Cerebral blood flow imaging using time-series analysis of indocyanine green molecular dynamics in mice

Abstract

Measurement of cerebral perfusion is important for study of various brain disorders such as stroke, epilepsy, and vascular dementia; however, efficient and convenient methods which can provide quantitative information about cerebral blood flow are not developed. Here we propose an optical imaging method using time-series analysis of dynamics of indocyanine green (ICG) fluorescence to generate cerebral blood flow maps. In scalp-removed mice, ICG was injected intravenously, and 740nm LED light was illuminated for fluorescence emission signals around 820nm acquired by cooled-CCD. Time-lapse 2-dimensional images were analyzed by custom-built software, and the maximal time point of fluorescent influx in each pixel was processed as a blood flow-related parameter. The generated map exactly reflected the shape of the brain without any interference of the skull, the dura mater, and other soft tissues. This method may be further applicable for study of other disease models in which the cerebral hemodynamics is changed either acutely or chronically. © 2010 Copyright SPIE - The International Society for Optical Engineering.