ArticleBiomedical engineering online2015
Evaluation of cytokeratin-19 in breast cancer tissue samples: a comparison of automatic and manual evaluations of scanned tissue microarray cylinders.
Article in Biomedical engineering online, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 27 citations in OpenAlex.
- Leveraging immune and clinicopathological profiles with machine learning to predict axillary lymph node metastasis in breast cancer patients.Breast cancer research : BCR · 2026Observational
- Reliability of stromal markers multiplex immunofluorescent staining: pathologist assessment compared to quantitative image analysis.American journal of cancer research · 2026Article
- Simultaneous Detection of Collagen I Alpha II and Cytokeratin 19 mRNA by Multiplex qPCR in Liquid Biopsy in Diagnosis of Patients with Resectable Solid Tumors.International journal of molecular sciences · 2024Article
- Matrix Metalloproteinase-9 Expression Is Associated with the Absence of Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer Patients.International journal of molecular sciences · 2023Article
- Article
- CD68 and CD83 immune populations in non-metastatic axillary lymph nodes are of prognostic value for the survival and relapse of breast cancer patients.Breast cancer (Tokyo, Japan) · 2022Article
- How the variability between computer-assisted analysis procedures evaluating immune markers can influence patients' outcome prediction.Histochemistry and cell biology · 2021Article
- The topology of vitronectin: A complementary feature for neuroblastoma risk classification based on computer-aided detection.International journal of cancer · 2020Article
- Article
- Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review.IEEE reviews in biomedical engineering · 2016Review
- New trends in biomedical engineering and bioinformatics applied to biomedicine - special issue of IWBBIO 2014.Biomedical engineering online · 2015Article
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDigital image (DI) analysis avoids visual subjectivity in interpreting immunohistochemical stains and provides more reproducible results. An automated procedure consisting of two variant methods for quantifying the cytokeratin-19 (CK19) marker in breast cancer tissues is presented.
methodsThe first method (A) excludes the holes inside selected CK19 stained areas, and the second (B) includes them. 93 DIs scanned from complete cylinders of tissue microarrays were evaluated visually by two pathologists and by the automated procedures. RESULTS AND
conclusionsThere was good concordance between the two automated methods, both of which tended to identify a smaller CK19-positive area than did the pathologists. The results obtained with method B were more similar to those of the pathologists; probably because it takes into account the entire positive tumoural area, including the holes. However, the pathologists overestimated the positive area of CK19. Further studies are needed to confirm the utility of this automated procedure in prognostic studies.
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