2006年10月
Computer simulated additional deep apical biopsy enhances cancer detection in palpably benign prostate gland
INTERNATIONAL JOURNAL OF UROLOGY
- ,
- ,
- ,
- ,
- ,
- 巻
- 13
- 号
- 10
- 開始ページ
- 1290
- 終了ページ
- 1295
- 記述言語
- 英語
- 掲載種別
- DOI
- 10.1111/j.1442-2042.2006.01557.x
- 出版者・発行元
- BLACKWELL PUBLISHING
Objectives: The objective of this study was to use computer simulation to investigate the optimal biopsy scheme for enhancing the detection of cancer in palpably benign prostate glands.
Methods: The predominant distribution of palpably benign prostate cancer is anterior apex to mid-prostate. We used computer simulation to optimize apical samplings and to simulate the biopsy procedure, including angle and length. A total of 254 consecutive patients with palpably benign prostate glands underwent sextant biopsy plus two additional deep apical biopsies.
Results: Based on the computer simulation, lateral sextant and two additional medially located deep apical cores with a sagittal penetration angle of 80 degrees had the maximum cancer detection. Of the 254 patients, 58 (22.8%) had prostate cancer: 28 (48.3%) were positive only at the standard sextant sites, 12 (20.7%) were positive exclusively at the deep apical sites, and the remaining 18 (31.0%) were positive at both sites. Patients with gray-zone prostate-specific antigen (PSA) ranges of 4.1-10.0 ng/mL had increased cancer detection rates of 24% compared to sextant biopsy. Enhanced cancer detection by the deep apical biopsy was also evident in patients with a prostatic volume > 40 cm(3) (by 36.4%) and PSA 2.1-4.0 ng/mL (by 13.3%).
Conclusions: Using a computer simulation-based biopsy scheme with deep apical sampling cores enhanced the detection of prostate cancer in palpably benign glands, especially in men with PSA ranges of 4.1-10.0 ng/mL or a gland volume of > 40 cm(3). Our approach with fewer sampling cores may have been more cost-effective than other extensive biopsy schemes, but further studies with larger samples are warranted.
Methods: The predominant distribution of palpably benign prostate cancer is anterior apex to mid-prostate. We used computer simulation to optimize apical samplings and to simulate the biopsy procedure, including angle and length. A total of 254 consecutive patients with palpably benign prostate glands underwent sextant biopsy plus two additional deep apical biopsies.
Results: Based on the computer simulation, lateral sextant and two additional medially located deep apical cores with a sagittal penetration angle of 80 degrees had the maximum cancer detection. Of the 254 patients, 58 (22.8%) had prostate cancer: 28 (48.3%) were positive only at the standard sextant sites, 12 (20.7%) were positive exclusively at the deep apical sites, and the remaining 18 (31.0%) were positive at both sites. Patients with gray-zone prostate-specific antigen (PSA) ranges of 4.1-10.0 ng/mL had increased cancer detection rates of 24% compared to sextant biopsy. Enhanced cancer detection by the deep apical biopsy was also evident in patients with a prostatic volume > 40 cm(3) (by 36.4%) and PSA 2.1-4.0 ng/mL (by 13.3%).
Conclusions: Using a computer simulation-based biopsy scheme with deep apical sampling cores enhanced the detection of prostate cancer in palpably benign glands, especially in men with PSA ranges of 4.1-10.0 ng/mL or a gland volume of > 40 cm(3). Our approach with fewer sampling cores may have been more cost-effective than other extensive biopsy schemes, but further studies with larger samples are warranted.
Web of Science ® 被引用回数 : 9
Web of Science ® の 関連論文(Related Records®)ビュー
- リンク情報
-
- DOI
- https://doi.org/10.1111/j.1442-2042.2006.01557.x
- CiNii Articles
- http://ci.nii.ac.jp/naid/10018302863
- PubMed
- https://www.ncbi.nlm.nih.gov/pubmed/17010007
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000240742500006&DestApp=WOS_CPL
- ID情報
-
- DOI : 10.1111/j.1442-2042.2006.01557.x
- ISSN : 0919-8172
- CiNii Articles ID : 10018302863
- PubMed ID : 17010007
- Web of Science ID : WOS:000240742500006