ArticleFrontiers in physiology2016
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.
Article in Frontiers in physiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 51 citations in OpenAlex.
- Review
- Fractal dimensions for tumour-related cell types of prostate cancer on histopathology images using multiple-threshold box counting algorithm.Biophysics and physicobiology · 2025Article
- Classifying breast cancer and fibroadenoma tissue biopsies from paraffined stain-free slides by fractal biomarkers in Fourier Ptychographic Microscopy.Computational and structural biotechnology journal · 2024Article
- Fractal analysis is a useful tool for evaluating prostate tissue remodeling caused by ethanol consumption and androgen therapy.Animal reproduction · 2023Article
- Application of Lacunarity for Quantification of Single Molecule Localization Microscopy Images.Cells · 2022Article
- The Longitudinal Assessment of Vascular Parameters of the Retina and Their Correlations with Systemic Characteristics in Type 2 Diabetes-A Pilot Study.Vision (Basel, Switzerland) · 2022Article
- The fractal and textural analysis of glomeruli in obese and non-obese patients.Journal of pathology informatics · 2022Review
- Local Fractal Connections to Characterize the Spatial Processes of Deforestation in the Ecuadorian Amazon.Entropy (Basel, Switzerland) · 2021Article
- Prognostic Significance of Lacunarity in Preoperative Biopsy of Colorectal Cancer.Pathology oncology research : POR · 2020Article
- Replicative senescence in MSCWJ-1 human umbilical cord mesenchymal stem cells is marked by characteristic changes in motility, cytoskeletal organization, and RhoA localization.Molecular biology reports · 2020Article
- Monitoring and Determining Mitochondrial Network Parameters in Live Lung Cancer Cells.Journal of clinical medicine · 2019Article
- Benefits of Fractal Approaches in Solid Dosage Form Development.Pharmaceutical research · 2019Review
- Fractal-based radiomic approach to predict complete pathological response after chemo-radiotherapy in rectal cancer.La Radiologia medica · 2018Article
- Automatic prediction of tumour malignancy in breast cancer with fractal dimension.Royal Society open science · 2016Article
- Computer-Aided Image Analysis and Fractal Synthesis in the Quantitative Evaluation of Tumor Aggressiveness in Prostate Carcinomas.Frontiers in oncology · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTumor 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.
methodsThe global fractal capacity D 0, information D 1 and correlation D 2 dimension, the local fractal dimension (LFD) and the local connected fractal dimension (LCFD), Shannon entropy H and lacunarity λ were measured using computer algorithms in digitalized images of both the reference set (n = 60) and the test set (n = 208) of prostate carcinomas.
resultsProstate carcinomas were re-stratified into seven classes of equivalence. The cut-off D 0-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 D 1 failed to define the same classes of equivalence. The pairs (D 0, LFD), (D 0, H), (D 0, λ), (D 1, LFD), (D 1, H), (D 1, λ) 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 D 0 < 1.5820, LFD < 1.3, LCFD > 1.5, H < 0.7, and λ > 0.8, the class C1 or C2 contains low complexity low aggressive carcinomas exclusively. For D 0 > 1.6980, LFD > 1.7644, LCFD > 1.7051, H > 0.9, and λ < 0.7, the class C6 or C7 contains high complexity high aggressive carcinomas.
conclusionsThe cut-off D 0-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 studies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.