September 2024
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6 Reads
Chaos Solitons & Fractals
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September 2024
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6 Reads
Chaos Solitons & Fractals
March 2023
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21 Reads
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6 Citations
Journal of Theoretical Biology
Cell-based models provide a helpful approach for simulating complex systems that exhibit adaptive, resilient qualities, such as cancer. Their focus on individual cell interactions makes them a particularly appropriate strategy to study cancer therapies' effects, which are often designed to disrupt single-cell dynamics. In this work, we propose them as viable methods for studying the time evolution of cancer imaging biomarkers (IBM). We propose a cellular automata model for tumor growth and three different therapies: chemotherapy, radiotherapy, and immunotherapy, following well-established modeling procedures documented in the literature. The model generates a sequence of tumor images, from which a time series of two biomarkers: entropy and fractal dimension, is obtained. Our model shows that the fractal dimension increased faster at the onset of cancer cell dissemination. At the same time, entropy was more responsive to changes induced in the tumor by the different therapy modalities. These observations suggest that the prognostic value of the proposed biomarkers could vary considerably with time. Thus, it is essential to assess their use at different stages of cancer and for different imaging modalities. Another observation derived from the results was that both biomarkers varied slowly when the applied therapy attacked cancer cells scattered along the automatons' area, leaving multiple independent clusters of cells at the end of the treatment. Thus, patterns of change of simulated biomarkers time series could reflect on essential qualities of the spatial action of a given cancer intervention.
January 2023
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7 Reads
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1 Citation
November 2022
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106 Reads
Cell-based models provide a helpful approach for simulating complex systems that exhibit adaptive, resilient qualities, such as cancer. Their focus on individual cell interactions makes them a particularly appropriate strategy to study the effects of cancer therapies, which often are designed to disrupt single-cell dynamics. In this work, we also propose them as viable methods for studying the time evolution of cancer imaging biomarkers (IBM). We propose a cellular automata model for tumor growth and three different therapies: chemotherapy, radiotherapy, and immunotherapy, following well-established modeling procedures documented in the literature. The model generates a sequence of tumor images, from which time series of two biomarkers: entropy and fractal dimension, is obtained. Our model shows that the fractal dimension increased faster at the onset of cancer cell dissemination, while entropy was more responsive to changes induced in the tumor by the different therapy modalities. These observations suggest that the predictive value of the proposed biomarkers could vary considerably with time. Thus, it is important to assess their use at different stages of cancer and for different imaging modalities. Another observation derived from the results was that both biomarkers varied slowly when the applied therapy attacked cancer cells in a scattered fashion along the automatons' area, leaving multiple independent clusters of cells at the end of the treatment. Thus, patterns of change of simulated biomarkers time series could reflect on essential qualities of the spatial action of a given cancer intervention.
January 2022
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3 Reads
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1 Citation
SSRN Electronic Journal
... Clearly, by looking at figure 2, we can see that the scaling factor decreases with a very heavy tailed trend by the increase of N, whereas, in figure 3, the portrayed data shows that both ε ( the scaling factor) and FD(fractal dimension) are decreasing at the same time. The following section presents some influential open problems in fractal oncology [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28]. Exploring these open problems could lead to significant advancements in our understanding of cancer biology and therapy, potentially impacting diagnosis, treatment, and patient outcomes. ...
March 2023
Journal of Theoretical Biology
... In the last decade, the number of studies dedicated to the development of mathematical models of behavior in living multicellular tissues has increased [1][2][3][4][5][6]. This interest among scientists is associated with the rapid advancement of computer technologies, which enable in silico investigations without harm to real living organisms. ...
January 2022
SSRN Electronic Journal