PURPOSE: The true accuracy of different biopsy strategies for detecting clinically significant prostate cancer is unknown, given the positive evaluation bias required for verification by radical prostatectomy. To evaluate how well different biopsy strategies perform at detecting clinically significant prostate cancer we used computer simulation in cystoprostatectomy cases with cancer. MATERIALS AND METHODS: A computer simulation study was performed on prostates acquired at radical cystoprostatectomy. A total of 346 prostates were processed and examined for prostate cancer using 3 mm whole mount slices. The 96 prostates that contained cancer were digitally reconstructed. Biopsy simulations incorporating various degrees of random localization error were performed using the reconstructed 3-dimensional prostate computer model. Each biopsy strategy was simulated 500 times. Two definitions of clinically significant prostate cancer were used to define the reference standard, including definition 1--Gleason score 7 or greater, and/or lesion volume 0.5 ml or greater and definition 2--Gleason score 7 or greater, and/or lesion volume 0.2 ml or greater. RESULTS: A total of 215 prostate cancer foci were present. The ROC AUC to detect and rule out definition 1 prostate cancer was 0.69, 0.75, 0.82 and 0.91 for 12-core transrectal ultrasound biopsy with a random localization error of 15 and 10 mm, 14-core transrectal ultrasound biopsy and template prostate mapping using a 5 mm sampling frame, respectively. CONCLUSIONS: To our knowledge our biopsy simulation study is the first to evaluate the performance of different sampling strategies to detect clinically important prostate cancer in a population that better reflects the demographics of a screened cohort. Compared to other strategies standard transrectal ultrasound biopsy performs poorly for detecting clinically important cancer. Marginal improvement can be achieved using additional cores placed anterior but the performance attained by template prostate mapping is optimal.
PURPOSE: The true accuracy of different biopsy strategies for detecting clinically significant prostate cancer is unknown, given the positive evaluation bias required for verification by radical prostatectomy. To evaluate how well different biopsy strategies perform at detecting clinically significant prostate cancer we used computer simulation in cystoprostatectomy cases with cancer. MATERIALS AND METHODS: A computer simulation study was performed on prostates acquired at radical cystoprostatectomy. A total of 346 prostates were processed and examined for prostate cancer using 3 mm whole mount slices. The 96 prostates that contained cancer were digitally reconstructed. Biopsy simulations incorporating various degrees of random localization error were performed using the reconstructed 3-dimensional prostate computer model. Each biopsy strategy was simulated 500 times. Two definitions of clinically significant prostate cancer were used to define the reference standard, including definition 1--Gleason score 7 or greater, and/or lesion volume 0.5 ml or greater and definition 2--Gleason score 7 or greater, and/or lesion volume 0.2 ml or greater. RESULTS: A total of 215 prostate cancer foci were present. The ROC AUC to detect and rule out definition 1 prostate cancer was 0.69, 0.75, 0.82 and 0.91 for 12-core transrectal ultrasound biopsy with a random localization error of 15 and 10 mm, 14-core transrectal ultrasound biopsy and template prostate mapping using a 5 mm sampling frame, respectively. CONCLUSIONS: To our knowledge our biopsy simulation study is the first to evaluate the performance of different sampling strategies to detect clinically important prostate cancer in a population that better reflects the demographics of a screened cohort. Compared to other strategies standard transrectal ultrasound biopsy performs poorly for detecting clinically important cancer. Marginal improvement can be achieved using additional cores placed anterior but the performance attained by template prostate mapping is optimal.
Authors: Eva M Serrao; Tristan Barrett; Karan Wadhwa; Deepak Parashar; Julia Frey; Brendan C Koo; Anne Y Warren; Andrew Doble; Christof Kastner; Ferdia A Gallagher Journal: Can Urol Assoc J Date: 2015-12-14 Impact factor: 1.862
Authors: Javier Romero-Otero; Borja García-Gómez; José M Duarte-Ojeda; Alfredo Rodríguez-Antolín; Antoni Vilaseca; Sigrid V Carlsson; Karim A Touijer Journal: Int J Urol Date: 2015-11-30 Impact factor: 3.369
Authors: Ghassan A Barayan; Armen G Aprikian; James Hanley; Wassim Kassouf; Fadi Brimo; Louis R Bégin; Simon Tanguay Journal: World J Urol Date: 2014-11-12 Impact factor: 4.226
Authors: B Calio; A Sidana; D Sugano; S Gaur; A Jain; M Maruf; S Xu; P Yan; J Kruecker; M Merino; P Choyke; B Turkbey; B Wood; P Pinto Journal: Prostate Cancer Prostatic Dis Date: 2017-08-01 Impact factor: 5.554
Authors: F Distler; J P Radtke; C Kesch; M Roethke; H-P Schlemmer; W Roth; M Hohenfellner; B Hadaschik Journal: Urologe A Date: 2016-02 Impact factor: 0.639