Investigating the distribution of prostate cancer using three-dimensional computer simulation.

Published

Journal Article

The objective of this work was to investigate the distribution of prostate cancer using three-dimensional (3-D) computer simulation. Two hundred and eighty-one 3-D computer prostate models were constructed from radical prostatectomy specimens. An algorithm was developed which divided each model into 24 symmetrical regions, and it then detected the presence of tumor within an individual region. The distribution rate of prostate cancer was assessed within each region of all 281 prostate models, and the difference between the rates was statistically analyzed using Mantel-Haenszel methodology. There was a statistically significant higher distribution rate of cancer in the posterior half (57.2%) compared to the anterior half ( 40.5%; P=0.001). The base regions (36.8%) had a statistically significant lower distribution rate than either the mid regions (56.3%; P=0.001) or the apical regions (53.5%; P=0.001). The mid regions did have a statistically significant higher distribution rate compared to the apical regions (P=0.032). There was no statistically significant difference between the distribution rate on the left half (48.5%) compared to that on the right half (49.2%; P=0.494). The spatial distribution of prostate cancer can be analyzed using 3-D computer prostate models. The results illustrate that prostate cancer is least commonly located in the anterior half and base regions of the prostate. Through an analysis of the spatial distribution of prostate cancer, we believe that new optimal biopsy strategies and techniques can be developed.

Full Text

Duke Authors

Cited Authors

  • Opell, MB; Zeng, J; Bauer, JJ; Connelly, RR; Zhang, W; Sesterhenn, IA; Mun, SK; Moul, JW; Lynch, JH

Published Date

  • 2002

Published In

Volume / Issue

  • 5 / 3

Start / End Page

  • 204 - 208

PubMed ID

  • 12496982

Pubmed Central ID

  • 12496982

International Standard Serial Number (ISSN)

  • 1365-7852

Digital Object Identifier (DOI)

  • 10.1038/sj.pcan.4500577

Language

  • eng

Conference Location

  • England