Quantifying local heterogeneity of in vivo transport dynamics using stochastic scanning multiphoton multifocal microscopy and segmented spatiotemporal image correlation spectroscopy

Hee Y. Kim; Justin E. Jureller; Andrey Kuznetsov; Louis H. Philipson; Norbert F. Scherer

doi:10.1117/12.763300

15 February 2008 Quantifying local heterogeneity of in vivo transport dynamics using stochastic scanning multiphoton multifocal microscopy and segmented spatiotemporal image correlation spectroscopy

Hee Y. Kim, Justin E. Jureller, Andrey Kuznetsov, Louis H. Philipson, Norbert F. Scherer

Author Affiliations +

Proceedings Volume 6860, Multiphoton Microscopy in the Biomedical Sciences VIII; 686021 (2008) https://doi.org/10.1117/12.763300
Event: SPIE BiOS, 2008, San Jose, California, United States

Abstract

Elucidating the mechanisms of insulin granule trafficking in pancreatic β-cells is a critical step in understanding Type II Diabetes and abnormal insulin secretion. In this paper, rapid-sampling stochastic scanning multiphoton multifocal microscopy (SS-MMM) was developed to capture fast insulin granule dynamics in vivo. Stochastic scanning of (a diffractive optic generated) 10×10 hexagonal array of foci with a galvanometer yields a uniformly sampled image with fewer spatio-temporal artifacts than obtained by conventional or multibeam raster scanning. In addition, segmented spatio-temporal image correlation spectroscopy (Segmented STICS) was developed to extract dynamics of insulin granules from the image sequences. Measurements we conducted on MIN6 cells, which exhibit an order of magnitude lower granule number density, allow comparison of particle tracking with Segmented-STICS. Segmentation of the images into 8×8 pixel segments (similar to a size of one granule) allows some amount of spatial averaging, which can reduce the computation time required to calculate the correlation function, yet retains information about the local spatial heterogeneity of transport. This allows the correlation analysis to quantify the dynamics within each of the segments producing a "map" of the localized properties of the cell. The results obtained from Segmented STICS are compared with dynamics determined from particle tracking analysis of the same images. The resulting range of diffusion coefficients of insulin granules are comparable to previously published values indicating that SS-MMM and segmented- STICS will be useful to address the imaging challenges presented by β-cells, particularly the extremely large number density of granules.

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Hee Y. Kim, Justin E. Jureller, Andrey Kuznetsov, Louis H. Philipson, and Norbert F. Scherer "Quantifying local heterogeneity of in vivo transport dynamics using stochastic scanning multiphoton multifocal microscopy and segmented spatiotemporal image correlation spectroscopy", Proc. SPIE 6860, Multiphoton Microscopy in the Biomedical Sciences VIII, 686021 (15 February 2008); https://doi.org/10.1117/12.763300

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