Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Evaluation of positivity of estrogen receptors on breast cancer tissue through computerized morphometric analysis

Evaluation of positivity of estrogen receptors on breast cancer tissue through computerized... IntroductionOne of the essential steps in determining breast cancer patients’ appropriate treatment is the assessment of hormone receptor expression in neoplastic tissues, which is mostly performed by the immunohistochemistry (IHC) technique. The quantitative evaluation of these receptors is usually done subjectively, which allows variability in the results. Therefore, this research aimed to develop low-cost software capable of automatically evaluating immunohistochemical digital images of breast cancer tissues, generating standardized results.MethodsFor the development of the tool, MATLAB R2015a was used. Digital immunohistochemical images were evaluated for quantification of the total nuclei of the neoplastic cells. Subsequently, the number of neoplastic cells with positivity for estrogen receptor expression was obtained, followed by a quantitative evaluation of the positivity intensity using the Allred scale. Three specialists evaluated the same digital images independently and without knowledge of the computational analysis results, performing the Allred score.ResultsAccuracy was between 78.5 and 95.1%, sensitivity between 96.6 and 100%, specificity between 67.2 and 93.3%, and efficiency between 83.6 and 94.9%. We found an excellent level of agreement between manual scoring and the software analysis for the Allred total scale.ConclusionThe proposed automated software is a viable alternative for measuring immunohistochemical estrogen receptor expression in breast cancer tissues. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Research on Biomedical Engineering Springer Journals

Evaluation of positivity of estrogen receptors on breast cancer tissue through computerized morphometric analysis

Download PDF
11 pages

Loading next page...
 
/lp/springer-journals/evaluation-of-positivity-of-estrogen-receptors-on-breast-cancer-tissue-YdI8K3nY6v
Publisher
Springer Journals
Copyright
Copyright © Sociedade Brasileira de Engenharia Biomedica 2021
ISSN
2446-4732
eISSN
2446-4740
DOI
10.1007/s42600-021-00170-3
Publisher site
See Article on Publisher Site

Abstract

IntroductionOne of the essential steps in determining breast cancer patients’ appropriate treatment is the assessment of hormone receptor expression in neoplastic tissues, which is mostly performed by the immunohistochemistry (IHC) technique. The quantitative evaluation of these receptors is usually done subjectively, which allows variability in the results. Therefore, this research aimed to develop low-cost software capable of automatically evaluating immunohistochemical digital images of breast cancer tissues, generating standardized results.MethodsFor the development of the tool, MATLAB R2015a was used. Digital immunohistochemical images were evaluated for quantification of the total nuclei of the neoplastic cells. Subsequently, the number of neoplastic cells with positivity for estrogen receptor expression was obtained, followed by a quantitative evaluation of the positivity intensity using the Allred scale. Three specialists evaluated the same digital images independently and without knowledge of the computational analysis results, performing the Allred score.ResultsAccuracy was between 78.5 and 95.1%, sensitivity between 96.6 and 100%, specificity between 67.2 and 93.3%, and efficiency between 83.6 and 94.9%. We found an excellent level of agreement between manual scoring and the software analysis for the Allred total scale.ConclusionThe proposed automated software is a viable alternative for measuring immunohistochemical estrogen receptor expression in breast cancer tissues.

Journal

Research on Biomedical Engineering – Springer Journals

Published: Dec 1, 2021

Keywords: Breast neoplasm; Computer-assisted; Image processing; Immunohistochemistry

References

  • The gold standard paradox in digital image analysis: manual versus automated scoring as ground truth
    Aeffner, F; Wilson, K; Martin, NT; Black, JC; Hendriks, CLL; Bolon, B; Young, GD
  • Estrogen and progesterone receptor testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists guideline update
    Allison, KH; Hammond, MEH; Dowsett, M; McKernin, SE; Carey, LA; Fitzgibbons, PL; Wolff, AC
  • Comparing computer-generated and pathologist-generated tumour segmentations for immunohistochemical scoring of breast tissue microarrays
    Akbar, S; Jordan, LB; Purdie, CA; Thompson, AM; McKenna, SJ
  • Prognostic and predictive factors in breast cancer by immunohistochemical analysis
    Allred, DC; Harvey, JM; Berardo, M; Clark, GM
  • Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries
    Bray, F; Ferlay, J; Soerjomataram, I; Siegel, RL; Torre, LA; Jemal, A
  • Clinical application of image analysis in pathology
    Cornish, TC
  • Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology
    Cicchetti, DV
  • Predictive factors of breast cancer evaluated by immunohistochemistry
    Gobbi, H; Rocha, RM; Nunes, CB
  • American Society of Clinical Oncology/College of American Pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer (unabridged version)
    Hammond, ME; Hayes, DF; Dowsett, M
  • Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer
    Krecsák, L; Micsik, T; Kiszler, G
  • Breast cancer in Brazil: present status and future goals
    Lee, BL; Liedke, PE; Barrios, CH; Simon, SD; Finkelstein, DM; Goss, PE
  • Quantitative immunohistochemistry using the CAS 200/486 image analysis system in invasive breast carcinoma: a reproducibility study
    Makkink-Nombrado, SV; Baak, JP; Schuurmans, L; Theeuwes, JW; van der Aa, T
  • Influence of delay on survival in patients with breast cancer: a systematic review
    Richards, MA; Westcombe, AM; Love, SB; Littlejohns, P; Ramirez, AJ
  • Digital image analysis in breast pathology-from image processing techniques to artificial intelligence
    Robertson, S; Azizpour, H; Smith, K; Hartman, J
  • From microscopy to whole slide digital images: a century and a half of image analysis
    Taylor, CR
  • Avaliação digital comparativa da expressão tecidual da proteína cerbB-2 em mulheres portadoras de doenças tumorais da mama
    Veiga, RKA; Melo-Júnior, MR; Araújo, F; Jorge, LS; Lins, CAB; Teles, N
  • A comparison of manual and automated methods of quantitation of estrogen/progesterone receptor expression in breast carcinoma
    Vijayashree, R; Aruthra, P; Rao, KR
  • Generalizing cell segmentation and quantification
    Wang, Z; Li, H
  • Estrogen and progesterone receptor testing in breast carcinoma: concordance of results between local and reference laboratories in Brazil
    Wludarski, SC; Lopes, LF; Duarte, IX; Carvalho, FM; Weiss, L; Bacchi, CE