COMPUTER MODELING OF PROSTATE BIOPSY - TUMOR SIZE AND LOCATION - NOT CLINICAL-SIGNIFICANCE - DETERMINE CANCER-DETECTION

Purpose: Sampling error is an inherent problem of prostate biopsy, and the determination of clinical significance based on biopsy results is problematic. We quantify the dimensions of these problems by computer simulation. Materials and Methods: We constructed 3-dimensional solid computer models of 59 autopsy prostates containing clinically undetec ted prostate cancer, and performed simulations of the standard prostat e biopsy method. Results: Biopsy simulation detected 19 tumors from th e 59 prostates, the majority of which were in the most accessible port ion of the prostate, the posterior peripheral zone. Using 0.5 cc or gr eater tumor volume or less than 0.5 cc and Gleason sum 7 or greater as criteria of significance, the model detected 58% (11 of 19) significa nt tumors and 20% (8 of 40) insignificant tumors. With 0.25 cc or grea ter tumor volume or less than 0.25 cc and Gleason sum 7 or greater as criteria 15 of 29 significant (52%) and 4 of 30 insignificant (13%) tu mors were detected. Among significant tumors defined by either volume criterion there was a statistical difference between detected and unde tected tumors in terms of mean tumor volume and mean ratio of tumor vo lume-to-prostate volume. Among insignificant tumors defined by either criterion there was no such difference. Conclusions: As much as 20 to 40% of currently detected prostate cancer may be histologically insign ificant, as 4 of 19 cancers were detected when 0.25 cc was used as vol ume determinant of clinical significance and 8 of 19 were detected whe n 0.5 cc volume was used. These tumors are detected randomly. On the o ther hand, perhaps only one-half to three-fourths of clinically signif icant prostate cancers are being detected, and then only because the v olume and anatomic location make them hard to miss.