This document summarizes a study that used quantitative image analysis of HER2 expression in esophagogastric adenocarcinoma tissue samples to identify prognostic factors. Automated image analysis was performed using the Definiens platform to extract over 50 image features from segmented cells and subcellular compartments. Multivariate regression analysis was able to predict disease-free and overall survival times from these quantitative image features, which were then shown to have prognostic value when analyzed with Kaplan-Meier survival curves. This demonstrated that automated quantitative image analysis can provide statistically significant prognostic factors not accessible to visual analysis alone.

1. 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

2. 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
Slide - 2 Quantitative image analysis
Definiens AG

3. 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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4. Pathologist Score 3+
Score depends an membrane staining intensity, staining completeness,
and percentage of stained tumor cells
5x
20x
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5. Pathologist Score 2+
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6. Pathologist Score 1+
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7. Pathologist Score 0
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8. Pathologist Score As Prognostic Factor
Score 0, 1+, 2+ versus 3+
Disease Free Survival Overall Survival
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9. Automated Image Analysis with Definiens Platform
Step 1. TMA core detection and grid assignment
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10. Automated Image Analysis with Definiens Platform
Step 2. Cell and cell compartment segmentation and classification
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11. Multi-hierarchical Segmentation: Cells
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12. Multi-hierarchical Segmentation: Nucleus, Cytoplasm and Membrane
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13. Multi-hierarchical Segmentation: Nucleus and Membrane Substructure
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14. Sample Image Analysis Results I
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15. Sample Image Analysis Results II
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16. Sample Image Analysis Results III
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17. Quantitative Image Analysis Results
Regression Learner Goals (54) image features
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18. Multivariate Regression Analysis to Predict Survival Time
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19. Use Predicted Disease Free Survival Time as Prognostic Factor
Kaplan Meier analysis of disease free survival time
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20. Use Predicted Overall Survival Time as Prognostic Factor
Kaplan Meier analysis of overall survival time
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21. 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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22. 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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