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Breast cancer: A fractal approach, scaling analysis and quantum cluster algorithm
Kevin de la Ossa-Doria1, Francisco Torres-Hoyos2, Rubén Baena-Navarro3
1Department of Physics, Faculty of Basic Sciences, Universidad de Córdoba, Montería, Colombia.
Summary
Understanding breast tumor growth is key for diagnosis and treatment. Invasive tumors follow specific scaling laws, unlike benign tumors, offering new insights into their complex morphology.
Area of Science:
- Biophysics
- Oncology
- Medical Imaging
Background:
- Breast tumor morphology is complex and crucial for diagnosis and treatment.
- Quantitative descriptors are needed to characterize tumor growth patterns.
- Scaling analysis offers a method to extract parameters like fractal dimension.
Purpose of the Study:
- To apply scaling analysis to characterize breast tumor growth.
- To differentiate between invasive and benign breast tumor behaviors using morphological parameters.
Main Methods:
- Utilized scaling analysis to extract local roughness exponents and fractal dimensions.
- Evaluated the morphological characteristics of invasive lobular carcinoma, ductal carcinoma in situ, and benign breast tumors.
Main Results:
- Invasive lobular and ductal carcinoma in situ tumors exhibited growth patterns consistent with the Family-Vicsek model.
- Benign breast tumors demonstrated distinct growth behaviors that deviated from the Family-Vicsek model.
Conclusions:
- The Family-Vicsek model effectively describes the growth dynamics of certain invasive breast cancers.
- Distinct scaling properties differentiate invasive from benign breast tumors, aiding in morphological characterization.
