Practical approaches to automated digital image analysis of Ki-67 labeling index in 997 breast carcinomas and causes of discordance with visual assessment

PloS One
Ah-Young KwonEun Yoon Cho

Abstract

The Ki-67 labeling index (LI) is an important prognostic factor in breast carcinoma. The Ki-67 LI is traditionally calculated via unaided microscopic estimation; however, inter-observer and intra-observer variability and low reproducibility are problems with this visual assessment (VA) method. For more accurate assessment and better reproducibility with Ki-67 LI, digital image analysis was introduced recently. We used both VA and automated digital image analysis (ADIA) (Ventana Virtuoso image management software) to estimate Ki-67 LI for 997 cases of breast carcinoma, and compared VA and ADIA results. VA and ADIA were highly correlated (intraclass correlation coefficient 0.982, and Spearman's correlation coefficient 0.966, p<0.05). We retrospectively analyzed cases with a greater than 5% difference between VA and ADIA results. The cause of these differences was: (1) tumor heterogeneity (98 cases, 56.0%), (2) VA interpretation error (32 cases, 18.3%), (3) misidentification of tumor cells (26 cases, 14.9%), (4) poor immunostaining or slide quality (16 cases, 9.1%), and (5) Estimation of non-tumor cells (3 cases, 1.7%). There were more discrepancies between VA and ADIA results in the group with a VA value of 10-20% compared to gro...Continue Reading

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Citations

Dec 15, 2019·Journal of Clinical Medicine·Eugeni Lopez-BonetJavier A Menendez
May 23, 2020·Breast Cancer : the Journal of the Japanese Breast Cancer Society·Rie HoriiFutoshi Akiyama
Nov 27, 2020·Journal of Gastroenterology and Hepatology·Shumpei YamamotoHiroyuki Okada
Apr 14, 2021··Martin LindvallJonas Löwgren

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Methods Mentioned

BETA
biopsy

Software Mentioned

Ventana Virtuoso management
Ventana
Ventana Virtuoso image management
SPSS
AIDA
ADIA

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