Advanced ultrasonic tissue-typing and imaging based on radio-frequency spectrum analysis and neural-network classification for guidance of therapy and biopsy procedures

Abstract Conventional B-mode ultrasound is the standard means of imaging the prostate for guiding prostate biopsies and planning brachytherapy of prostate cancer (CaP). Yet B-mode images 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 for visualizing prostate tumors. Such tissue-typing utilizes non-linear methods, such as neural-networks, to classify tissue based on spectral-parameter and clinical-variable values. Tissue-type images based on these methods are intended to improve guidance of prostate biopsies and 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 show locations and volumes of cancer foci.