Application of spectrum analysis and neural-network classification to imaging for targeting and monitoring treatment 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 no imaging modality, including B-mode images, reliably shows cancerous lesions of the prostate. Tissue-typing imaging based on spectrum analysis of ultrasonic radio-frequency (RF) echo signals may be able to overcome the limitations of conventional imaging modalities for visualizing prostate tumors. Such tissue typing utilizes 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