Acute myeloid leukemia 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 that segments 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 characterise 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/10.5281/zenodo.7383160 and the source code at https://github.com/Jfo004/ConfocalCellSegmentation.
Keywords: Acute myeloid leukaemia; Automatic image processing; Cell segmentation; Confocal imaging; Myelodysplastic syndrome; Zebrafish.
© 2022. Published by The Company of Biologists Ltd.