Computer simulation of the probability of detecting low volume carcinoma of the prostate with six random systematic...

Six random systematic core biopsies (SRSCB) of the prostate (biopsies from apex, middle, and base of each lobe) have been commonly used in detection of prostate carcinoma. The objective of this study was to verify the validity of the SRSCB technique in detecting cancer in prostates with low-volume tumor (less than 6 cc).

We developed a computer model of the prostate to simulate the SRSCB technique. The data for development of this model were taken from 159 radical prostatectomy specimens in which 112 patients had tumor volumes measured and in which 91 prostates had tumors with volumes less than 6 cc (by whole-mount sectioning).

The simulation shows that only 20.3% of the simulated prostates, with total aggregate tumor volume between 0.034 and 5.1 cc, had a tumor distribution for which the SRSCB technique has a 95% probability of detecting the tumor. In fact, 26.8% had a tumor distribution that was completely disjointed from the six recommended biopsy regions. To compare these results with other possible occurrence, various biases for the angle of biopsy and the distribution of cancer foci were incorporated into the model. Study results should be viewed with the understanding that any simulated model has its limitations. In our simulated model, the shape of the simulated tumor foci (spherical) does not represent all the possible shapes of prostate cancer. However, these results indicate that detection of cancer with biopsies taken from the apex, middle, and base of each lobe of a prostate with tumor volumes of less than 6 cc may not be as effective as it is in prostates with larger tumor volumes or patients with an abnormal digital rectal examination. The study of bias models suggests that the distributional pattern of cancerous foci can have a significant impact on the effectiveness of a given biopsy strategy.

We concluded that future attempts to improve systematic biopsy strategies for detection of low-volume cancer should include biomechanical characteristics of prostate cancer, including gland volume and tumor distribution. Driven by the conclusions from this idealized model, we have developed a three-dimensional model of the prostate gland from its whole-mount histologic maps. It is anticipated that this continuing investigation will lead to realistic guidelines for improving biopsy techniques.