Literature DB >> 17175129

Implementation of a map in radical prostatectomy specimen allows visual estimation of tumor volume.

O Bettendorf1, F Oberpenning, T Köpke, A Heinecke, L Hertle, W Boecker, A Semjonow.   

Abstract

INTRODUCTION: Tumor volume is one of the best documented prognostic factors for prostate cancer. There are several methods to gain this important parameter but unfortunately most of the clinicians in the world do not get this information in their routine practice from the pathologist. We developed a standardized method to handle radical prostatectomy specimens including a special form of mapping in order to document relevant morphological data. The aim of this study was to investigate if our model of mapping prostate cancer, which we use in routine practice, may serve for visual estimation of tumor volume.
METHODS: We estimated the tumor volume of prostate cancer by visual estimation of 350 maps of radical prostatectomy specimens and correlated these data with established prognostic parameters and clinical outcome.
RESULTS: Significant correlations between tumor volumes, as obtained from our mapping, and known prognostic parameters such as preoperative serum levels of prostatic specific antigen, loss of differentiation, histological grade, lymph node metastasis, and margins were found. In a multivariate analysis, only Gleason score and tumor stage were shown to be independent prognostic parameters. DISCUSSION: We demonstrate that mapping of prostate cancer is more than a simple method of documentation but may serve as a method for visual estimation of tumor volume of prostate cancer after radical prostatectomy. This method can further be used for a visual documentation of the tumor stage independent of changes in the TNM classification. The method is inexpensive and practicable and can therefore be applied in routine surgical pathology.

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Year:  2006        PMID: 17175129     DOI: 10.1016/j.ejso.2006.11.004

Source DB:  PubMed          Journal:  Eur J Surg Oncol        ISSN: 0748-7983            Impact factor:   4.424


  5 in total

1.  Specific spatial distribution patterns of tumor foci are associated with a low risk of biochemical recurrence in pT2pN0R0 prostate cancer.

Authors:  Okyaz Eminaga; Mahmoud Abbas; Olaf Bettendorf; Axel Semjonow
Journal:  World J Urol       Date:  2020-06-26       Impact factor: 4.226

2.  Automatic cancer detection on digital histopathology images of mid-gland radical prostatectomy specimens.

Authors:  Wenchao Han; Carol Johnson; Andrew Warner; Mena Gaed; Jose A Gomez; Madeleine Moussa; Joseph Chin; Stephen Pautler; Glenn Bauman; Aaron D Ward
Journal:  J Med Imaging (Bellingham)       Date:  2020-07-16

3.  Prostate cancer detection with real-time elastography using a bi-plane transducer: comparison with step section radical prostatectomy pathology.

Authors:  Yunkai Zhu; Yaqing Chen; Tingyue Qi; Jun Jiang; Jun Qi; Yongjiang Yu; Xiaohong Yao; Wenbin Guan
Journal:  World J Urol       Date:  2012-08-12       Impact factor: 4.226

4.  Clinical map document based on XML (cMDX): document architecture with mapping feature for reporting and analysing prostate cancer in radical prostatectomy specimens.

Authors:  Okyaz Eminaga; Reemt Hinkelammert; Axel Semjonow; Joerg Neumann; Mahmoud Abbas; Thomas Koepke; Olaf Bettendorf; Elke Eltze; Martin Dugas
Journal:  BMC Med Inform Decis Mak       Date:  2010-11-15       Impact factor: 2.796

5.  CMDX©-based single source information system for simplified quality management and clinical research in prostate cancer.

Authors:  Okyaz Eminaga; Mahmoud Abbas; Reemt Hinkelammert; Ulf Titze; Olaf Bettendorf; Elke Eltze; Enver Ozgür; Axel Semjonow
Journal:  BMC Med Inform Decis Mak       Date:  2012-12-03       Impact factor: 2.796

  5 in total

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