Quantitative nuclear morphometry, Markovian texture descriptors, and DNA content captured on a CAS-200 Image analysis system, combined with @entity1364 and @entity1722 /neu immunohistochemistry for prediction of XXXX progression.

@entity1 @entity1364 @entity263 @entity1885 @entity5 @entity982 @entity1722
One hundred and twenty-four localized @entity263 @entity1 operated on at Johns Hopkins Hospital (JHH) since 1975 were identified. The sample was optimized for evaluation of @entity263 progression. Based upon accurate clinical histories, these radical prostatectomy @entity1 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 @entity1 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 @entity982 -embedded specimens, several five micron sections were cut and placed on Probe-On slides; one slide was H_E-stained and the other was Feulgen-stained. The H_E 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 1.2 beta, was used to capture the Feulgen-stained images and to perform the calculations. From the "dotted" areas, 150 @entity5 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- @entity1885 complex stain to detect and quantitate @entity5 cells binding monoclonal antibodies directed against @entity1364 ( @entity1364 ) and @entity1722 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 = < 0.0001), @entity1722 antigenicity (p = 0.0147), CAS-200 DNA ploidy (p = 0.008), and twelve Markovian nuclear texture and shape features (p = < 0.0001), whereas @entity1364 (p = 0.160) failed. The optimal set of nuclear morphometry progression tumor features were selected using backward stepwise logistic regression estimate analysis which drops variables due to collinearity. Although post-operative Gleason score is a strong univariate predictor of progression, DNA ploidy and @entity1722 /neu contributed significantly to further stratification of higher risk groups within the low Gleason score subpopulation. The best Markovian features combined with post-operative Gleason score generated sensitivity = 90%, specificity = 96%, positive predictive value = 94%, negative predictive value = 93% and the area under the receiver operator curve was 0.975.
