PURPOSE: The probability of detecting small foci of prostate cancer is related to the amount of tissue represented. When multiple prostate biopsy cores are embedded in a single block, less tissue is evaluated because it is difficult to embed all cores in a single plane for optimal tissue representation. A computer simulation of sectioning biopsy cores was devised to examine the total surface area available at various angles of embedding and predict the ability to detect small tumor foci. MATERIALS AND METHODS: The computer simulation of biopsy core was done using commercially available software. Biopsy cores were represented as 3-dimensional cylindrical objects and the cutting blade was represented by a 2-dimensional plane. The intersection of the plane and cylinder represented the cut surface, which varied depending on cylinder angle and position. The simulation program calculates available surface area. RESULTS: Maximal surface area was obtained when the plane was horizontal to the long axis of the core. Any divergence of the cylinder from horizontal decreased the represented area. A single section through a 1 x 15 mm. biopsy core at 0 degrees yielded a surface area of 15 mm(2). The surface area was decreased to 13.3, 9.01 and 4.52 mm(2) at 3, 5 and 10 degrees, respectively. At a small focus of 0.6 mm. there was 100% detection under optimal circumstance, which decreased to 56.2% and 27.9% as the angle increased to 3 and 10 degrees, respectively. CONCLUSIONS: Optimal sectioning, that is maximal surface area, of the core is obtained when a biopsy core is sectioned at a 0-degree angle, that is horizontal to its long axis. It is much more likely when each biopsy core is embedded individually. When multiple cores are embedded together, it is difficult to position all cores in the same plane since cores move to different planes and the cut surface of the cylinders substantially decreases. Thus, for optimal surface representation and cancer detection embedding individual cores is appropriate.
PURPOSE: The probability of detecting small foci of prostate cancer is related to the amount of tissue represented. When multiple prostate biopsy cores are embedded in a single block, less tissue is evaluated because it is difficult to embed all cores in a single plane for optimal tissue representation. A computer simulation of sectioning biopsy cores was devised to examine the total surface area available at various angles of embedding and predict the ability to detect small tumor foci. MATERIALS AND METHODS: The computer simulation of biopsy core was done using commercially available software. Biopsy cores were represented as 3-dimensional cylindrical objects and the cutting blade was represented by a 2-dimensional plane. The intersection of the plane and cylinder represented the cut surface, which varied depending on cylinder angle and position. The simulation program calculates available surface area. RESULTS: Maximal surface area was obtained when the plane was horizontal to the long axis of the core. Any divergence of the cylinder from horizontal decreased the represented area. A single section through a 1 x 15 mm. biopsy core at 0 degrees yielded a surface area of 15 mm(2). The surface area was decreased to 13.3, 9.01 and 4.52 mm(2) at 3, 5 and 10 degrees, respectively. At a small focus of 0.6 mm. there was 100% detection under optimal circumstance, which decreased to 56.2% and 27.9% as the angle increased to 3 and 10 degrees, respectively. CONCLUSIONS: Optimal sectioning, that is maximal surface area, of the core is obtained when a biopsy core is sectioned at a 0-degree angle, that is horizontal to its long axis. It is much more likely when each biopsy core is embedded individually. When multiple cores are embedded together, it is difficult to position all cores in the same plane since cores move to different planes and the cut surface of the cylinders substantially decreases. Thus, for optimal surface representation and cancer detection embedding individual cores is appropriate.
Authors: Marc A Bjurlin; H Ballentine Carter; Paul Schellhammer; Michael S Cookson; Leonard G Gomella; Dean Troyer; Thomas M Wheeler; Steven Schlossberg; David F Penson; Samir S Taneja Journal: J Urol Date: 2013-02-26 Impact factor: 7.450
Authors: David Parada; Nahum Calvo; Karla Peña; Vanesa Morente; Rosana Queralt; Pilar Hernandez; Francesc Riu Journal: Prostate Cancer Date: 2011-06-09