OBJECTIVE: The purpose of this study was to determine whether several quantitative ultrasonographic measures have potential to discriminate prostate cancer from normal prostate and to determine the best combination of these measures. The true spatial distributions of cancer within the prostates studied were obtained histologically after radical prostatectomy. The relationship between Doppler ultrasonography and microvessel count was also investigated. METHODS: Three-dimensional Doppler ultrasonographic data were acquired from 39 patients before radical prostatectomy. The removed prostate was sectioned, and whole-mount hematoxylineosin-stained slides were used to identify all regions of cancer within each prostate. These histologic and ultrasonographic data were spatially registered. Doppler ultrasonographic measures were calculated within uniformly sized three-dimensional regions that were either entirely cancerous or noncancerous, and receiver operating characteristic analysis was performed on the results. Microvessel counts were made within each contiguous cancerous region and correlated with ultrasonographic measures. RESULTS: Color pixel density was the best simple measure for discriminating prostate cancer (accuracy, 80%). The mean power mode value (normalized mean power in color pixels) was inversely related to cancer with an accuracy of 1--normalized mean power in color pixels = 65% (low mean power is more cancerous). When color pixel density was combined with the normalized mean power in color pixels, its accuracy improved slightly to 84%. The peak microvessel count had a negative correlation with color pixel density as well as with cancer stage. CONCLUSION: Doppler ultrasonography does provide discriminatory information for prostate cancer, with color pixel density being the most promising measure.
OBJECTIVE: The purpose of this study was to determine whether several quantitative ultrasonographic measures have potential to discriminate prostate cancer from normal prostate and to determine the best combination of these measures. The true spatial distributions of cancer within the prostates studied were obtained histologically after radical prostatectomy. The relationship between Doppler ultrasonography and microvessel count was also investigated. METHODS: Three-dimensional Doppler ultrasonographic data were acquired from 39 patients before radical prostatectomy. The removed prostate was sectioned, and whole-mount hematoxylineosin-stained slides were used to identify all regions of cancer within each prostate. These histologic and ultrasonographic data were spatially registered. Doppler ultrasonographic measures were calculated within uniformly sized three-dimensional regions that were either entirely cancerous or noncancerous, and receiver operating characteristic analysis was performed on the results. Microvessel counts were made within each contiguous cancerous region and correlated with ultrasonographic measures. RESULTS: Color pixel density was the best simple measure for discriminating prostate cancer (accuracy, 80%). The mean power mode value (normalized mean power in color pixels) was inversely related to cancer with an accuracy of 1--normalized mean power in color pixels = 65% (low mean power is more cancerous). When color pixel density was combined with the normalized mean power in color pixels, its accuracy improved slightly to 84%. The peak microvessel count had a negative correlation with color pixel density as well as with cancer stage. CONCLUSION: Doppler ultrasonography does provide discriminatory information for prostate cancer, with color pixel density being the most promising measure.