3D quantification of zebrafish cerebrovascular architecture by automated image analysis of light sheet fluorescence microscopy datasets

Abstract

Zebrafish transgenic lines and light sheet fluorescence microscopy allow in-depth insights into vascular development in vivo and 3D. However, robust quantification of the zebrafish cerebral vasculature in 3D remains a challenge, and would be essential to describe the vascular architecture. Here, we report an image analysis pipeline that allows 3D quantification of the total or regional zebrafish brain vasculature. This is achieved by landmark- or object-based inter-sample registration and extraction of quantitative parameters including vascular volume, surface area, density, branching points, length, radius, and complexity. Application of our analysis pipeline to a range of sixteen genetic or pharmacological manipulations shows that our quantification approach is robust, allows extraction of biologically relevant information, and provides novel insights into vascular biology. To allow dissemination, the code for quantification, a graphical user interface, and workflow documentation are provided. Together, we present the first 3D quantification approach to assess the whole 3D cerebrovascular architecture in zebrafish.

GliaMorph: A modular image analysis toolkit to quantify Müller glial cell morphology

“…Euclidean Distance Maps ( EDMn ) of object voxel distance to the nearest background voxel were produced from binary segmented images using the Fiji plugin “Distance Map 3D”, which calculates distance in three-dimensional Euclidean space ( Eq.10 ; Process > Binary > Distance Map in 3D [76]). To quantify thickness ( TN ), EDMs were multiplied with extracted skeletons, resulting in a 1D representation of vessel radii as represented by intensity of voxels (see [77]).…”

Cerebrovascular development: mechanisms and experimental approaches

“…To establish such predictive models, descriptive models are often required first to enable the establishment of boundary conditions. As such, (bio)medical image analysis and cerebrovascular quantification tools are not only essential to understand vascular biology, but also to allow such modelling approaches [ 53 – 56 ]. These models are complemented by an increasing data availability and analysis on single-cell transcriptomics, cellular diversity, cross-species diversity as well as regional specializations [ 4 , 57 – 59 ].…”