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

Background: Tumor grading, PSA concentration, and stage determine a risk of prostate cancer patients with accuracy of about 70%. An approach based on the fractal geometrical model was proposed to eliminate subjectivity from the evaluation of tumor aggressiveness and to improve the prediction. This s...

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Main Author: Przemyslaw eWaliszewski
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-02-01
Series:Frontiers in Physiology
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fphys.2016.00034/full
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spelling doaj-9c5d9234cc24493291d7523eeca4929e2020-11-24T23:05:05ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2016-02-01710.3389/fphys.2016.00034172355The 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 CarcinomasPrzemyslaw eWaliszewski0Przemyslaw eWaliszewski1Alb Fils KlinikenThe Bedlewo Institute for Complexity ResearchBackground: Tumor grading, PSA concentration, and stage determine a risk of prostate cancer patients with accuracy of about 70%. An approach based on the fractal geometrical model was proposed to eliminate subjectivity from the evaluation of tumor aggressiveness and to improve the prediction. This study was undertaken to validate classes of equivalence for the spatial distribution of cancer cell nuclei in a larger, independent set of prostate carcinomas.Methods: The global fractal capacity D0, information D1 and correlation D2 dimension, the local fractal dimension (LFD) and the local connected fractal dimension (LCFD), Shannon entropy H and lacunarity were measured using computer algorithms in digitalized images of both the reference set (n = 60) and the test set (n = 208) of prostate carcinomas.Results: Prostate carcinomas were re-stratified into seven classes of equivalence. The cut-off D0 values 1.5450, 1.5820, 1.6270, 1.6490, 1.6980, 1.7640 defined the classes from C1 to C7, respectively. The other measures but the D1 failed to define the same classes of equivalence. The pairs (D0, LFD), (D0, H), (D0, ), (D1, LFD), (D1, H), (D1, ) characterized the spatial distribution of cancer cell nuclei in each class. The co-application of those measures enabled the subordination of prostate carcinomas to one out of three clusters associated with different tumor aggressiveness. For D0 < 1.5820, LFD < 1.3, LCFD  1.5, H < 0.7 and  > 0.8, the class C1 or C2 contains low complexity low aggressive carcinomas exclusively. For D0 > 1.6980, LFD > 1.7644, LCFD > 1.7051, H > 0.9, and < 0.7, the class C6 or C7 contains high complexity high aggressive carcinomas. Conclusions: The cut-off D0 values defining the classes of equivalence were validated in this study. The cluster analysis suggested that the number of the subjective Gleason grades and the number of the objective classes of equivalence could be decreased from seven to three without a loss of clinically relevant information. Two novel quantitative criteria based on the complexity and the diversity measures enabled the identification of low or high aggressive prostate carcinomas and should be verified in the future multicenter, randomized studyhttp://journal.frontiersin.org/Journal/10.3389/fphys.2016.00034/fullFractalsComplexityimage analysisentropymultifractalslacunarity
collection DOAJ
language English
format Article
sources DOAJ
author Przemyslaw eWaliszewski
Przemyslaw eWaliszewski
spellingShingle Przemyslaw eWaliszewski
Przemyslaw eWaliszewski
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
Frontiers in Physiology
Fractals
Complexity
image analysis
entropy
multifractals
lacunarity
author_facet Przemyslaw eWaliszewski
Przemyslaw eWaliszewski
author_sort Przemyslaw eWaliszewski
title 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
title_short 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_sort 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
publisher Frontiers Media S.A.
series Frontiers in Physiology
issn 1664-042X
publishDate 2016-02-01
description Background: Tumor grading, PSA concentration, and stage determine a risk of prostate cancer patients with accuracy of about 70%. An approach based on the fractal geometrical model was proposed to eliminate subjectivity from the evaluation of tumor aggressiveness and to improve the prediction. This study was undertaken to validate classes of equivalence for the spatial distribution of cancer cell nuclei in a larger, independent set of prostate carcinomas.Methods: The global fractal capacity D0, information D1 and correlation D2 dimension, the local fractal dimension (LFD) and the local connected fractal dimension (LCFD), Shannon entropy H and lacunarity were measured using computer algorithms in digitalized images of both the reference set (n = 60) and the test set (n = 208) of prostate carcinomas.Results: Prostate carcinomas were re-stratified into seven classes of equivalence. The cut-off D0 values 1.5450, 1.5820, 1.6270, 1.6490, 1.6980, 1.7640 defined the classes from C1 to C7, respectively. The other measures but the D1 failed to define the same classes of equivalence. The pairs (D0, LFD), (D0, H), (D0, ), (D1, LFD), (D1, H), (D1, ) characterized the spatial distribution of cancer cell nuclei in each class. The co-application of those measures enabled the subordination of prostate carcinomas to one out of three clusters associated with different tumor aggressiveness. For D0 < 1.5820, LFD < 1.3, LCFD  1.5, H < 0.7 and  > 0.8, the class C1 or C2 contains low complexity low aggressive carcinomas exclusively. For D0 > 1.6980, LFD > 1.7644, LCFD > 1.7051, H > 0.9, and < 0.7, the class C6 or C7 contains high complexity high aggressive carcinomas. Conclusions: The cut-off D0 values defining the classes of equivalence were validated in this study. The cluster analysis suggested that the number of the subjective Gleason grades and the number of the objective classes of equivalence could be decreased from seven to three without a loss of clinically relevant information. Two novel quantitative criteria based on the complexity and the diversity measures enabled the identification of low or high aggressive prostate carcinomas and should be verified in the future multicenter, randomized study
topic Fractals
Complexity
image analysis
entropy
multifractals
lacunarity
url http://journal.frontiersin.org/Journal/10.3389/fphys.2016.00034/full
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