Computer Aided Semi-Automated Evaluation of HER2 Immunodetection—A Robust Solution for Supporting the Accuracy of Anti HER2 Therapy

Abstract

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.

Validation of Whole-Slide Imaging for Histolopathogical Diagnosis: Current State

“…These diagnostic algorithms facilitate quantification of IHC positivity resulting in a more objective evaluation, which is extremely useful in the evaluation of some biological markers. Algorithms for the evaluation of IHC stains are variably used depending on the subspecialties and are particularly useful in cases of breast cancer [26,27,28,29]. …”

“…A major advantage of digitization in breast pathology is the possibility to use image analysis to improve the accuracy and reproducibility of HER-2, estrogen and progesterone receptors, and Ki67 scoring, which have a crucial role in the planning of treatment strategies [27,28,29,49]. Moreover, the evaluation may be improved with the use of automatic quantification algorithms (fig.…”

Computer-based image analysis in breast pathology

“…Therefore, membrane segmentation is one of the main steps of automated methods for quantification of HER2. A color-based approach,[49] water shedding,[50] and skeletonization[51] were used for membrane segmentation. After the segmentation stage, a group of features was extracted from the membrane and then utilized for prediction of HER2 score.…”

“…After the segmentation stage, a group of features was extracted from the membrane and then utilized for prediction of HER2 score. The extracted features were based on membrane staining intensity,[49515253] membrane completeness,[4953] or membrane color properties. [5455] Instead of restricting the area for feature selection to the segmented membrane, Ali et al .…”

Validation of whole-slide imaging in the primary diagnosis of liver biopsies in a University Hospital

“…This is not only extremely useful in tumors boards, but also allows expert tele-consultation of difficult cases and frozen section intra-operative biopsies [9,10]. Finally, with WSI algorithms can be used for the evaluation and quantification of immuhistochemical stains, resulting in a more objective evaluation [11][12][13][14]. This tool is likely to become essential to achieve standardized diagnoses in the near future.…”