2.1.0 Confluence Assay

Application Name

Confluence Assay

Version

2.1.0

Documentation Version

23.02.2024 - 1

Input Image(s)

2D (standard and/or WSI) / Time Series / z-Stack / Multichannel Images; RGB or Grayscale (8-bit, 16-bit)

Input Parameter(s)

Regions of interest (optional)

Keywords

confluence, in-vitro, cell growth, growth rate, regeneration, proliferation, migration, microscopy

Short Description

Detection and measurement of the percentage of the analysed image covered by adherent cells. Cell confluence is important for determining timings for splitting and harvesting cells.

References / Literature

For more information regarding cell confluency check e.g. Confluency or

Cell Confluency: Why It Matters and 3 Easy Methods

Table of contents

IKOSA Prisma Confluence 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 in the list of available applications, please contact your organization's administrator or our team at support@ikosa.ai.

Application description

This application automatically measures the percentage of the analysed image covered by a monolayer of adherent cells. In addition to the percentage area covered with cells, areas that are not covered with cells are quantified. A ratio of each area (covered and uncovered) compared to the overall image size is also calculated. The application supports images from phase contrast and brightfield microscopy and arbitrary cell types. This analysis can also be performed on time lapse recordings (time series) to study directional cell migration in vitro, z-stacks, or multichannel images.

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.

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)

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 formats

File formats

3 (RGB)

or

1 (Gray)

8 Bit

or

16 Bit

WSI formats: arbitrary

Standard images: max. 25,000 x 25,000

typically: 0.3-1.16

Image content

Microscopy (phase contrast or brightfield) image of a cell monolayer showing adherent cells, typically taken with 10x magnification.

*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 the analysis results for the input image or all inclusion ROIs.

2

jpg

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

results_vis/t<time-step>_z<z-layer>_c<channel>.jpg (for time series, z-stack, or multichannel image, no ROI), or

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

results_vis/t<time-step>_z<z-layer>_c<channel>_<roi-id>.jpg (for time series, z-stack, or multichannel image, ROI <roi-id>):

A visualization of the analysis result for a specific time step (of a time series), z-layer (of a z-stack), or channel (of a multichannel image) for either the whole image (if no inclusion ROIs selected for analysis) or each individual inclusion ROI.

Description for visualizations:

  • Areas and contours

    • no color: cell free (uncovered) area

    • green: adherent cells and cell-covered area

Confluence Assay App output visualisation
Confluence Assay App input file visualisation

 

Reference: Zaritsky A; Natan S; Kaplan D; Ben-Jacob E; Tsarfaty I (2015): Supplemental materials for "Live time-lapse dataset of in vitro wound healing experiments." GigaScience Database. http://dx.doi.org/10.5524/100118

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

3

json

annotation_results.json:

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

4

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.

5

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.

6

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

If one or more time steps (of a time series), z-layers (of a z-stack), or channels (of a multichannel image) were specified, the results in a specific row refer to the time step/z-layer/channel specified in the corresponding column.

If one or more ROIs were specified, the results in a specific row refer to the ROI specified in the corresponding columns, otherwise (empty ROI columns) the results refer to the whole image.

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

cells_covered_area [Px^2]

1011878

0 - #of pixels in image

Total area with adherent cells in Pixel^2, includes cell-covered area and free/floating cells).

8

cells_covered_area_ratio [%]

68.6

0 - 100

Ratio of total area with adherent cells to the total area of the image/ROI.

9

uncovered_area [Px^2]

36698

0 - #of pixels in image

Total cell-free area in Pixel^2.

10

uncovered_area_ratio [%]

31.4

0 - 100

Ratio of the cell-free area to total area of image/ROI.

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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