Optimization of Ki67 digital image analysis in breast cancer by automated tumor area identification
Paul Jank·Wolfgang D. Schmitt·M Untch·M Reinisch·T Link·Albert Grass·Jens-Uwe Blohmer·Claus Hanusch·Anne-Sophie Litmeyer·J Huober·Dominik Gerber·Christine Solbach·Vesna Bjelic-Radisic·Kai Saeger·Andreas Schneeweiss·Kerstin Rhiem·Moritz Gleitsmann·Susanne von Gerlach·Bärbel Felder·Moritz Jesinghaus·Carsten Denkert·Sibylle Loibl·Maximilian J Krämer
Accurate assessment of Ki67, a marker of cellular proliferation, is critical for breast cancer diagnostics and treatment decision-making. This study evaluates an automated Ki67-area identification approach, combined with digital image analysis (DIA) for exact Ki67 quantification. A total of 61 tissue samples from breast cancer patients from two clinical trials (GeparSixto and GeparSepto) were analyzed. The supervised DIA workflow employed automated Ki67-stained tumor area identification, followe