Quantitative nuclear morphometry, Markovian texture descriptors, and DNA content captured on a CAS-200 image analysis system, combined with PCNA and HER-2/neu immunohistochemistry for prediction of prostate cancer progression

R. W. Veltri, Alan Wayne Partin, Jonathan Ira Epstein, G. M. Marley, C. M. Miller, D. S. Singer, K. P. Patton, S. R. Criley, D. S. Coffey

Research output: Contribution to journalArticle


One hundred and twenty-four localized prostate cancer patients operated on at Johns Hopkins Hospital (JHH) since 1975 were identified. The sample was optimized for evaluation of prostate cancer progression. Based upon accurate clinical histories, these radical prostatectomy patients included 50 progressors and 74 non-progressors using appearance of serum PSA as an indication of recurrence (mean follow-up = 8.6 ± 1.8 years, range 7-15 years). All patients included in the study had no involvement of their seminal vesicles or lymph nodes at the time of prostatectomy. Average time to progression was 3.6 ± 2 years, range of 1-8 years. Using paraffin-embedded specimens, several five micron sections were cut and placed on Probe-On® slides; one slide was HandE-stained and the other was Feulgen-stained. The HandE and Feulgen-stained slides were screened and 'dotted' by pathologists at JHH and CytoDynostics, Inc. A CAS-200 Image analysis system (Cell Image Systems, Elmhurst, IL) equipped with a Cell Measurement Program Version 1.2β, was used to capture the Feulgen-stained images and to perform the calculations. From the 'dotted' areas, 150 cancer cells were selected for measurement of DNA content and 27 nuclear morphometric shape and size factors, including 21 Markovian chromatin texture variables. Additional sections were used for immunochemistry staining with an alkaline phosphatase streptavidin-biotin complex stain to detect and quantitate cancer cells binding monoclonal antibodies directed against proliferating cell nuclear antigen (PCNA) and HER-2/neu antigen. All data were entered into a statistical program (STATA®) for further analysis and univariate and multivariate statistical analysis was performed using logistic regression and its stepwise variant. The biomarkers of greatest utility to detect progressors when analyzed univariately included post-operative Gleason score (p =

Original languageEnglish (US)
Pages (from-to)249-258
Number of pages10
JournalJournal of Cellular Biochemistry
Issue numberSUPPL. 19
StatePublished - 1994
Externally publishedYes



  • Chromatin texture
  • DNA ploidy
  • Nuclear morphometry
  • Prostate cancer progression
  • Tumor markers

ASJC Scopus subject areas

  • Biochemistry
  • Cell Biology

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