Evidence map›Paper›PMID 25015793›Full record

ArticleDer Urologe. Ausg. A2014

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

P Waliszewski, F Wagenlehner, S Kribus, W Schafhauser, W Weidner, S Gattenlöhner

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Article in Der Urologe. Ausg. A, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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What it found

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3 · Its place in the literature

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2 citing papers in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

P WaliszewskiKlinik für Urologie, Andrologie und Kinderurologie, Justus-Liebig-Universität, Rudolf-Buchheim-Straße 7, 35392, Gießen, Deutschland, complexityresearch@yahoo.com.
F Wagenlehner
S Kribus
W Schafhauser
W Weidner
S Gattenlöhner

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSignificant 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

methodsThe 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).

resultsThe 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%.

conclusionThe method of fractal geometry enables both an objective and quantitative grading of prostate cancer.

Indexed as

AlgorithmsFractalsSignal Processing, Computer-AssistedCell NucleusHumansImage Interpretation, Computer-AssistedMaleNeoplasm GradingObserver VariationPattern Recognition, AutomatedPilot ProjectsProstatic NeoplasmsReproducibility of ResultsSensitivity and Specificity

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