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

Overview

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 date

  • January 1, 2002

Research

keywords

  • Brachytherapy
  • Neural Networks, Computer
  • Prostatic Neoplasms

Identity

Scopus Document Identifier

  • 0013290186

Digital Object Identifier (DOI)

  • 10.1016/s1538-4721(02)00002-8

PubMed ID

  • 15062187

Additional Document Info

volume

  • 1

issue

  • 1