PUBLICATION
A new software tool for computer assisted in vivo high-content analysis of transplanted fluorescent cells in intact zebrafish larvae
- Authors
- Førde, J.L., Reiten, I.N., Fladmark, K.E., Kittang, A.O., Herfindal, L.
- ID
- ZDB-PUB-221115-7
- Date
- 2022
- Source
- Biology Open 11(12): (Journal)
- Registered Authors
- Fladmark, Kari E.
- Keywords
- Acute myeloid leukaemia, Automatic image processing, Cell segmentation, Confocal imaging, Myelodysplastic syndrome, Zebrafish
- MeSH Terms
-
- Animals
- Computers
- Image Processing, Computer-Assisted*/methods
- Larva
- Software
- Zebrafish*
- PubMed
- 36355409 Full text @ Biol. Open
Citation
Førde, J.L., Reiten, I.N., Fladmark, K.E., Kittang, A.O., Herfindal, L. (2022) A new software tool for computer assisted in vivo high-content analysis of transplanted fluorescent cells in intact zebrafish larvae. Biology Open. 11(12):.
Abstract
Acute myeloid leukaemia and myelodysplastic syndromes are cancers of the bone marrow with poor prognosis in frail and older patients. To investigate cancer pathophysiology and therapies, confocal imaging of fluorescent cancer cells and their response to treatments in zebrafish larvae yields valuable information. While zebrafish larvae are well suited for confocal imaging, the lack of efficient processing of large datasets remains a severe bottleneck. To alleviate this problem, we present a software tool to segment cells from confocal images and track characteristics such as volume, location in the larva and fluorescent intensity on a single-cell basis. Using this software tool, we were able to characterize the responses of the cancer cell lines Molm-13 and MDS-L to established treatments. By utilizing the computer-assisted processing of confocal images as presented here, more information can be obtained while being less time-consuming and reducing the demand of manual data handling, when compared to a manual approach, thereby accelerating the pursuit of novel anti-cancer treatments. The presented software tool is available as an ImageJ java-plugin at https://zenodo.org/ and the source code at https://github.com/Jfo004/ConfocalCellSegmentation.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping