Quantification of cerebral blood flow in adults by contrast-enhanced near-infrared spectroscopy: Validation against MRI

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  • Daniel Milej
    Department of Medical Biophysics, Western University, London, ON, Canada
  • Lian He
    Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA
  • Androu Abdalmalak
    Department of Medical Biophysics, Western University, London, ON, Canada
  • Wesley B Baker
    Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
  • Udunna C Anazodo
    Department of Medical Biophysics, Western University, London, ON, Canada
  • Mamadou Diop
    Department of Medical Biophysics, Western University, London, ON, Canada
  • Sudipto Dolui
    Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
  • Venkaiah C Kavuri
    Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA
  • William Pavlosky
    Imaging Division, Lawson Health Research Institute, London, ON, Canada
  • Lin Wang
    Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA
  • Ramani Balu
    Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
  • John A Detre
    Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
  • Olivia Amendolia
    Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA
  • Francis Quattrone
    Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA
  • W Andrew Kofke
    Department of Anesthesiology and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
  • Arjun G Yodh
    Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA
  • Keith St Lawrence
    Department of Medical Biophysics, Western University, London, ON, Canada

Description

<jats:p> The purpose of this study was to assess the accuracy of absolute cerebral blood flow (CBF) measurements obtained by dynamic contrast-enhanced (DCE) near-infrared spectroscopy (NIRS) using indocyanine green as a perfusion contrast agent. For validation, CBF was measured independently using the MRI perfusion method arterial spin labeling (ASL). Data were acquired at two sites and under two flow conditions (normocapnia and hypercapnia). Depth sensitivity was enhanced using time-resolved detection, which was demonstrated in a separate set of experiments using a tourniquet to temporally impede scalp blood flow. A strong correlation between CBF measurements from ASL and DCE-NIRS was observed (slope = 0.99 ± 0.08, y-intercept = −1.7 ± 7.4 mL/100 g/min, and R<jats:sup>2</jats:sup> = 0.88). Mean difference between the two techniques was 1.9 mL/100 g/min (95% confidence interval ranged from −15 to 19 mL/100g/min and the mean ASL CBF was 75.4 mL/100 g/min). Error analysis showed that structural information and baseline absorption coefficient were needed for optimal CBF reconstruction with DCE-NIRS. This study demonstrated that DCE-NIRS is sensitive to blood flow in the adult brain and can provide accurate CBF measurements with the appropriate modeling techniques. </jats:p>

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