Abstract

Background: Benign prostate hyperplasia (BPH) is the most common benign disease of the human prostate. The comparison between global versus local changes in spatial patterns of pathological lesions provoked a growing interest in some fields such as neuropathology. To date, there is little data on this subject in prostatic pathology. Given the interest of local parameters to distinguish between normal and pathological structures, the present study will apply first and second order stereological tools to find out if the cytokeratin18 (ck18) immunoexpression shows relevant local changes in BPH compared to normal prostate, independently if global estimates were similar in both groups. Methods: To verify if the global and local changes in immuno-expression of ck18 are relevant to ascertain differences between normal (CTR) and BPH cases, the following parameters will be applied: Volume fraction of epithelium immunostained for ck18 (VV ck18), both in global and local estimates; dispersion indices of VV ck18; estimates of local variance of VV ck18 (positional and of scale) using wavelet analysis; and lacunarity analysis to measure the tissue heterogeneity. Then, the set of values from the parameters studied that show significant differences between CTR and BPH will be employed to perform stepwise linear discriminant analyses to determine if locally estimated parameters were able to classify accurately the cases in CTR and BPH groups. Results and Conclusions: The findings of the present study indicate that changes in the expression of ck18 by the hyperplastic prostatic epithelium are not homogeneous. This limits the use of a single biopsy based markers to predict biological behavior in BPH. On the other hand, the local changes in the expression of ck18 are more evident in terms of VV ck18 and its local variability, whereas other parameters that are useful in other pathologies, such as lacunarity, are less relevant In prostatic hyperplasia.

Highlights

  • Benign prostate hyperplasia (BPH) is the most common benign disease of human prostate [1] [2], representing approximately 50% of medical consultations made by urological disease [3] [4]. the pathogenesis of BPH is unclear, it is known to be multifactorial; being necessary the presence of two factors for prostate growth occurs: the androgen stimulus and age [5]

  • Given the interest of local parameters to distinguish between normal and pathological structures, the present study will apply first and second order stereological tools to find out if the cytokeratin18 immunoexpression shows relevant local changes in BPH compared to normal prostate, independently if global estimates were similar in both groups

  • For example: The study of the distribution of microvessels in normal and pathological prostate [21], the distribution of cell nuclei populations in prostatic adenocarcinoma and prostatic intraepithelial neoplasia (PIN) [22], the estimation of K function and isotropy of normal prostatic acini compared to cancer [23], and the local changes of glandular pattern in BPH compared to normal prostate [24]

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Summary

Introduction

Benign prostate hyperplasia (BPH) is the most common benign disease of human prostate [1] [2], representing approximately 50% of medical consultations made by urological disease [3] [4]. For example: The study of the distribution of microvessels in normal and pathological prostate [21], the distribution of cell nuclei populations in prostatic adenocarcinoma and PIN [22], the estimation of K function and isotropy of normal prostatic acini compared to cancer [23], and the local changes of glandular pattern in BPH compared to normal prostate [24]. In some of these studies, several discrepancies between global and local results were detected. 2: Dispersion indices of global VV ck, as Morisita index [25] [26]. 3: Estimates of the local variance of VV ck (positional and of scale) using wavelet analysis [27] [28] [29] [30]. 4: Lacunarity analysis in order to measure the distribution of gap sizes interspersed among the immunostained acini (i.e.: tissue heterogeneity) [31]

Material
Processing of the Tissues
Immunohistochemistry
Data Acquisition
Quantitative Measurements
Statistical Analysis
Local Quantitative Findings
Discriminant Analysis
Discussion
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