Quantifying cerebral blood flow in an adult pig ischemia model by a depth-resolved dynamic contrast-enhanced optical method

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Abstract

Dynamic contrast-enhanced (DCE) near-infrared (NIR) methods have been proposed for bedside monitoring of cerebral blood flow (CBF). These methods have primarily focused on qualitative approaches since scalp contamination hinders quantification. In this study, we demonstrate that accurate CBF measurements can be obtained by analyzing multi-distance time-resolved DCE data with a combined kinetic deconvolution optical reconstruction (KDOR) method. Multi-distance time-resolved DCE-NIR measurements were made in adult pigs (n = 8) during normocapnia, hypocapnia and ischemia. The KDOR method was used to calculate CBF from the DCE-NIR measurements. For validation, CBF was measured independently by CT under each condition. The mean CBF difference between the techniques was − 1.7 mL/100 g/min with 95% confidence intervals of − 16.3 and 12.9 mL/100 g/min; group regression analysis revealed a strong agreement between the two techniques (slope = 1.06 ± 0.08, y-intercept = − 4.37 ± 4.33 mL/100 g/min, p < 0.001). The results of an error analysis suggest that little a priori information is needed to recover CBF, due to the robustness of the analytical method and the ability of time-resolved NIR to directly characterize the optical properties of the extracerebral tissue (where model mismatch is deleterious). The findings of this study suggest that the DCE-NIR approach presented is a minimally invasive and portable means of determining absolute hemodynamics in neurocritical care patients.

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