2.0.0 Ki-67 Quantification Breast Cancer Application Documentation
- fanny.dobrenova (Unlicensed)
- Philipp Kainz
- Michael Mayrhofer-Reinhartshuber (Unlicensed)
- polina.vinogradova (Unlicensed)
Application Name | Ki-67 Quantification Breast Cancer |
|---|---|
Version | 2.0.0 |
Documentation Version | 15.03.2020 - 1 |
Input Image(s) | 2D (standard and/or WSI); RGB |
Input Parameter(s) | Regions of interest (optional) |
Keywords | pathology, ihc, ki67, ki-67, nuclei, microscopy, mamma, breast, tissue, detection, tumor, oncology, carcinoma |
Short Description | Detection of tumor cell nuclei in immunohistochemically (IHC) stained sections of human breast cancer. Counting of positively (brown) and negatively (blue) stained nuclei and calculation of positive/negative ratio. |
References / Literature | Reference department: Diagnostic and Research Institute of Pathology, Medical University of Graz, Dr.med.univ. Martin Asslaber |
Important: Research Use Only!
This application is not certified as a medical device and must not be used for diagnostic or therapeutic purposes.
Table of contents
IKOSA Prisma Ki-67 Quantification Breast Cancer
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 detects and counts tumor cell nuclei in immunohistochemically (IHC) stained sections of human breast cancer. Positively (brown) and negatively (blue) stained nuclei are counted separately. The ratio of the detected positively and negatively stained nuclei is calculated. The application was developed and tested with microscopy images of human tissue sections.
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) |
|---|---|---|---|---|
2D (standard and/or WSI)
Check image format File formats | 3 (RGB)
| 8 Bit | WSI formats: arbitrary Standard images: max. 25,000 x 25,000 | Typically: 0.3 - 0.5 |
Image content Microscopy image of IHC Ki-67 stained sample, typically taken with 20x magnification. Additional requirements
| ||||
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 global analysis results for the input image. |
| 2 | jpg | results_visualization.jpg: A visualization of the analysis:
 Please note: This file is only generated for standard images (not for Whole Slide Images). |
| 3 | json | annotation_results.json: JSON file containing positions of detected nuclei. 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. The file is empty if no ROIs were defined for analysis. |
| 5 | jpg | rois_visualization.jpg: An overview visualization to show locations of all analyzed ROIs for the 2D 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 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 |
|---|---|---|---|---|
1 | roi_id | ROI-03 | ROI-01 - | <roi-id> starting from “ROI1”. Empty, if no inclusion ROI is specified and the whole image was analyzed. |
2 | roi_name | “central” | text | Custom text to identify the ROI. Empty, if no inclusion ROI is specified and the whole image was analyzed. |
3 | nuclei count | 1232 | 0 - | Number of detected nuclei. |
4 | blue nuclei count | 386 | 0 - | Number of detected blue nuclei. |
5 | brown nuclei count | 846 | 0 - | Number of detected brown nuclei. |
6 | ratio brown/blue nuclei | 2.19 | 0 - inf | Number of brown nuclei divided by the number of blue nuclei. if blue=0 the result is "inf" (infinity). |
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!
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