Carcinoma of the prostate (CaP) is a disease characterized by its high prevalence, its heterogeneity of morphology and marked variation in its clinical behavior. In order to exert any meaningful impact on the clinical management of early stage disease - the potentially curable stage - information about the natural history of the disease is needed. Much of the existing knowledge regarding the natural history of early stage disease comes from morphometric studies. These studies, however, have used relatively primitive computer techniques. Likewise, biopsy techniques used for detection of CaP have been developed purely from clinical studies on patients. Advantage has not been taken of the power of modern computer modeling capabilities. Our group has developed an algorithm for the three dimensional reconstruction of prostatic histopathologic features obtained from sections of radical prostatectomy specimens. In the following proposal, we describe a series of studies using our model to: a) test the hypothesis that our new model will provide additional insight into the interrelationships of tumor volume, histologic grade and pathologic stage of CaP, b) test the hypothesis that improved biopsy strategies can be developed using computer modeling, and c) assess the ability of needle biopsies to evaluate the heterogeneity of prostatic carcinoma. The overall goal of this project is to provide a better understanding of the natural history of early stage CaP that should be of direct translational use in guiding the clinical management of patients afflicted with this common disease.
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| Werahera, Priya N; Sullivan, Kathryn; La Rosa, Francisco G et al. (2012) Optimization of prostate cancer diagnosis by increasing the number of core biopsies based on gland volume. Int J Clin Exp Pathol 5:892-9 |
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| Ruijter, E T; Werahera, P N; van de Kaa, C A et al. (1998) Detection of abnormal E-cadherin expression by simulated prostate biopsy. J Urol 160:1368-71;discussion 1371-2 |
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