Image Analysis


To acknowledge use of this shared resource, please include the following in your publications: This research was partially supported by UNM Comprehensive Cancer Center Support Grant NCI P30CA118100 and made use of the Human Tissue Repository and Tissue Analysis Shared Resource, which receives additional support from The University of New Mexico School of Medicine Department of Pathology.

Image Analysis Images of immunohistochemically stained tissue sections or immunofluorescence sections are captured on the Leica Versa 200 digital scanner and uploaded to the HALO imaging and annotation software. The HALO software allows you to annotate the tissue (tumor, stroma, muscle, fat etc.) and then count cells that are positive for protein of choice (Figure) within each of these annotated regions. It will also enable you to analyze and quantify nearest neighbor interactions. The software includes a figure-making tool that can create multi-panel photos of images in publishable formats including reference frames and scale bars.

Figure: Figure shows quantification of staining for Ki67 in breast cancer. Top left panel shows the tissue microarray sample, the middle panel shows Ki67 staining (brown) without the HALO markup and the right panel show the same image with the HALO markup. The markup shows low level staining (yellow), moderate staining (brown) and high levels (red) of Ki67 in the nucleus of tumor cells. Blue staining are cells that are negative for Ki67. The software can independently count Ki67 staining in the stoma of the tumor. The table shows a read out of the number and percentage of cells in each staining category and the histogram shows the distribution of staining.