Human epidermal growth factor receptor 2 (HER2), a transmembrane tyrosine kinase receptor encoded by the gene on chromosome 17q12, is a predictive and prognostic biomarker in invasive breast cancer (BC). Approximately 20% of BC are HER2-positive as a result of gene amplification and overexpression of the HER2 protein. Quantification of is performed routinely on all invasive BCs, to assist in clinical decision making for prognosis and treatment for -positive BC patients by manually counting gene signals. We propose an automated system to quantify the gene status from chromogenic hybridization (CISH) whole slide images (WSI) in invasive BC. The proposed method selects untruncated and nonoverlapped singular nuclei from the cancer regions using color unmixing and machine learning techniques. Then, and chromosome enumeration probe 17 (CEP17) signals are detected based on the RGB intensity and counted per nucleus. Finally, the -to-CEP17 signal ratio is calculated to determine the amplification status following the ASCO/CAP 2018 guidelines. The proposed method reduced the labor and time for the quantification. In the experiment, the correlation coefficient between the proposed automatic CISH quantification method and pathologist manual enumeration was 0.98. The -values larger than 0.05 from the one-sided paired -test ensured that the proposed method yields statistically indifferent results to the reference method. The method was established on WSI scanned by two different scanners. Through the experiments, the capability of the proposed system has been demonstrated.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6868351 | PMC |
http://dx.doi.org/10.1117/1.JMI.6.4.047501 | DOI Listing |
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