1.0.0 TEM Myocardium Assay

 

Application Name

TEM Myocardium Assay

Version

1.0.0

Documentation Version

15.03.2020 - 1

Input Image(s)

2D (standard); RGB and grayscale, 8 bit or 16 bit.

RGB images are automatically converted to grayscale images.

Input Parameter(s)

None

Keywords

cardiovascular, ex-vivo, myocardium, organelle, mitochondria, lipid droplet, sarcomere, z-stripe, microscopy, transmission electron microscopy, tem

Short Description

Segmentation of mitochondria, lipid droplets, sarcomere, and z-stripes in myocardial tissue sections imaged by transmission electron microscopy.

References / Literature

Reference laboratory: Core Facility Ultrastructure Analysis Graz: Dr. Dagmar Kolb.

Table of contents

IKOSA Prisma TEM Myocardium 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@kmlvision.com.

Application description

This application automatically segments and measures different types of structures (mitochondria, lipid droplets, sarcomere, z-stripes) in myocardial tissue sections imaged by transmission electron microscopy. The application was developed and tested with images of myocardial tissue sections of mice.

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://www.kmlvision.com/wp-content/uploads/2020/07/kmlvision-ikosa-sample-images-for-tem-myocardium-assay.zip

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)

 

Check image formats

3 (RGB)

1 (Grayscale)

 

RGB images are automatically converted to grayscale images

8 Bit

or

16 Bit

Min: 512 x 512

Max: 6144 x 6144

typically: 3-6

Image content

Transmission electron microscopy image of myocardial tissue section.

Additional requirements

Before imaging, the sample is embedded in synthetic resin, then sliced into ultra-thin sections of approximately 70 nm. Platin blue and lead citrate are used for contrasting.

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.

Description of output files and their content

Files

File format

Description

File format

Description

1

csv

results.csv

A csv file containing global analysis results for the input image.

2

jpg

results_visualization.jpg

A visualization of the analysis:

  • lipid droplets are shown in blue,

  • mitochondria are shown in red,

  • sarcomeres are shown in green

  • z-stripes are shown in purple

    • the lengths that were used to measure the z-stripe distances are shown as green lines

  • the numbers written within each detected object show the ID of each object. The same IDs are used within the different CSV files.

Results visualization
Input image

Reference: Dr. Dagmar Kolb, Core Facility Ultrastructure Analysis, Medical University of Graz

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

3

csv

results_01_lipid_droplets.csv

lipid droplet results

4

csv

results_02_mitochondria.csv

mitochondria results

5

csv

results_03_sarcomeres.csv

sarcomere results

6

csv

results_04_zstripes.csv

z-stripe results

Content

results.csv

Single csv-file

Column NO.

Column name

Examples

Value range

Description

Column NO.

Column name

Examples

Value range

Description

1

Lipid Droplets - count

5

0 -

number of lipid droplets

2

Lipid Droplets - total area [Px^2]

5432

0 -

total area covered by lipid droplets in Pixel^2

3

Lipid Droplets - total area [%]

2.523

0 - 100

total area covered by lipid droplets in % of image size

4

Lipid Droplets - completely within image - count

4

0 -

number of lipid droplets that are completely within the image (i.e. instances that do not touch the image borders)

5

Lipid Droplets - completely within image - total area [Px^2]

1321

0 - 

total area covered by lipid droplets that are completely within the image (i.e. instances that do not touch the image borders) in Pixel^2

6

Lipid Droplets - completely within image - total area [%]

1.245

0 - 100

total area covered by lipid droplets that are completely within the image (i.e. instances that do not touch the image borders) in % of image size

7

Mitochondria - count

5

0 -

number of mitochondria

8

Mitochondria - total area [Px^2]

5432

0 -

total area covered by mitochondria in Pixel^2

9

Mitochondria - total area [%]

2.523

0 - 100

total area covered by mitochondria in % of image size

10

Mitochondria - completely within image - count

4

0 -

number of mitochondria that are completely within the image (i.e. instances that do not touch the image borders)

11

Mitochondria - completely within image - total area [Px^2]

1321

0 - 

total area covered by mitochondria that are completely within the image (i.e. instances that do not touch the image borders) in Pixel^2

12

Mitochondria - completely within image - total area [%]

