Ultrasonic spectrum-analysis and neural-network classification as a basis for ultrasonic imaging to target brachytherapy of prostate cancer.
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.
Feleppa
Ernest J
EJ
Biomedical Engineering Laboratories, Riverside Research Institute, New York, NY 10038, USA. feleppa@rrinyc.org
Ennis
Ronald D
RD
Schiff
Peter B
PB
Wuu
Cheng-Shie
CS
Kalisz
Andrew
A
Ketterling
Jeffery
J
Urban
Stella
S
Liu
Tian
T
Fair
William R
WR
Porter
Christopher R
CR
Gillespie
John R
JR
D001918:Brachytherapy / Q000379:methods*; D006801:Humans; D008297:Male; D016571:Neural Networks, Computer; D011471:Prostatic Neoplasms / Q000145:classification / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D014463:Ultrasonography / Q000379:methods