This is a proposal for a 5-year continuation of a study to show feasibility of differentiating cancerous from noncancerous tissues in the prostate using spectrum analysis of ultrasonic pulse-echo signals. Results from studies conducted with current support show the spectrum analysis methods of the investigators provide more than a 50% improvement in the sensitivity of ultrasound-guided biopsies. Further studies are proposed to improve: 1) biopsy guidance for early detection and timely treatment of prostate cancer, 2) staging for treatment planning and monitoring, and 3) understanding of the mechanisms of ultrasonic scattering in prostate tissue for advancement of methods for distinguishing cancerous from noncancerous prostate tissue. This three-fold purpose is consistent with priorities defined in the August 1998 Report of the Prostate Cancer Review Group (PRG) to the Advisory Committee of the Director of the National Cancer Institute. The proposed studies will be undertaken by a consortium that consists of the applicant organization, the Memorial Sloan-Kettering Cancer Center (MSKCC), as in prior studies, and the Walter Reed Army Medical Center (WRAMC) with its affiliated Armed Forces Institute of Pathology (AFIP). The basic method of data collection for spectrum analysis will be the same as in the current studies as will the derivation of parameters that describe scattering but new analysis based on parameter classifications will be employed in the studies for which this proposal seeks funding. An important part of the research is the presentation of tissue-type information in clinical useful images. These methods are nonlinear nearest-neighbor and neural-network tools. The efficacy of the derived parameters and images will be assessed using standard ROC methods and the classification techniques underlying them will include new non-linear methods based on nearest-neighbor and neural network tools.
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| Feleppa, Ernest J; Alam, S Kaisar; Deng, Cheri X (2002) Emerging ultrasound technologies for early markers of disease. Dis Markers 18:249-68 |
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| Feleppa, E J; Ennis, R D; Schiff, P B et al. (2001) Spectrum-analysis and neural networks for imaging to detect and treat prostate cancer. Ultrason Imaging 23:135-46 |
| Feleppa, E J; Fair, W R; Liu, T et al. (2000) Three-dimensional ultrasound analyses of the prostate. Mol Urol 4:133-9;discussion 141 |
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