Prognostic value of automatically extracted nuclear morphometric features in whole slide images of male breast cancer

Mitko Veta, Robert Kornegoor, André Huisman, Anoek H J Verschuur-Maes, Max A. Viergever, Josien P W Pluim, Paul J. Van Diest

Research output: Contribution to journalArticle

Abstract

Numerous studies have shown the prognostic significance of nuclear morphometry in breast cancer patients. Wide acceptance of morphometric methods has, however, been hampered by the tedious and time consuming nature of the manual segmentation of nuclei and the lack of equipment for high throughput digitization of slides. Recently, whole slide imaging became more affordable and widely available, making fully digital pathology archives feasible. In this study, we employ an automatic nuclei segmentation algorithm to extract nuclear morphometry features related to size and we analyze their prognostic value in male breast cancer. The study population comprised 101 male breast cancer patients for whom survival data was available (median follow-up of 5.7 years). Automatic segmentation was performed on digitized tissue microarray slides, and for each patient, the mean nuclear area and the standard deviation of the nuclear area were calculated. In univariate survival analysis, a significant difference was found between patients with low and high mean nuclear area (P0.022), while nuclear atypia score did not provide prognostic value. In Cox regression, mean nuclear area had independent additional prognostic value (P0.032) to tumor size and tubule formation. In conclusion, we present an automatic method for nuclear morphometry and its application in male breast cancer prognosis. The automatically extracted mean nuclear area proved to be a significant prognostic indicator. With the increasing availability of slide scanning equipment in pathology labs, these kinds of quantitative approaches can be easily integrated in the workflow of routine pathology practice.

Original languageEnglish (US)
Pages (from-to)1559-1565
Number of pages7
JournalModern Pathology
Volume25
Issue number12
DOIs
StatePublished - Dec 2012
Externally publishedYes

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Male Breast Neoplasms
Pathology
Equipment and Supplies
Workflow
Survival Analysis
Breast Neoplasms
Survival
Population
Neoplasms

Keywords

  • digital pathology
  • grading
  • image analysis
  • male breast cancer
  • whole slide images

ASJC Scopus subject areas

  • Pathology and Forensic Medicine

Cite this

Veta, M., Kornegoor, R., Huisman, A., Verschuur-Maes, A. H. J., Viergever, M. A., Pluim, J. P. W., & Van Diest, P. J. (2012). Prognostic value of automatically extracted nuclear morphometric features in whole slide images of male breast cancer. Modern Pathology, 25(12), 1559-1565. https://doi.org/10.1038/modpathol.2012.126

Prognostic value of automatically extracted nuclear morphometric features in whole slide images of male breast cancer. / Veta, Mitko; Kornegoor, Robert; Huisman, André; Verschuur-Maes, Anoek H J; Viergever, Max A.; Pluim, Josien P W; Van Diest, Paul J.

In: Modern Pathology, Vol. 25, No. 12, 12.2012, p. 1559-1565.

Research output: Contribution to journalArticle

Veta, M, Kornegoor, R, Huisman, A, Verschuur-Maes, AHJ, Viergever, MA, Pluim, JPW & Van Diest, PJ 2012, 'Prognostic value of automatically extracted nuclear morphometric features in whole slide images of male breast cancer', Modern Pathology, vol. 25, no. 12, pp. 1559-1565. https://doi.org/10.1038/modpathol.2012.126
Veta, Mitko ; Kornegoor, Robert ; Huisman, André ; Verschuur-Maes, Anoek H J ; Viergever, Max A. ; Pluim, Josien P W ; Van Diest, Paul J. / Prognostic value of automatically extracted nuclear morphometric features in whole slide images of male breast cancer. In: Modern Pathology. 2012 ; Vol. 25, No. 12. pp. 1559-1565.
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