HER2-positive breast cancers usually benefit from anti-HER2 therapy, thus, HER2 evaluation became inevitable for patient selection. HER2-negative (IHC 0, 1+) and strong positive (IHC 3+) cases can easily be interpreted with immunohistochemistry, but equivocal (IHC 2+) cases require further analysis of HER2 gene amplification using in situ hybridization. Our study aimed to validate digital pathology and automated image analysis for unbiased evaluation of HER2 immunostains. We developed an image segmentation algorithm for analyzing HER2-immunostaining (4B5 clone) in tissue microarrays of breast cancers. Two pathologists assessed 309 microscopic regions of at least 100 tumor cells each—representing all HER2 positivity groups—according to international guidelines either semi-quantitatively or by using the MembraneQuant software. Scoring results were statistically correlated with each other and with FISH data, and almost perfect agreement was found (inter-method Cohen’s kappa = 0.872, Spearman-rho = 0.928). When clinical relevance (scoring disagreement that may define erroneous treatment selection) was examined high agreement was found (quadratic weighted kappa = 0.967). Image analysis classified cases with excellent correlation with visual evaluation, therefore, MembraneQuant software proved to be a reliable tool for assessing HER2 immunoreactions and supporting better targeting anti-HER2 therapy. As digital analysis of immunomorphological markers allows permanent archiving, standardization and accurate reviewing of results, it supports quality assurance initiatives in diagnostic pathology—especially of equivocal cases which are hard to interpret.

Fluorescence in situ hybridization is a widely used diagnostic procedure in pathology. This method can reveal the genetic background of malignant lesions. The aim of our study was to develop and optimize an image segmentation algorithm specifically for FISH quantification in breast cancer tissue. Moreover, we aimed to validate the results of our algorithm and to compare them with a semi-automated assessment (i.e. scoring on a computer screen) and the results of the conventional (i.e. manual microscopic) IHC quantification.

HER2 positive breast cancers can benefit from trastuzumab therapy based on a validated immunohistocemical reports. HER2-negative and strong positive cases are easy to interpret, but equivocal cases should be analyzed with FISH-technique to reveal HER2 amplification. Image analysis methods have been recently developed such as MembraneQuant by 3DHISTECH to support this process. We validated MembraneQuant software on HER2-immunostained (clone 4B5) tissue microarrays of 100 breast cancers covering all positivity groups and tested if semi-automated software analysis of HER2 immunostaining can discriminate between FISH-positive and negative equivocal cases. The renowned 4-tiered evaluation guidelines were used. The HER2 gene status of the 15 equivocalcases was also assessed with FISH. Detailed MembraneQuant analysis in the 9 FISH- and 6 FISH+ cases was used to predict HER2 amplification status.

BACKGROUND:The immunohistochemical detection of estrogen (ER) and progesterone (PR) receptors in breast cancer is routinely used for prognostic and predictive testing. Whole slide digitalization supported by dedicated software tools allows quantization of the image objects (e.g. cell membrane, nuclei) and an unbiased analysis of immunostaining results. Validation studies of image analysis applications for the detection of ER and PR in breast cancer specimens provided strong concordance between the pathologist's manual assessment of slides and scoring performed using different software applications.METHODS:The effectiveness of two connected semi-automated image analysis software (NuclearQuant v. 1.13 application for Pannoramic™ Viewer v. 1.14) for determination of ER and PR status in formalin-fixed paraffin embedded breast cancer specimens immunostained with the automated Leica Bond Max system was studied. First the detection algorithm was calibrated to the scores provided an independent assessors (pathologist), using selected areas from 38 small digital slides (created from 16 cases) containing a mean number of 195 cells. Each cell was manually marked and scored according to the Allred-system combining frequency and intensity scores. The performance of the calibrated algorithm was tested on 16 cases (14 invasive ductal carcinoma, 2 invasive lobular carcinoma) against the pathologist's manual scoring of digital slides.RESULTS:The detection was calibrated to 87 percent object detection agreement and almost perfect Total Score agreement (Cohen's kappa 0.859, quadratic weighted kappa 0.986) from slight or moderate agreement at the start of the study, using the un-calibrated algorithm. The performance of the application was tested against the pathologist's manual scoring of digital slides on 53 regions of interest of 16 ER and PR slides covering all positivity ranges, and the quadratic weighted kappa provided almost perfect agreement (κ = 0.981) among the two scoring schemes.CONCLUSIONS:NuclearQuant v. 1.13 application for Pannoramic™ Viewer v. 1.14 software application proved to be a reliable image analysis tool for pathologists testing ER and PR status in breast cancer.