Qualitopix - Choice of Reference for Automatic Quality Assessment of the Estrogen Receptor

Ottosen, A., Harder, S., Schønau, A., Vyberg, M., Røge, R., Nielsen, S.

Introduction: Immunohistochemistry is an important tool in patient diagnostics, and therefore external quality assessment (EQA) of immunoassays is essential to obtain optimal and comparable results. EQA is typically performed manually, which is partly subjective causing inconsistent scoring. 

Digital image analysis (DIA) may support EQA by extracting useful information in images to provide objective and standardized results. We propose a solution for automatic quality assessment of semi-quantitative biomarkers, called QUALITOPIX. Our solution can be used to evaluate the precision of an IHC-test in comparison to reference-test by quantification of staining sufficiency. 

For Estrogen Receptor (ER) slides, the fundamental principle is using DIA to quantify the intensity of the stained tumor nuclei into an H-score [1]. The quality is evaluated by calculating the absolute distance from the slide of the individual lab to an established reference, where a large distance indicates staining insufficiency. We present this original (Method 1) and an extended method (Method 2), that amplifies insufficiency caused by weak staining and accounts for background staining. 

We have investigated two different references: One based on a reference from the same tissue block and a joined reference across multiple blocks. Both references have been used in combination with the two methods. 

 


Detecting lymph node metastases in breast cancer using deep learning

Thagaard, J., Medicine & Technology, Technical University of Denmark

We use deep learning to automatically detect and classify breast cancer metastases, providing crucial information for the prognosis and treatment decision of breast cancer. Our method qualified for IEEE International Symposium on Biomedical Imaging 2017 Grand Challenge CAMELYON17 Melbourne, Australia. We were ranked 5thout of 23 qualifying teams of international research groups and commercial teams, with a marginal score difference to the winner of the CAMELYON17 competition.

 


Membrane connectivity as a robust measure for the HER2 IHC score

Brügmann, A., Eld, M., Lelkaitis, G., Nielsen, S., Grunkin, M., Hansen, J., Foged, N., Vyberg, M.

The use of digital image analysis for HER2 IHC evaluation is encouraged by ASCO/CAP and reimbursement policies. By individually analyzing the invasive tumor cells and determining the ratio of invasive tumor cells with positive membrane staining, the commercially available classical HER2 IHC algorithms for image analysis are compatible with the scoring principles of the ASCO/CAP guidelines.

Several practical limitations and controversial aspects are associated with individual cell evaluation and counting. Whether by microscopy or digital reading on a monitor, manual scoring of HER2 IHC is therefore typically performed as an overall assessment of the degree of membrane staining within the invasive tumor region of interest (ROI). Counting principles are more readily implemented if based on image analysis, but the controversial aspects of individual cell evaluation remain. It is complicated for algorithms to identify individual invasive tumor cells, since their nucleus and/or cell membrane may not be clearly defined after HER2 IHC staining. Also, it is not obvious if a cell membrane belongs to a particular cell and/or adjacent cells in a dense region of invasive tumor. Furthermore, the classical algorithms and cell ratio quantification require a meticulous outlining of the ROI to avoid contributions from e.g., stromaand ductalcarcinoma in situ.

In this study, we present a novel HER2 IHC algorithm, which uses principles that are not direct translations of the ASCO/CAP and reagent manufacturer’s guidelines. Rather than estimating cell ratio, the present algorithm exploits the unique capacity of computerized image analysis to quantify the characteristic “chicken wire” pattern of HER2 IHC by measuring the connectivity and size distribution of stained membranes. The validation study included 430 ROI’s easily outlined in 86 scanned images of 43 invasive breast carcinoma specimens stained by HercepTestand Pathway HER2/neu, and showed a 92.3% agreement with independent manual reading by 5 experienced assessors.