Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

Application Name

Network Formation Assay

Version

3.0.0

Documentation Version

2903.1112.2024 - 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

Table of Contents
minLevel1
maxLevel7
excludeTable 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)

2D (standard and/or WSI),

Time Series,

Multichannel,

Z-stack*

Check image format File formats

1 (Greyscale)

3 (RGB)

8 Bit

Standard and WSI:
Max: 8200 x 8200

typically: 1.75

Image content

Microscopy image of 2D network (“tube”) formation assay, typically taken with 4x magnification.

Additional requirements: None

Info

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

Note

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

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

csv

results_02_tubes.csv:

A csv file containing statistics about detected tubes.

4

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 skeleton (centerline) of the tubular-structure is shown as a red line.

  • The area covered by cells is shown in red.a color representing its local thickness.
    The colormap for the thickness is displayed below:

    colormap_thickness_horizontal.pngImage Added
  • 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.

grafik-20241203-071642.pngImage Added

Image RemovedImage Removed

grafik-20241203-071739.pngImage Added

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

Info

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

Info

Please note: the image quality might be reduced for the presentation in the technical docs.

45

json

annotation_results.json:

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

56

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.

67

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.

Info

Please note: This file is only created, if inclusion ROIs were defined for analysis.

78

json

jobResultBundleMeta.json:

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

Info

Please note: This file is only included, if bundled or merged analysis jobs are downloaded.

Info

Please note:

  • In the case of inclusion ROIs that are partially outside of the image, the ROIs are cropped to the areas that lie inside the image.

  • In the case of inclusion ROIs that are completely outside of the image, no analysis is performed. However, they are still listed in corresponding results files.

  • A <roi-id> is generated automatically by the application corresponding to the creation date of a ROI. The location of a ROI within an image with its specific <roi-id> can be seen in the file “rois_visualization.jpg.” ROIs that are completely outside of the image are not shown in this file.

  • All visualizations are downscaled to 25 megapixels (MP), if the original image or inclusion ROI is larger than 25 MP.

  • Loops with an area ≤200 pixels are not detected.

Content

results.csv

Single csv-file

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.

It is calculated by taking the length of the skeleton, which is a simplified representation of its shape. The skeleton can be seen in the visualization.

11

average_tube_length [Px]

34.95

0 - # of pixels in image

Average length of detected tubes in pixels.

12

mean_tube_thickness [Px]

21.268

1-

Average thickness of detected tubes in pixels.

results_01_loops.csv

Single csv-file

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.

results_02_tubes.csv

Single csv-file that lists all tubes that were detected within the image.

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 -

tube id.

8

tube_thickness [Px]

5.1243

1-

Average thickness of the tube in pixels.

9

tube_type

1

0, 1, 2 or 3

Type of the tube:

0: endpoint-to-endpoint (isolated branch/tube)
1: junction-to-endpoint
2: junction-to-junction
3: isolated cycle

10

tube_length [Px]

452.3

1 -

Length of the tube in pixels.

It is calculated by taking the length of the skeleton, which is a simplified representation of its shape. The skeleton of each tube can be seen in the visualization.

Info

Please note: The parameters marked with an asterisk (*) are calculated using https://scikit-image.org/.

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