INTRODUCTION: Accurate assessment of estrogen receptor (ER), progesterone 
receptor (PR), and Ki-67 is essential in the histopathologic diagnostics of 
breast cancer. Commercially available image analysis systems are usually bundled 
with dedicated analysis hardware and, to our knowledge, no easily installable, 
free software for immunostained slide scoring has been described. In this study, 
we describe a free, Internet-based web application for quantitative image 
analysis of ER, PR, and Ki-67 immunohistochemistry in breast cancer tissue 
sections.
METHODS: The application, named ImmunoRatio, calculates the percentage of 
positively stained nuclear area (labeling index) by using a color deconvolution 
algorithm for separating the staining components (diaminobenzidine and 
hematoxylin) and adaptive thresholding for nuclear area segmentation. 
ImmunoRatio was calibrated using cell counts defined visually as the gold 
standard (training set, n = 50). Validation was done using a separate set of 50 
ER, PR, and Ki-67 stained slides (test set, n = 50). In addition, Ki-67 labeling 
indexes determined by ImmunoRatio were studied for their prognostic value in a 
retrospective cohort of 123 breast cancer patients.
RESULTS: The labeling indexes by calibrated ImmunoRatio analyses correlated well 
with those defined visually in the test set (correlation coefficient r = 0.98). 
Using the median Ki-67 labeling index (20%) as a cutoff, a hazard ratio of 2.2 
was obtained in the survival analysis (n = 123, P = 0.01). ImmunoRatio was shown 
to adapt to various staining protocols, microscope setups, digital camera 
models, and image acquisition settings. The application can be used directly 
with web browsers running on modern operating systems (e.g., Microsoft Windows, 
Linux distributions, and Mac OS). No software downloads or installations are 
required. ImmunoRatio is open source software, and the web application is 
publicly accessible on our website.
CONCLUSIONS: We anticipate that free web applications, such as ImmunoRatio, will 
make the quantitative image analysis of ER, PR, and Ki-67 easy and 
straightforward in the diagnostic assessment of breast cancer specimens.