Literature DB >> 25015793

[Objective grading of prostate carcinoma based on fractal dimensions: Gleason 3 + 4= 7a ≠ Gleason 4 + 3 =7b].

P Waliszewski1, F Wagenlehner, S Kribus, W Schafhauser, W Weidner, S Gattenlöhner.   

Abstract

BACKGROUND: Significant intra- and interobserver variability ranging between 40 and 80% is observed in tumor grading of prostate carcinoma. By combining geometric and statistical methods, an objective system of grading can be designed.
MATERIAL AND METHODS: The distributions of cell nuclei in two-dimensional patterns of prostate cancer classified subjectively as Gleason score 3+3, 3+4, 4+3, 4+4, 4+5, 5+4, and 5+5 were analyzed with algorithms measuring the global fractal dimensions of the Rényi family and with the algorithm for the local connected fractal dimension (LCFD).
RESULTS: The dimensions for global fractal capacity, information, and correlation (standard deviation) were 1.470 (045), 1.528 (046), and 1.582 (099) for homogenous Gleason grade 3 (n = 16), 1.642 (034), 1.678 (041), and 1.673 (084) for homogenous Gleason grade 4 (n=18), and 1.797 (042), 1.791 (026), and 1.854 (031) for homogenous Gleason grade 5 (n=12), respectively. The LCFD algorithm can be used to distinguish both qualitatively and quantitatively between mixed and heterogeneous patterns, such as Gleason score 3+4=7a (intermediate risk cancer) and Gleason score 4+3=7b (high-risk cancer). Sensitivity of the method is 89.3%, and specificity 84.3%.
CONCLUSION: The method of fractal geometry enables both an objective and quantitative grading of prostate cancer.

Entities:  

Mesh:

Year:  2014        PMID: 25015793     DOI: 10.1007/s00120-014-3470-z

Source DB:  PubMed          Journal:  Urologe A        ISSN: 0340-2592            Impact factor:   0.639


  19 in total

1.  Distribution of gland-like structures in human gallbladder adenocarcinomas possesses fractal dimension.

Authors:  P Waliszewski
Journal:  J Surg Oncol       Date:  1999-07       Impact factor: 3.454

2.  Determination of optical coefficients and fractal dimensional parameters of cancerous and normal prostate tissues.

Authors:  Yang Pu; Wubao Wang; Mohammad Al-Rubaiee; Swapan Kumar Gayen; Min Xu
Journal:  Appl Spectrosc       Date:  2012-06-15       Impact factor: 2.388

Review 3.  The 2005 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma.

Authors:  Jonathan I Epstein; William C Allsbrook; Mahul B Amin; Lars L Egevad
Journal:  Am J Surg Pathol       Date:  2005-09       Impact factor: 6.394

4.  The reasons behind variation in Gleason grading of prostatic biopsies: areas of agreement and misconception among 266 European pathologists.

Authors:  Daniel M Berney; Ferran Algaba; Philippe Camparo; Eva Compérat; David Griffiths; Glen Kristiansen; Antonio Lopez-Beltran; Rodolfo Montironi; Murali Varma; Lars Egevad
Journal:  Histopathology       Date:  2013-11-06       Impact factor: 5.087

5.  Color graphs for automated cancer diagnosis and grading.

Authors:  Dogan Altunbay; Celal Cigir; Cenk Sokmensuer; Cigdem Gunduz-Demir
Journal:  IEEE Trans Biomed Eng       Date:  2009-10-20       Impact factor: 4.538

6.  [PREFERE - the German prostatic cancer study: questions and claims surrounding study initiation in January 2013].

Authors:  T Wiegel; P Albers; R Bussar-Maatz; A Gottberg; M Härter; M Kieser; G Kristiansen; G Nettekoven; P Martus; H Schmidberger; S Wellek; M Stöckle
Journal:  Urologe A       Date:  2013-04       Impact factor: 0.639

Review 7.  Histologic grading of prostate cancer: a perspective.

Authors:  D F Gleason
Journal:  Hum Pathol       Date:  1992-03       Impact factor: 3.466

8.  The impact of pathology review on treatment recommendations for patients with adenocarcinoma of the prostate.

Authors:  Paul L Nguyen; Delray Schultz; Andrew A Renshaw; Robin T Vollmer; William R Welch; Kerri Cote; Anthony V D'Amico
Journal:  Urol Oncol       Date:  2004 Jul-Aug       Impact factor: 3.498

9.  Multifeature prostate cancer diagnosis and Gleason grading of histological images.

Authors:  Ali Tabesh; Mikhail Teverovskiy; Ho-Yuen Pang; Vinay P Kumar; David Verbel; Angeliki Kotsianti; Olivier Saidi
Journal:  IEEE Trans Med Imaging       Date:  2007-10       Impact factor: 10.048

10.  Classifying prostate cancer malignancy by quantitative histomorphometry.

Authors:  Markus Loeffler; Lars Greulich; Patrick Scheibe; Philip Kahl; David Adler; Ulf-Dietrich Braumann; Jens-Peer Kuska; Nicolas Wernert
Journal:  J Urol       Date:  2012-03-16       Impact factor: 7.450

View more
  2 in total

1.  The Quantitative Criteria Based on the Fractal Dimensions, Entropy, and Lacunarity for the Spatial Distribution of Cancer Cell Nuclei Enable Identification of Low or High Aggressive Prostate Carcinomas.

Authors:  Przemyslaw Waliszewski
Journal:  Front Physiol       Date:  2016-02-11       Impact factor: 4.566

2.  Fractal analysis and the diagnostic usefulness of silver staining nucleolar organizer regions in prostate adenocarcinoma.

Authors:  Alex Stepan; Cristiana Simionescu; Daniel Pirici; Raluca Ciurea; Claudiu Margaritescu
Journal:  Anal Cell Pathol (Amst)       Date:  2015-08-20       Impact factor: 2.916

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.