{"id":3557,"date":"2025-04-14T10:59:04","date_gmt":"2025-04-14T08:59:04","guid":{"rendered":"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/?p=3557"},"modified":"2025-10-14T11:05:49","modified_gmt":"2025-10-14T09:05:49","slug":"high-content-imaging-with-mikaia","status":"publish","type":"post","link":"https:\/\/websites.fraunhofer.de\/smart-sensing-insights\/high-content-imaging-with-mikaia\/","title":{"rendered":"High Content Imaging: Analyzing Ex-Vivo Drug Response Assays with MIKAIA"},"content":{"rendered":"\n

Researchers at the Fraunhofer Institute for Toxicology and Experimental Medicine (ITEM) have developed PEDRA<\/strong>: Platform for Ex-Vivo Drug Response Assays<\/strong><\/a>. Up to 100 compounds are tested in parallel on primary patient-derived cells using High Content Imaging and further methods.<\/p>\n\n\n\n

\"visualization
Platform for Ex-vivo Drug Response Assays (PEDRA); this article focuses on generating the High Content Imaging readout with MIKAIA\u00ae (\u00a9 Fraunhofer ITEM, created with BioRender.com)<\/figcaption><\/figure>\n\n\n\n

The following video illustrates the image analysis conducted with MIKAIA\u00ae<\/sup>.<\/p>\n\n\n\n

High Content Image Analysis with MIKAIA\u00ae<\/sup><\/h2>\n\n\n\n

This video was created with MIKAIA\u00ae<\/sup> 2.3.0 and shows the analysis of a single well and subsequent batch-analysis of multiple-wells with MIKAIA\u00ae<\/sup>‘s FL Cell Analysis App<\/a>. Voice-over \/ speaker: Volker Bruns, Fraunhofer IIS.<\/p>\n\n\n\n

Panel & cell type mapping<\/h2>\n\n\n\n
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Each scan shows an individual well from a multi-well plate. The panel includes a tumor marker (EpCAM), an immune cell marker (CD45), and a viability marker. MIKAIA\u00ae<\/sup> detects all cells based on the DAPI channel, then measures the mean fluorescence intensity (MFI) per marker and cell. A cell’s type is determined by deciding which markers are expressed and then matching the combination to the configured cell type map.<\/p>\n<\/div>\n\n\n\n

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\"\"<\/figure>\n<\/div>\n<\/div>\n\n\n\n

Inspecting results — Gaining confidence in image analysis<\/h2>\n\n\n\n

After the analysis has run (ca. 15 seconds for one well), all nuclei are outlined. Cells are assigned to the types specified in the cell type map. <\/p>\n\n\n\n

The “cells (by marker)<\/strong>” group contains one annotation class per marker. Cells that express multiple markers yield multiple annotations and, therefore, these annotation classes should be viewed one at a time. They are convenient for inspecting and visualizing which cells express a particular marker. <\/p>\n\n\n\n

Conversely, the “cells (by co-expression)<\/strong>” group contains annotation classes per marker combination. Here, each cell is assigned to exactly one of these classes, allowing for simultaneous visualization of all classes. <\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

The video above shows how this analysis is rolled out to a larger dataset. All images are batch-analyzed and results are written to a folder along the way. From the set of output files, the summary CSV file is the most important output file. It contains the desired read-outs per well: cell abundances by type. From this, PEDRA will assess which compound most effectively kills tumor cells while leaving immune cells alive.<\/p>\n\n\n\n

Contacts for PEDRA — Platform for Ex-Vivo Drug Response Assays<\/h2>\n\n\n\n
\n
\n
\"\"<\/figure>\n\n\n\n

Lukas W\u00f6hrl<\/strong>
Product Owner &
PhD Candidate
Fraunhofer ITEM
Send email<\/a>
<\/p>\n<\/div>\n\n\n\n

\n
\"\"<\/figure>\n\n\n\n

Dr. Christian Werno<\/strong>
Head of Department of Molecular and Functional Assays
Fraunhofer ITEM
Send email<\/a><\/p>\n<\/div>\n\n\n\n

<\/div>\n<\/div>\n\n\n\n
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\"\"<\/figure>\n<\/div><\/div>\n\n\n\n
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This project is conducted in the context of
and receives funding by
Fraunhofer Cluster of Excellence <\/strong><\/a>
Immune-Mediated Diseases (CIMD)<\/strong><\/a><\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Researchers at the Fraunhofer Institute for Toxicology and Experimental Medicine (ITEM) have developed PEDRA: Platform for Ex-Vivo Drug Response Assays. Up to 100 compounds are tested in parallel on primary patient-derived cells using High Content Imaging and further methods. The following video illustrates the image analysis conducted with MIKAIA\u00ae. High Content Image Analysis with MIKAIA\u00ae […]<\/p>\n","protected":false},"author":2,"featured_media":3558,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3,35,28],"tags":[37,7,29,109,5],"coauthors":[56],"class_list":["post-3557","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-digital-pathology","category-life-science","category-mikaia-university","tag-ai","tag-mikaia","tag-mikaia-app-note","tag-use-case","tag-video"],"yoast_head":"\nHigh Content Imaging of ex-vivo drug response assay with MIKAIA<\/title>\n<meta name=\"description\" content=\"MIKAIA is used for the analysis of high-content imaging in ex-vivo drug response assays. 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