1390 Identification Of Prognostic Factors Using Quantitative Image Analysis Of Her2 Expression.Pdf...
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Transcript of 1390 Identification Of Prognostic Factors Using Quantitative Image Analysis Of Her2 Expression.Pdf...
Identification of Prognostic Factors using Quantitative Image Analysis of HER2 Expression by Immunohistochemistry (IHC) in Adenocarcinoma of the Esophagogastric Junction
Günter Schmidt, Gerd Binnig
Definiens AG München
Annette Feuchtinger, Axel Walch
Pathology, HelmholtzZentrum München
52nd Symposium of the Society for Histochemistry
Prague, 1 - 4 September 2010
Study Overview
Surgical Resection Prognostic factor performance Klinikum Rechts der Isar, TU Munich Definiens AG; Biomathematics and
Biometry, Helmholtz Zentrum
Visual HER2 scoring by pathologist Pathology, Helmholtz Zentrum
Illustration
Image: University of California, 1919
Tissue IHC staining and
image acquisition Pathology, Helmholtz Zentrum
Definiens Developer XD, 2010
Quantitative image analysis Definiens AG
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Data: Tissue Micro Arrays of Biopsy Tissue Sections
132 cancer patients �
390 tissue cores on 3 TMAs �
HER2 (human epidermal �growth factor receptor 2)
� Membrane protein
� Known to indicate
aggressive cancer subtypes
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Pathologist Score 3+ Score depends an membrane staining intensity, staining completeness,
and percentage of stained tumor cells
5x
20x
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Pathologist Score As Prognostic Factor Score 0, 1+, 2+ versus 3+
Disease Free Survival Overall Survival
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Automated Image Analysis with Definiens Platform Step 1. TMA core detection and grid assignment
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Automated Image Analysis with Definiens Platform Step 2. Cell and cell compartment segmentation and classification
Use Predicted Disease Free Survival Time as Prognostic Factor Kaplan Meier analysis of disease free survival time
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Use Predicted Overall Survival Time as Prognostic Factor Kaplan Meier analysis of overall survival time
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Disease Free Survival Time Prediction after Feature Space Reduction Kaplan Meier analysis indicates significant prognostic value (2 fold cross validated)
Single object properties �
� cell_brown(q05)*
� cell_brown(q50)
� cell_brown(q95)
Properties of object relations �
� membrane_cytoplasm_ratio_red(q05)
� membrane_cytoplasm_ratio_red(q50)
� membrane_cytoplasm_ratio_red(q95)
� membrane_cytoplasm_ratio_green(q05)
� membrane_cytoplasm_ratio_green(q50)
� membrane_cytoplasm_ratio_green(q95)
(*) q05/50/95 are 5%/50%/95% quantiles of object feature values per core
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Summary
Automated quantitative image analysis �
� Extracts rich set of image object measurements previously not accessible to
biologist / pathologist
� Provides statistically significant prognostics factors
Definiens Cognition Network Technology comprises �
� Context driven segmentation and classification generates multi-hierarchical
network of image objects
� Comprehensible image analysis process
Definiens image analysis platform is �
� Open for integration: image acquisition, algorithms, data bases
� Scalable using distributed, load balanced, computer grid
� See more at www.definiens.com
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