Description of magnetic resonance imaging-derived enhancement variables in pathologically confirmed prostate cancer and normal peripheral zone regions-Reference-Cited by-同舟云学术

Description of magnetic resonance imaging-derived enhancement variables in pathologically confirmed prostate cancer and normal peripheral zone regions

Published:2009-09 Issue:5 Volume:104 Page:621-627
ISSN:1464-4096
Container-title:BJU International
language:en
Short-container-title:

Author:

Zelhof Bashar,Lowry Martin,Rodrigues Greta,Kraus Sigurd,Turnbull Lindsay

Publisher

Wiley

Subject

Urology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/j.1464-410X.2009.08457.x/fullpdf

Reference26 articles.

1. Advances in angiogenesis research: relevance to urological oncology;Campbell;J Urol,1997

2. Quantitative microvessel density. A staging and prognostic marker for human prostatic carcinoma;Brawer;Cancer,1996

3. Tumor angiogenesis correlates with metastasis in invasive prostate carcinoma;Weidner;Am J Pathol,1993

4. Ki-67 expression is a prognostic marker of prostate cancer recurrence after radical prostatectomy;Bettencourt;J Urol,1996

5. Dynamic contrast enhanced MRI in prostate cancer;Alonzi;Eur J Radiol,2007

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