This study evaluates 2-Photon fluorescence microscopy of in vivo and ex vivo cleared samples for visualizing cortical vasculature.
Four mice brains were imaged with in vivo 2PFM. Mice were then perfused with a FITC gel and cleared in fructose. The same regions imaged in vivo were imaged ex vivo. Vessels were segmented automatically in both images using an in-house developed algorithm that accounts for the anisotropic and spatially varying PSF ex vivo. Through non-linear warping, the ex vivo image and tracing were aligned to the in vivo image. The corresponding vessels were identified through a local search algorithm. This enabled comparison of identical vessels in vivo/ex vivo. A similar process was conducted on the in vivo tracing to determine the percentage of vessels perfused. Of all the vessels identified over the four brains in vivo, 98% were present ex vivo. There was a trend towards reduced vessel diameter ex vivo by 12.7%, and the shrinkage varied between specimens (0% to 26%). Large diameter surface vessels, through a process termed 'shadowing', attenuated in vivo signal from deeper cortical vessels by 40% at 300 μm below the cortical surface, which does not occur ex vivo.
In summary, though there is a mean diameter shrinkage ex vivo, ex vivo imaging has a reduced shadowing artifact. Additionally, since imaging depths are only limited by the working distance of the microscope objective, ex vivo imaging is more suitable for imaging large portions of the brain.
Micro-computed tomography (micro-CT) provides a means for obtaining a detailed three-dimensional description of the structure of micro-vasculature in whole organs. This whole organ description allows for the examination of flow models and self similarity relationships that would otherwise be inaccessible using conventional sampling based descriptions of the microvasculature. The number of vessels that compose the micro-vasculature in a whole organ is so large, however, that such analysis is only feasible using automated image processing techniques. In this paper, the segmentation and data representation challenges of such analysis are examined with reference to mouse kidney vasculature. A semi-automated analysis method is described and is applied to a set of mouse kidneys to assess the feasibility and reproducibility of population studies. This analysis includes a new method to separate parallel arterial and venous vessels that are distinct but touching at the resolution of the micro-CT scan. Also described is a new formalism for representing the derived vessel structure that lends itself to regularization. Distributions of arterial and venous structural parameter are presented for six kidneys (three of each) taken from age matched animals of the CD1 strain. These results show a high degree of similarity among specimens and suggest that population studies to examine the influence of subtle disease or genetic factors are feasible.
KEYWORDS: Monte Carlo methods, Collimators, Point spread functions, Single photon emission computed tomography, Medical imaging, Physics, Computer simulations, Analog electronics, Signal attenuation, Photon transport
Monte Carlo methods play an important role in medical imaging research. Direct analog Monte Carlo simulations can be very accurate but require considerable computational resources. Variance reduction techniques may offer a solution to this problem. In this paper we present a comparison of expected values of standard quantities of interest for SPECT using these two simulation methods. The effect of variance reduction on the statistical characteristics of the simulated data is also investigated.
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