Risk biomarker assessment for breast cancer progression: replication precision of nuclear morphometry

N.M. Poulin, A. Frost, A. Carraro, E.C. Mommers, M. Guillaud, P.J. van Diest, W. Grizzle, S. Beenken

Research output: Contribution to journalArticleAcademicpeer-review


Nuclear morphometry is a method for quantitative measurement of histopathologic changes in the appearance of stained cell nuclei. Numerous studies have indicated that these assessments may provide clinically relevant information related to the degree of progression and malignant potential of breast neoplasia. Nuclear features are derived from computerized analysis of digitized microscope images, and a quantitative Feulgen stain for DNA was used. Features analyzed included: (1) DNA content; (2) nuclear size and shape; and (3) texture features, describing spatial features of chromatin distribution. In this study replicated measurements are described on a series of 54 breast carcinoma specimens of differing pathologic grades. Duplicate measurements were performed using two serial sections, which were processed and analyzed separately. The value of a single feature measurement, the nuclear area profile, was shown to be the strongest indicator of progression. A quantitative nuclear grade was derived and shown to be strongly correlated with not only the pathologic nuclear grade, but also with tubule formation, mitotic grade, and with the overall histopathologic grade. Analysis of replication precision showed that the standard methods of the histopathology laboratory, if practiced in a uniform manner, are sufficient to ensure reproducibility of these assessments. We argue that nuclear morphometry provides a standardized and reproducible framework for quantitative pathologic assessments.

Original languageEnglish
Pages (from-to)129-138
Number of pages10
JournalAnalytical Cellular Pathology
Issue number3
Publication statusPublished - 2003


  • Algorithms
  • Biomarkers, Tumor
  • Breast Neoplasms
  • Cell Nucleus
  • Chromatin
  • DNA, Neoplasm
  • Female
  • Humans
  • Prognosis
  • Reproducibility of Results
  • Risk Factors


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