Isolating specific cell and tissue compartments from 3D images for quantitative regional distribution analysis using novel computer algorithms.

Background: Isolating specific cellular and tissue compartments from 3D image stacks for quantitative distribution analysis is crucial for understanding cellular and tissue physiology under normal and pathological conditions. Current approaches are limited because they are designed to map the distributions of synapses onto the dendrites of stained neurons and/or require specific proprietary software packages for their implementation.
New Method: To overcome these obstacles, we developed algorithms to Grow and Shrink Volumes of Interest (GSVI) to isolate specific cellular and tissue compartments from 3D image stacks for quantitative analysis and incorporated these algorithms into a user-friendly computer program that is open source and downloadable at no cost.
Results: The GSVI algorithm was used to isolate perivascular regions in the cortex of live animals and cell membrane regions of stained spinal motoneurons in histological sections. We tracked the real-time, intravital biodistribution of injected fluorophores with sub-cellular resolution from the vascular lumen to the perivascular and parenchymal space following a vascular microlesion, and mapped the precise distributions of membrane-associated KCC2 and gephyrin immunolabeling in dendritic and somatic regions of spinal motoneurons.
Comparison With Existing Methods: Compared to existing approaches, the GSVI approach is specifically designed for isolating perivascular regions and membrane-associated regions for quantitative analysis, is user-friendly, and free.
Conclusions: The GSVI algorithm is useful to quantify regional differences of stained biomarkers (e.g., cell membrane-associated channels) in relation to cell functions, and the effects of therapeutic strategies on the redistributions of biomolecules, drugs, and cells in diseased or injured tissues.
(Copyright © 2014 Elsevier B.V. All rights reserved.)