Ultrasonic spectrum-analysis and neural-network classification as a basis for ultrasonic imaging to target brachytherapy of prostate cancer

Brachytherapy. 2002;1(1):48-53. doi: 10.1016/s1538-4721(02)00002-8.

Abstract

Conventional B-mode ultrasound is the standard means of imaging the prostate for guiding prostate biopsies and planning brachytherapy of prostate cancer. Yet B-mode images do not allow adequate visualization of cancerous lesions of the prostate. Ultrasonic tissue-typing imaging based on spectrum analysis of radiofrequency echo signals has shown promise for overcoming the limitations of B-mode imaging for visualizing prostate tumors. Tissue typing based on radiofrequency spectrum analysis uses nonlinear methods, such as neural networks, to classify tissue by using spectral-parameter and clinical-variable values. Two- and three-dimensional images based on these methods show potential for improving the guidance of prostate biopsies and the targeting of radiotherapy of prostate cancer. Two-dimensional images have been imported into instrumentation for real-time biopsy guidance and into commercial dose-planning software for brachytherapy planning. Three-dimensional renderings seem to be capable of depicting locations and volumes of cancer foci.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Brachytherapy / methods*
  • Humans
  • Male
  • Neural Networks, Computer*
  • Prostatic Neoplasms / classification
  • Prostatic Neoplasms / diagnostic imaging*
  • Prostatic Neoplasms / radiotherapy*
  • Ultrasonography / methods