1.245

0 - 100

total area covered by mitochondria that are completely within the image (i.e. instances that do not touch the image borders) in % of image size

13

Sarcomeres - count

5

0 -

number of sarcomeres

14

Sarcomeres - total area [Px^2]

5432

0 -

total area covered by sarcomeres in Pixel^2

15

Sarcomeres - total area [%]

2.523

0 - 100

total area covered by sarcomeres in % of image size

16

Sarcomeres - completely within image - count

4

0 -

number of sarcomeres that are completely within the image (i.e. instances that do not touch the image borders)

17

Sarcomeres - completely within image - total area [Px^2]

1321

0 - 

total area covered by sarcomeres that are completely within the image (i.e. instances that do not touch the image borders) in Pixel^2

18

Sarcomeres - completely within image - total area [%]

1.245

0 - 100

total area covered by sarcomeres that are completely within the image (i.e. instances that do not touch the image borders) in % of image size

19

Z-Stripes - count

5

0 -

number of Z-Stripes

20

Z-Stripes - total area [Px^2]

5432

0 -

total area covered by Z-Stripes in Pixel^2

21

Z-Stripes - total area [%]

2.523

0 - 100

total area covered by sarcomeres in % of image size

22

Z-Stripes - completely within image - count

4

0 -

number of Z-Stripes that are completely within the image (i.e. instances that do not touch the image borders)

23

Z-Stripes - completely within image - total area [Px^2]

1321

0 - 

total area covered by Z-Stripes that are completely within the image (i.e. instances that do not touch the image borders) in Pixel^2

24

Z-Stripes - completely within image - total area [%]

1.245

0 - 100

total area covered by Z-Stripes that are completely within the image (i.e. instances that do not touch the image borders) in % of image size

25

Z-Stripes - mean distance [Px]

327.0

0 -

Mean distance between Z-Stripes (i.e. the mean length of sarcomeres) in Pixels. This parameter is only estimated in transverse muscle sections.

The distance between Z-stripes is estimated by finding  Z-stripes that are parallel (+/- 30°)

results_01_lipid_droplets.csv

Single csv-file

Column NO.

Column name

Examples

Value range

Description

Column NO.

Column name

Examples

Value range

Description

1

id

1, 2, 3, ...

1 -

id of each lipid droplet

2

area [Px^2]

1532

1 -

area of each lipid droplet in Pixel^2

3

area [%]

1.95

0 -

area of each lipid droplet in % of image size

4

completely within image

yes

{yes, no}

yes if the lipid droplet is completely within the image (i.e. the lipid droplet does not touch the border), otherwise no.

results_02_mitochondria.csv

Single csv-file

Column NO.

Column name

Examples

Value range

Description

Column NO.

Column name

Examples

Value range

Description

1

id

1, 2, 3, ...

1 -

id of each mitochondria

2

area [Px^2]

1532

1 -

area of each mitochondria in Pixel^2

3

area [%]

1.95

0 -

area of each mitochondria in % of image size

4

completely within image

yes

{yes, no}

yes if the mitochondria is completely within the image (i.e. the mitochondria does not touch the border), otherwise no.

results_03_sarcomeres.csv

Single csv-file

Column NO.

Column name

Examples

Value range

Description

Column NO.

Column name

Examples

Value range

Description

1

id

1, 2, 3, ...

1 -

id of each sarcomere

2

area [Px^2]

1532

1 -

area of each sarcomere in Pixel^2

3

area [%]

1.95

0 -

area of each sarcomere in % of image size

4

completely within image

yes

{yes, no}

yes if the sarcomere is completely within the image (i.e. the sarcomere does not touch the border), otherwise no.

results_04_zstripes.csv

Single csv-file

Column NO.

Column name

Examples

Value range

Description

Column NO.

Column name

Examples

Value range

Description

1

id

1, 2, 3, ...

1 -

id of each z-stripe

2

area [Px^2]

1532

1 -

area of each z-stripe in Pixel^2

3

area [%]

1.95

0 -

area of each z-stripe in % of image size

4

completely within image

yes

{yes, no}

yes if the z-stripe is completely within the image (i.e. the z-stripe does not touch the border), otherwise no.

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@kmlvision.com.

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

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

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