Journal: BMC Biology
Article Title: MATISSE: a method for improved single cell segmentation in imaging mass cytometry
doi: 10.1186/s12915-021-01043-y
Figure Lengend Snippet: Combining fluorescence microscopy with multiplex IMC data of colorectal tissue advances quality of single cell segmentation. a Cartoon describing MATISSE, a novel pipeline adding microscopic imaging to multiplex IMC analysis and downstream segmentation. In short: tissue sections on slides were stained using isotope-conjugated primary antibodies, DNA intercalator, and DAPI. The tissue was first scanned using a fluorescent microscope and then processed with IMC. Data produced by both techniques is aligned using the nuclear staining. Nuclear and membranous pixel probability maps are produced based on the fluorescent images and IMC data respectively. These probability maps are used to generate a segmentation map, where all detected cells are included. b Representative images of DNA intercalator on a colorectal tissue section analyzed by Ir193 labeling and IMC (left) or DAPI labeling and fluorescent microscopy (IF, right). c IMC-only (IMC) and MATISSE cell segmentation (MATISSE) were performed, and shown are the different predicted outlines on a representative image of Ir193 labeling. Arrows indicate areas with cell fragmentation. d Display of a large region of interest (ROI) showing an overlay of the predicted cell outlines (pink) upon IMC or MATISSE segmentation on a representative IMC image of DNA-Ir193 labeling of colorectal tissue. Highlighted in yellow is the approximate position of the basement membrane surrounding the epithelial monolayer. Scale bar 25 μm. e Cell density was calculated as the number of cells within a radius of 10 μM from the center of each single cell [ , ]. This number is displayed with a color code for each cell in the representative image
Article Snippet: We observed that incorporating fluorescent microscopy images based on DAPI nuclear staining into MATISSE workflow resulted in superior visual and signal intensity-based separation of nuclei in dense areas (Fig. b, Additional file : Fig S1B).
Techniques: Fluorescence, Microscopy, Multiplex Assay, Imaging, Staining, Produced, Labeling, Membrane
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![Combining fluorescence microscopy with multiplex IMC data of colorectal tissue advances quality of single cell segmentation. a Cartoon describing MATISSE, a novel pipeline adding microscopic imaging to multiplex IMC analysis and downstream segmentation. In short: tissue sections on slides were stained using isotope-conjugated primary antibodies, DNA intercalator, and <t>DAPI.</t> The tissue was first scanned using <t>a</t> <t>fluorescent</t> microscope and then processed with IMC. Data produced by both techniques is aligned using the nuclear staining. Nuclear and membranous pixel probability maps are produced based on the fluorescent images and IMC data respectively. These probability maps are used to generate a segmentation map, where all detected cells are included. b Representative images of DNA intercalator on a colorectal tissue section analyzed by Ir193 labeling and IMC (left) or DAPI labeling and fluorescent microscopy (IF, right). c IMC-only (IMC) and MATISSE cell segmentation (MATISSE) were performed, and shown are the different predicted outlines on a representative image of Ir193 labeling. Arrows indicate areas with cell fragmentation. d Display of a large region of interest (ROI) showing an overlay of the predicted cell outlines (pink) upon IMC or MATISSE segmentation on a representative IMC image of DNA-Ir193 labeling of colorectal tissue. Highlighted in yellow is the approximate position of the basement membrane surrounding the epithelial monolayer. Scale bar 25 μm. e Cell density was calculated as the number of cells within a radius of 10 μM from the center of each single cell [ , ]. This number is displayed with a color code for each cell in the representative image](https://pub-med-central-images-cdn.bioz.com/pub_med_central_ids_ending_with_4487/pmc08114487/pmc08114487__12915_2021_1043_Fig1_HTML.jpg)