Quantitative determination of maximal imaging depth in all-NIR multiphoton microscopy images of thick tissues

We report two methods for quantitatively determining maximal imaging depth from thick tissue images captured using all-near-infrared (NIR) multiphoton microscopy (MPM). All-NIR MPM is performed using 1550 nm laser excitation with NIR detection. This method enables imaging more than five-fold deep in thick tissues in comparison with other NIR excitation microscopy methods. In this study, we show a correlation between the multiphoton signal along the depth of tissue samples and the shape of the corresponding empirical probability density function (pdf) of the photon counts. Histograms from this analysis become increasingly symmetric with the imaging depth. This distribution transitions toward the background distribution at higher imaging depths. Inspired by these observations, we propose two independent methods based on which one can automatically determine maximal imaging depth in the all-NIR MPM images of thick tissues. At this point, the signal strength is expected to be weak and similar to the background. The first method suggests the maximal imaging depth corresponds to the deepest image plane where the ratio between the mean and median of the empirical photon-count pdf is outside the vicinity of 1. The second method suggests the maximal imaging depth corresponds to the deepest image plane where the squared distance between the empirical photon-count mean obtained from the object and the mean obtained from the background is greater than a threshold. We demonstrate the application of these methods in all-NIR MPM images of mouse kidney tissues to study maximal depth penetration in such tissues.