A simple digital image analysis for automated Ki67 assessment in primary breast cancer.

Alataki, Anastasia; Zabaglo, Lila; Tovey, Holly; Dodson, Andrew; Dowsett, Mitch

AIMS Ki67 is a well-established immunohistochemical marker associated with cell proliferation that has prognostic and predictive value in breast cancer. Quantitative evaluation of Ki67 is traditionally performed by assessing stained tissue slides using light microscopy. Automated image analysis systems have become available and if validated they could provide greater standardisation and improving precision of Ki67 scoring. Here, we aimed to evaluate the use of the Cognition Master Professional Suite (CogM) image analysis software, a simple system for scoring Ki67 in primary breast cancer samples. METHODS AND RESULTS Sections from 94 core-cut biopsies, 20 excision specimens, and 29 pairs of core-cuts and excisions were stained for Ki67 with MIB1 antibody and the Dako EnVision FLEX Detection System. Stained slides were scanned to convert them to digital data. Computer-based Ki67 scoring was performed by CogM. Manual Ki67 scoring assessment was conducted on previously stained sections from the same biopsies using a clinically validated system that had been calibrated against risk of recurrence. A high correlation between manual and digital scores was observed (rCores =0.92, 95% CI=0.87-0.94, p<0.0001; rExcisions =0.95, 95% CI=0.86-0.98, p<0.0001) and there was no significant bias between them (p=0.45). There was also a high correlation on Ki67 scores between paired core-cuts and excisions using CogM (r=0.78, 95% CI=0.59-0.89, p<0.0001). CONCLUSIONS CogM image analysis allows for a standardised automated Ki67 scoring that accurately replicates previously clinically validated and calibrated manual scores.