Blind Biobanking of the Prostatectomy Specimen: Critical Evaluation of the Existing Techniques and Development of the New 4-Level Tissue Extraction Model With High Sampling Efficacy.

BACKGROUND: Fresh tissue is mandatory to perform high-quality translation studies. Several models for tissue extraction from prostatectomy specimens without guidance by frozen sections are already introduced. However, little is known about the sampling efficacy of these models, which should provide representative tissue in adequate volumes, account for multifocality and heterogeneity of tumor, not violate the routine final pathological examination, and perform quickly without frozen section-based histological control. The aim of the study was to evaluate the sampling efficacy of the existing tissue extraction models without guidance by frozen sections ("blind") and to develop an optimized model for tissue extraction. METHODS: Five hundred thirty-three electronic maps of the tumor distribution in prostates from a single-center cohort of the patients subjected to radical prostatectomy were used for analysis. Six available models were evaluated in silico for their sampling efficacy. Additionally, a novel model achieving the best sampling efficacy was developed. RESULTS: The available models showed high efficacies for sampling "any part" from the tumor (up to 100%), but were uniformly low in efficacy to sample all tumor foci from the specimens (with the best technique sampling only 51.6% of the all tumor foci). The novel 4-level extraction model achieved a sampling efficacy of 93.1% for all tumor foci. CONCLUSIONS: The existing "blind" tissue extraction models from prostatectomy specimens without frozen sections control are suitable to target tumor tissues but these tissues do not represent the whole tumor. The novel 4-level model provides the highest sampling efficacy and a promising potential for integration into routine. Prostate 77: 396-405, 2017. © 2016 Wiley Periodicals, Inc.