Development of a multi-exposure speckle imaging for mice brain imaging

Haleh Soleimanzad; Hirac Gurden; Frédéric Pain

doi:10.1117/12.2255816

Abstract

In the last decade, Laser Speckle Contrast Imaging (LSCI) has been proposed and validated for imaging cerebral blood flow at the rodent brain surface in vivo. The technique relies on the calculation of the spatial speckle contrast, which is related to the velocity of scatterers (red blood cells). The implementation of the technique requires a partial craniotomy so that the brain tissues of interest can be illuminated with a laser diode. However, the studies of changes in the microcirculation during disease progression or treatment require longitudinal studies (i.e. imaging is done repeatedly over weeks or even months). Practically, the less invasive way to obtain such data is to image through the thinned skull without a craniotomy. However the presence of static scatterers (skull) will affect the speckle calculation and produce a bias in the estimation of the microcirculation changes. An extension to LSCI, termed Multi-Exposure Speckle Imaging (MESI) was proposed and validated a few years ago that address these limitations. It relies on a model of the speckle contrast as a function of the exposure time and the proportion of static scatterers. Here, we used MESI with the aim of repeatedly imaging the olfactory bulb of mice models of obesity. First, we have developed a MESI set up which was characterized on microfluidic flow phantoms with different flow-rates and channel diameters to simulate blood flow in animal model characteristics. Second, we show that MESI can discriminate flows in the presence of static scatterers and it can measure flow changes consistently. Finally we provide an in vivo validation of the technique in mice with and without a craniotomy.

Conference Presentation

Citation Download Citation

Haleh Soleimanzad, Haleh Soleimanzad, Hirac Gurden, Hirac Gurden, Frédéric Pain, Frédéric Pain, "Development of a multi-exposure speckle imaging for mice brain imaging", Proc. SPIE 10051, Neural Imaging and Sensing, 1005110 (8 February 2017); doi: 10.1117/12.2255816; https://doi.org/10.1117/12.2255816

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