Q-VAT: Quantitative Vascular Analysis Tool

As our imaging capability increase, so does our need for appropriate image quantification tools. Quantitative Vascular Analysis Tool (Q-VAT) is an open-source software, written for Fiji (ImageJ), that perform automated analysis and quantification on large two-dimensional images of whole tissue sections. Importantly, it allows separation of the vessel measurement based on diameter, allowing the macro- and microvasculature to be quantified separately. To enable analysis of entire tissue sections on regular laboratory computers, the vascular network of large samples is analyzed in a tile-wise manner, significantly reducing labor and bypassing several limitations related to manual quantification. Double or triple-stained slides can be analyzed, with a quantification of the percentage of vessels where the staining's overlap. To demonstrate the versatility, we applied Q-VAT to obtain morphological read-outs of the vasculature network in microscopy images of whole-mount immuno-stained sections of various mouse tissues.


Online repository
Source code for the Q-VAT (Fiji) ImageJ and is available for download, together with more a more detailed user guide on https://github.com/bramcal/Q-VAT.git.

Supplementary Figures
Supplementary Figure 1. Overview of the Q-VAT masking tool for pre-processing. (A) User interface and input parameters of the Q-VAT masking tool. Through this interface the user selects the input directory containing the data to be pre-processed, the spatial calibration (µm/pixel) and various input parameters: the radius of the biggest object (µm), tissue mask particle size lower range (µm²), radius for median filtering (µm), area of the small particles that should be removed from the vascular mask (µm²) and the thresholding method (Default, Huang or Otsu). The user can choose whether or not to save a validation image. (B) Schematic diagram showing the ImageJ commands performed by the Q-VAT masking tool to automatically create a vascular mask and tissue mask.

Supplementary Figure 2.
Example of the co-staining functionality, which allows the user to add one or two co-stainings and calculate co-staining ratios. Original fluorescence microscopy of all vessels in the tissue (1:1000, L32470), the perfused vessels using an injection of Biotinylated Lycopersicon esculentum Lectin (B-1175) and the merged image (Top). Vascular mask obtained using the Q-VAT masking tool for each channel (Bottom).
Supplementary Figure 3. Dataset of randomly selected tiles used for evaluating the performance of the automated segmentation. The first column shows the original fluorescence images, while the second column displays the manual segmentation results used as an approximation of the ground truth. The manual segmentation images were compared to the automated segmentation obtained using the different methods for vascular feature quantification. Automated segmentation results using Q-VAT, AngioTool, and REAVER are shown in the third, fourth, and fifth columns, respectively.

Supplementary Figure 4.
Comparison of the morphological read-outs without (uncorrected) and with (corrected) the addition of small hole filling and pruning of small protrusions in the vasculature for (A) cluster density (#/mm²), (B) vascular density (%), (C) branch density (#/mm²) and (D) endpoint density (#/mm²). Values are presented as mean absolute error ± SEM. Two-way tailed t-test were used for group-wise comparisons, and statistical significance was determined at p<0.05. were considered statistically significant.

Supplementary Tables
Supplementary Table 1. Input parameters Q-VAT masking tool.

Input Parameter Values
Brain Heart Liver Retina Morphological read-out Description

Mean vessel diameter (µm)
Average of the mean vessel diameter of all branches in the tile

Vascular density (%)
Area within the tissue that is covered by vasculature Vessel length density (mm/mm²) Total vessel length within the tile normalized by the tissue area

Mean branch length (µm)
Average of the mean branch length within the tile

Tortuosity index
Average arc-chord ratio (i.e. ratio between the branch length and the Euclidian distance)