| Title |
A methodology to ensure and improve accuracy of Ki67 labelling index estimation by automated digital image analysis in breast cancer tissue / |
| Authors |
Laurinavičius, Arvydas ; Plancoulaine, Benoit ; Laurinavičienė, Aida ; Herlin, Paulette ; Meškauskas, Raimundas ; Baltrušaitytė, Indra ; Besusparis, Justinas ; Dasevičius, Darius ; Elie, Nicolas ; Iqbal, Yasir ; Bor, Catherine ; Ellis, Ian Ogilvie |
| DOI |
10.1186/bcr3639 |
| Full Text |
|
| Is Part of |
Breast cancer research.. London : Current Medicine Group Ltd. 2014, vol. 16, no 2, art no R35 [p. 1-13].. ISSN 1465-5411 |
| Abstract [eng] |
Misclassification rate of 5-7 % was achieved, compared to that of 11-18 % for the VE-median-based prediction. Conclusions Our experiments provide methodology to achieve accurate Ki67-LI estimation by DIA, based on proper validation, calibration, and measurement error correction procedures, guided by quantified bias from reference values obtained by stereology grid count. This basic validation step is an important prerequisite for high-throughput automated DIA applications to investigate tissue heterogeneity and clinical utility aspects of Ki67 and other immunohistochemistry (IHC) biomarkers. |
| Published |
London : Current Medicine Group Ltd |
| Type |
Journal article |
| Language |
English |
| Publication date |
2014 |
