Prostate imaging based on RF spectrum analysis and non-linear classifiers for guiding biopsies and targeting radiotherapy

Published

Other Article

Conventional B-mode ultrasound is the standard means of imaging the prostate for guiding prostate biopsies and planning radiotherapy (i.e., brachytherapy and external-beam radiation) of prostate cancer (CaP). Yet B-mode images essentially do not allow visualization of cancerous lesions of the prostate. Ultrasonic tissue-typing imaging based on spectrum analysis of radio-frequency (RF) echo signals has shown promise for overcoming the limitations of B-mode imaging in distinguishing cancerous from common forms of non-cancerous prostate tissue. Such tissue typing utilizes non-linearmethods, such as nearest-neighbor and neural-network techniques, to classify tissues based on spectral-parameter and clinical-variable values. Our research seeks to develop imaging techniques based on these methods for the purpose of improving the guidance of prostate biopsies and the targeting of brachytherapy and external-beam radiotherapy of prostate cancer. Images based on these methods have been imported into real-time instrumentation for biopsy guidance and into commercial dose-planning software for real-time brachytherapy. Three-dimensional renderings show locations and volumes of cancer foci. These methods offer exciting possibilities for effective low-cost depiction of prostate cancer in real-time and off-line images. Real-time imaging showing cancerous regions of the prostate can be of value in directing biopsies, determining whether biopsy is warranted, assisting in clinical staging, targeting brachytherapy, planning conformal external-beam radiation procedures, and monitoring treatment.

Full Text

Duke Authors

Cited Authors

  • Feleppa, EJ; Ketterling, JA; Kalisz, A; Urban, S; Porter, CR; Gillespie, J; Schiff, PB; Ennis, RD; Wuu, CS; Moul, JW; Sesterhenn, IA; Scardino, PT

Published Date

  • January 1, 2001

Published In

Volume / Issue

  • 4325 /

Start / End Page

  • 371 - 379

International Standard Serial Number (ISSN)

  • 0277-786X

Digital Object Identifier (DOI)

  • 10.1117/12.428213

Citation Source

  • Scopus