Prostate imaging based on rf spectrum analysis and nonlinear classifiers for guiding biopsies and targeting radiotherapy

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Abstract
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-linear methods, 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. 3D 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.

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