New Wavelet Neurovascular Bundle for Bedside Evaluation of Cerebral Autoregulation and Neurovascular Coupling in Newborns with Hypoxic-Ischemic Encephalopathy

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Abstract

Neonatal encephalopathy (NE) resulting from birth asphyxia constitutes a major global public health burden for millions of infants every year, and despite therapeutic hypothermia, half of these neonates have poor neurological outcomes. As new neuroprotective interventions are being studied in clinical trials, there is a critical need to establish physiological surrogate markers of therapeutic efficacy, to guide patient selection and/or to modify the therapeutic intervention. The challenge in the field of neonatal brain injury has been the difficulty of clinically discerning NE severity within the short therapeutic window after birth or of analyzing the dynamic aspects of the cerebral circulation in sick NE newborns. To address this roadblock, we have recently developed a new “wavelet neurovascular bundle” analytical system that can measure cerebral autoregulation (CA) and neurovascular coupling (NVC) at multiple time scales under dynamic, nonstationary clinical conditions. This wavelet analysis may allow noninvasive quantification at the bedside of (1) CA (combining metrics of blood pressure and cerebral near-infrared spectroscopy, NIRS) and (2) NVC (combining metrics obtained from NIRS and EEG) in newborns with encephalopathy without mathematical assumptions of linear and stationary systems. In this concept paper, we present case examples of NE using the proposed physiological wavelet metrics of CA and NVC. The new approach, once validated in large NE studies, has the potential to optimize the selection of candidates for therapeutic decision-making, and the prediction of neurocognitive outcomes.

Original languageEnglish (US)
JournalDevelopmental Neuroscience
DOIs
StateAccepted/In press - Mar 30 2017

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Brain Hypoxia-Ischemia
Brain Diseases
Homeostasis
Newborn Infant
Near-Infrared Spectroscopy
Cerebrovascular Circulation
Parturition
Induced Hypothermia
Wavelet Analysis
Asphyxia
Therapeutics
Brain Injuries
Patient Selection
Neurovascular Coupling
Electroencephalography
Decision Making
Public Health
Biomarkers
Clinical Trials
Blood Pressure

Keywords

  • Amplitude-integrated electroencephalography
  • Hypothermia
  • Near-infrared spectroscopy
  • Neurovascular coupling

ASJC Scopus subject areas

  • Neurology
  • Developmental Neuroscience

Cite this

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abstract = "Neonatal encephalopathy (NE) resulting from birth asphyxia constitutes a major global public health burden for millions of infants every year, and despite therapeutic hypothermia, half of these neonates have poor neurological outcomes. As new neuroprotective interventions are being studied in clinical trials, there is a critical need to establish physiological surrogate markers of therapeutic efficacy, to guide patient selection and/or to modify the therapeutic intervention. The challenge in the field of neonatal brain injury has been the difficulty of clinically discerning NE severity within the short therapeutic window after birth or of analyzing the dynamic aspects of the cerebral circulation in sick NE newborns. To address this roadblock, we have recently developed a new “wavelet neurovascular bundle” analytical system that can measure cerebral autoregulation (CA) and neurovascular coupling (NVC) at multiple time scales under dynamic, nonstationary clinical conditions. This wavelet analysis may allow noninvasive quantification at the bedside of (1) CA (combining metrics of blood pressure and cerebral near-infrared spectroscopy, NIRS) and (2) NVC (combining metrics obtained from NIRS and EEG) in newborns with encephalopathy without mathematical assumptions of linear and stationary systems. In this concept paper, we present case examples of NE using the proposed physiological wavelet metrics of CA and NVC. The new approach, once validated in large NE studies, has the potential to optimize the selection of candidates for therapeutic decision-making, and the prediction of neurocognitive outcomes.",
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