinahon, Luis M Gomero, Meltem Izzetoglu, Patricia A Shewokis, Shadi N Malaeb and Kurtulus Izzetoglu
Computer methods and programs in biomedicine, v 288, Forthcoming
Jan 2027
DOI: https://doi.org/10.1016/j.cmpb.2026.109675
PMID: 42849372
Featured in Collection :   Drexel's Newest Publications
url
https://doi.org/10.1016/j.cmpb.2026.109675View
Published, Version of Record (VoR) Open Access via Drexel Libraries Read and Publish Program 2026 Open CC BY V4.0

Abstract

Cerebral blood flow Diffuse correlation spectroscopy Hemodynamic trend indices Hemorrhagic shock Hypoxia
Background and Objective Reliable detection and monitoring of circulatory shock is critical to provide timely and effective treatments. Specifically, continuous cerebral hemodynamic monitoring is essential as cerebral tissues are vulnerable to hypoxic-ischemic conditions. Diffuse correlation spectroscopy (DCS) is a non-invasive optical technique that measures cerebral blood flow (CBF) in microvasculature by calculating a cerebral blood flow index (BFI). Current CBF monitoring by DCS commonly relies on BFI magnitude changes or changes relative to a baseline (rBFI) of optical signals. However, BFI and rBFI are often confounded by robust compensatory mechanisms meant to stabilize CBF, thereby masking potential early indicators of shock. To address this limitation, we applied a cumulative sum approach to develop BFI-derived Hemodynamic Trend Indices (HTIs), to selectively monitor dynamic trends in CBF leading to shock. Methods Newborn piglet models of controlled blood loss (BL) and hypoxia were selected to investigate BFI, rBFI, and HTIs response to shock. Ascending and descending HTIs (aHTI and dHTI) were calculated from two-sided cumulative sum of BFI slopes. Machine learning and statistical models evaluated these biomarkers’ shock detection performance and sensitivity to insult progression. Results In hemorrhage and hypoxia groups, HTIs diverged from baseline at earlier insult epochs; HTIs at 10% BL (Hedges’ g = -0.85, 1.13) versus BFI at 50% BL, and after only ∼10-30 minutes of hypoxia, while BFI and rBFI declined after 40 minutes. In No-Shock vs. Shock classification, dHTI outperformed absolute BFI, achieving ∼0.90 accuracy and >0.8 F1-scores. Conclusion The proposed hemodynamic trend indices can monitor directional changes in CBF during insult progression towards shock, and may be further developed as potential clinical biomarkers for early indication of cerebral hemodynamic decompensation prior to circulatory collapse.

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