2.2.0 Network Formation Assay Application Documentation

 

Application Name

Network Formation Assay

Version

2.2.0

Documentation Version

19.12.2023 - 1

Input Image(s)

2D (standard and/or WSI) / Time Series / z-Stack / Multichannel Images; RGB or Grayscale (8 bit)

Input Parameter(s)

Regions of interest (optional)

Keywords

network, tube, formation, in-vitro, angiogenesis, vessel, growth, microscopy, matrigel

Short Description

Detection of branching points, loops, and cell coverage in network formation assay used for in-vitro angiogenesis research.

References / Literature

For more information regarding the assay check e.g. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3230200/;

Reference laboratory: Department of Obstetrics and Gynecology: Dr. Ursula Hiden; Jasmin Strutz, MSc;

Table of contents

IKOSA Prisma Network Formation Assay

You can use this image analysis application or any of our other applications in your account on the IKOSA platform. If it is not on the list of available applications, please contact your organization's administrator or our team at support@ikosa.ai.

Application description

This application automatically segments the network created by cells in a 2D network (tube) formation assay, typically on an extracellular matrix such as provided as the growth-factor reduced Matrigel® assay, and extracts relevant measures (loops, branching points, covered area).

In the following sections, we provide the necessary input data requirements that are necessary to obtain accurate image analysis results and a description of the output files.

Sample data

To try out this application, sample images can be downloaded here: https://drive.google.com/open?id=1WnUnZr4gbXp6-vpEvPfIa8yBgW_Ko3-P.

Input data requirements

Input image(s)

Input for this application is the following image data:

Image type

Color channels

Color depth (per channel)

Size (px)

Resolution (μm/px)

*Please note: Z-stack images cannot be uploaded into IKOSA but still can be analyzed via IKOSA Prisma API.

Important:

For all images, the following requirements apply:

  • The illumination must be constant throughout the image(s).

  • The sample must be in focus, i.e. no blurry regions in image(s).

Input parameter(s)

No additional input parameters are required for this application.

As an optional parameter, a single or multiple regions of interest (ROIs) can be defined in which the analysis should be performed (‘inclusion ROIs’).

Description of output files and their content

Files

File format

Description

File format

Description

1

csv

results.csv:

A csv file containing statistics about input image.

2

csv

results_01_loops.csv:

A csv file containing statistics about detected loops.

3

jpg

results_vis/vis.jpg (2D image, no ROI), or

results_vis/t<time-step>.jpg (time step <time-step> of time series, no ROI), or

results_vis/<roi-id>.jpg (2D image, ROI <roi-id>), or

results_vis/t<time-step>_<roi-id>.jpg (time step <time-step> of time series, ROI <roi-id>):

A visualization of the analysis result for a specific time step for either the whole image (if no inclusion ROIs selected for analysis) or each individual inclusion ROI:

  • Branching points are visualized as green circles.

  • The area covered by cells is shown in red.

  • The loops are visualized using different colors and labelled with L followed by the loop id. The loop id corresponds to the id in results_01_loops.csv.

Results visualization
Input image

Reference: Dr. Ursula Hiden, Department of Obstetrics and Gynecology, Medical University of Graz; Jasmin Strutz, MSc, Department of Obstetrics and Gynecology, Medical University of Graz

Please note: These files are only created if qualitative result visualization was requested when submitting the analysis job.

4

json

annotation_results.json:

JSON file containing segmented cells. The position is measured from the left upper corner (1,1) of the image.

5

json

roiMeta.json:

A json file containing all information regarding the ROIs defined for the analysis job to ensure reproducibility. Also, information regarding image and analysis dimensions is provided.

6

jpg

rois_visualization.jpg, or

t<time-step>_z<z-layer>_c<channel>_rois_visualization.jpg:

An overview visualization to show locations of all analyzed ROIs for the 2D image or time step <time-step> of a time series, z-layer <z-layer> of a z-stack, or channel <channel> of a multichannel image.

7

json

jobResultBundleMeta.json:

A json file containing all information regarding the analysis job (application name and version, project, etc.) to ensure reproducibility.

Content

results.csv

Single csv-file

Column NO.

Column name

Examples

Value range

Description

Column NO.

Column name

Examples

Value range

Description

1

t

3

1 - 

Time step, i.e. the position of the image in the time series.

2

z

5

1 - 

z-layer, i.e. the position of the layer in the z-stack.

3

c

2

1 - 

Channel, i.e. the position of the channel in the multichannel image.

4

roi_id

ROI-03

ROI-01 - 

<roi-id> starting from “ROI-01”. Empty, if no inclusion ROI is specified and the whole image was analyzed.

5

roi_name

“central”

text

Custom text to identify the ROI. Empty, if no inclusion ROI is specified and the whole image was analyzed.

6

roi_size [Px^2]

1212212

1 -

Size of the ROI that was analyzed in pixels^2. The size of the whole image is given if no inclusion ROI is specified and the whole image was analyzed.

7

branching points

104

0 -

Number of detected branching points.

8

covered area [Px^2]

93869

0 - # of pixels in image

Total area covered by cells or tubes in pixels.

9

num_tubes

190

0 -

Number of tubes detected.

10

total_tube_length [Px]

6641.4

0 - # of pixels in image

Total length of all tubes in pixels.

11

average_tube_length [Px]

34.95

0 - # of pixels in image

Average length of detected tubes in pixels.

results_01_loops.csv

Single csv-file

Column NO.

Column name

Examples

Value range

Description

Column NO.

Column name

Examples

Value range

Description

1

t

3

1 - 

Time step, i.e. the position of the image in the time series.

2

z

5

1 - 

z-layer, i.e. the position of the layer in the z-stack.

3

c

2

1 - 

Channel, i.e. the position of the channel in the multichannel image.

4

roi_id

ROI-03

ROI-01 - 

<roi-id> starting from “ROI-01”. Empty, if no inclusion ROI is specified and the whole image was analyzed.

5

roi_name

“central”

text

Custom text to identify the ROI. Empty, if no inclusion ROI is specified and the whole image was analyzed.

6

roi_size [Px^2]

1212212

1 -

Size of the ROI that was analyzed in pixels^2. The size of the whole image is given if no inclusion ROI is specified and the whole image was analyzed.

7

object_id

1

1 -

Loop id.

8

area [Px^2]

10747

201 - # of pixels in image

Area of the loop in pixels.

9

perimeter [Px]

452.3

0 -

Perimeter of loop in pixels.

Error information

More information about errors can be found in the Application Error Documentation.

Contact

If you have any questions about this app, as well as suggestions or ideas for new ones, email us at support@ikosa.ai.

Feel free to book a 30-minute meeting to speak with us about IKOSA and the apps!

https://calendly.com/kolaido/book-the-ikosa-platform-demo

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