Although it is an important biomarker in oncology (mostly in breast and prostate), Ki-67 immunohistochemistry (IHC) analysis has yet to be standardized. Working groups have provided guidelines for Ki-67 scoring in different cancer types to limit pathologist’s variability.¹‚² AI solutions to assist scoring have recently emerged in the evaluation of Ki-67 as rapid and robust solutions. In this study, we compared the results of Ki-67 scoring performed with Aiforia® Platform (deep learning AI platform) against three independent pathologists on various solid tumors.
Cerba Research stained 192 tumors of various origins including breast and prostate with the CONFIRM anti-Ki-67 clone (30-9) (ROCHE monoclonal primary antibody (IVD)) on the Ventana Benchmark Ultra. Three pathologists were appropriately trained following the International Ki-67 Working Group (IKWG) recommendations and scored tissues accordingly.³
¹ Polley MY et al. An international study to increase concordance in Ki-67 scoring. Mod Pathol. 2015 Jun;28(6):778-86. doi: 10.1038/modpathol.2015.38.
² Nielsen TO et al. Assessment of Ki-67 in Breast Cancer: Updated Recommendations From the International Ki-67 in Breast Cancer Working Group. J Natl Cancer Inst. 2021 Jul 1;113(7):808-819. doi: 10.1093/jnci/djaa201.
³ Welcome to Ki-67-QC calibrator. URL [http://www.gpec.ubc.ca:8080/tmadb-0.1/calibrator/index]
Out of 192 cores, only 158 were analyzed due to absence of tissue and/or pathologists unable to score. Ki-67+ cells were detected in 24.38 - 28.71% of the tumor cells on average depending on the analysis approach applied. The study shows a very high consistency of results obtained for Ki-67 scoring between the two image analysis softwares (r2=0.95) on solid tumors analyzed (n=158). The correlation obtained between the pathologists was however weaker (mean r2=0.83), despite appropriate training and following guidelines, but remains within an acceptable range.
Rania Gaspo, Dir, Global Therapy Area Lead, from Cerba Research, comments on the results: “In a nutshell, this work shows that recent AI-based image analysis tools such as Aiforia® Platform provide valuable assistance in the field of image analysis and allowed us to drastically reduce inter-pathologist variability in the Ki-67 scoring of solid tumors. We were also positively surprised with the speed of execution of Aiforia® Platform that was able to process regions of interest for all cores in just 2 minutes, saving us a lot of time and effort.”
Read more on the ESMO poster: “Pichon X, Gaspo R, Iglesias S, Kumar D, Tliba M, Burrer R, Finan A. Evidence for the utility of artificial intelligence (AI) and image analysis in Ki-67 quantification in solid tumors. Presented at: ESMO annual meeting; October 20-24, 2023; Madrid, Spain”.