BACKGROUND: Breast cancers that overexpress the human epidermal growth factor 
receptor 2 (HER2) are eligible for effective biologically targeted therapies, 
such as trastuzumab. However, accurately determining HER2 overexpression, 
especially in immunohistochemically equivocal cases, remains a challenge. Manual 
analysis of HER2 expression is dependent on the assessment of membrane staining 
as well as comparisons with positive controls. In spite of the strides that have 
been made to standardize the assessment process, intra- and inter-observer 
discrepancies in scoring is not uncommon. In this manuscript we describe a 
pathologist assisted, computer-based continuous scoring approach for increasing 
the precision and reproducibility of assessing imaged breast tissue specimens.
METHODS: Computer-assisted analysis on HER2 IHC is compared with manual scoring 
and fluorescence in situ hybridization results on a test set of 99 digitally 
imaged breast cancer cases enriched with equivocally scored (2+) cases. Image 
features are generated based on the staining profile of the positive control 
tissue and pixels delineated by a newly developed Membrane Isolation Algorithm. 
Evaluation of results was performed using Receiver Operator Characteristic (ROC) 
analysis.
RESULTS: A computer-aided diagnostic approach has been developed using a 
membrane isolation algorithm and quantitative use of positive immunostaining 
controls. By incorporating internal positive controls into feature analysis a 
greater Area Under the Curve (AUC) in ROC analysis was achieved than feature 
analysis without positive controls. Evaluation of HER2 immunostaining that 
utilized membrane pixels, controls, and percent area stained showed 
significantly greater AUC than manual scoring, and significantly less false 
positive rate when used to evaluate immunohistochemically equivocal cases.
CONCLUSION: It has been shown that by incorporating both a membrane isolation 
algorithm and analysis of known positive controls a computer-assisted diagnostic 
algorithm was developed that can reproducibly score HER2 status in IHC stained 
clinical breast cancer specimens. For equivocal scoring cases, this approach 
performed better than standard manual evaluation as assessed by ROC analysis in 
our test samples. Finally, there exists potential for utilizing image-analysis 
techniques for improving HER2 scoring at the immunohistochemically equivocal 
range.