Recent developments in tissue-type imaging (TTI) for planning and monitoring treatment of prostate cancer.

Because current methods of imaging prostate cancer are inadequate, biopsies cannot be effectively guided and treatment cannot be effectively planned and targeted. Therefore, our research is aimed at ultrasonically characterizing cancerous prostate tissue so that we can image it more effectively and thereby provide improved means of detecting, treating and monitoring prostate cancer. We base our characterization methods on spectrum analysis of radiofrequency (rf) echo signals combined with clinical variables such as prostate-specific antigen (PSA).

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.

Role of advanced 2 and 3-dimensional ultrasound for detecting prostate cancer.

Purpose: We explored the clinical usefulness of spectrum analysis and neural networks for classifying prostate tissue and identifying prostate cancer in patients undergoing transrectal ultrasound for diagnostic or therapeutic reasons.

Materials And Methods: Data on a cohort of 215 patients who underwent transrectal ultrasound guided prostate biopsies at Memorial-Sloan Kettering Cancer Center, New York, New York were included in this study. Radio frequency data necessary for 2 and 3-dimensional (D) computer reconstruction of the prostate were digitally recorded at transrectal ultrasound and prostate biopsy.