Optimized prostate biopsy via a statistical atlas of cancer spatial distribution

Dinggang Shen, Zhiqiang Lao, Jianchao Zeng, Wei Zhang, Isabel A. Sesterhenn, Leon Sun, Judd W. Moul, Edward H. Herskovits, Gabor Fichtinger, Christos Davatzikos

Research output: Contribution to journalArticle

65 Citations (Scopus)

Abstract

A methodology is presented for constructing a statistical atlas of spatial distribution of prostate cancer from a large patient cohort, and it is used for optimizing needle biopsy. An adaptive-focus deformable model is used for the spatial normalization and registration of 100 prostate histological samples, which were provided by the Center for Prostate Disease Research of the US Department of Defense, resulting in a statistical atlas of spatial distribution of prostate cancer. Based on this atlas, a statistical predictive model was developed to optimize the needle biopsy sites, by maximizing the probability of detecting cancer. Experimental results using cross-validation show that the proposed method can detect cancer with a 99% success rate using seven needles, in these samples.

Original languageEnglish
Pages (from-to)139-150
Number of pages12
JournalMedical Image Analysis
Volume8
Issue number2
DOIs
Publication statusPublished - 2004 Jun 1

Keywords

  • Deformable registration
  • Image normalization
  • Image warping
  • Needle biopsy
  • Prostate cancer
  • Statistical atlas

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

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  • Cite this

    Shen, D., Lao, Z., Zeng, J., Zhang, W., Sesterhenn, I. A., Sun, L., Moul, J. W., Herskovits, E. H., Fichtinger, G., & Davatzikos, C. (2004). Optimized prostate biopsy via a statistical atlas of cancer spatial distribution. Medical Image Analysis, 8(2), 139-150. https://doi.org/10.1016/j.media.2003.11.002