title: Computational growth model of breast microcalcification clusters in simulated mammographic environments.
abstract: When screening for breast cancer, the radiological interpretation of mammograms is a difficult task, particularly when classifying precancerous growth such as microcalcifications (MCs). Biophysical modeling of benign vs. malignant growth of MCs in simulated mammographic backgrounds may improve characterization of these structures
  
  
  
  A mathematical model based on crystal growth rules for calcium oxide (benign) and hydroxyapatite (malignant) was used in conjunction with simulated mammographic backgrounds, which were generated by fractional Brownian motion of varying roughness and quantified by the Hurst exponent to mimic tissue of varying density. Simulated MC clusters were compared by fractal dimension, average circularity of individual MCs, average number of MCs per cluster, and average cluster area.
  
  
  
  Benign and malignant clusters were distinguishable by average circularity, average number of MCs per cluster, and average cluster area with p<0.01 across all Hurst exponent values considered. Clusters were distinguishable by fractal dimension with p<0.05 in low Hurst exponent environments. As the Hurst exponent increased (tissue density increased) benign and malignant MCs became indistinguishable by fractal dimension.
  
  
  
  The fractal dimension of MCs changes with breast tissue density, which suggests tissue environment plays a role in regulating MC growth. Benign and malignant MCs are distinguishable in all types of tissue by shape, size, and area, which is consistent with findings in the literature. These results may help to better understand the effects of the tissue environment on tumor progression, and improve classification of MCs in mammograms via computer-aided diagnosis.
authors.affiliation: CompuMAINE Laboratory, Department of Mathematics and Statistics, University of Maine, Orono, ME 04469, USA.
authors.forename: Shayne M
authors.initials: SM
authors.lastname: Plourde
authors.affiliation: CompuMAINE Laboratory, Department of Mathematics and Statistics, University of Maine, Orono, ME 04469, USA.
authors.forename: Zach
authors.initials: Z
authors.lastname: Marin
authors.affiliation: CompuMAINE Laboratory, Department of Mathematics and Statistics, University of Maine, Orono, ME 04469, USA; Department of Physics and Astronomy, University of Maine, Orono, ME 04469, USA.
authors.forename: Zachary R
authors.initials: ZR
authors.lastname: Smith
authors.affiliation: CompuMAINE Laboratory, Department of Mathematics and Statistics, University of Maine, Orono, ME 04469, USA.
authors.forename: Brian C
authors.initials: BC
authors.lastname: Toner
authors.affiliation: CompuMAINE Laboratory, Department of Mathematics and Statistics, University of Maine, Orono, ME 04469, USA.
authors.forename: Kendra A
authors.initials: KA
authors.lastname: Batchelder
authors.affiliation: CompuMAINE Laboratory, Department of Mathematics and Statistics, University of Maine, Orono, ME 04469, USA. Electronic address: andre.khalil@maine.edu.
authors.forename: Andre
authors.initials: A
authors.lastname: Khalil
mesh_terms: D001941:Breast Diseases / Q000000981:diagnostic imaging*; D002114:Calcinosis / Q000000981:diagnostic imaging*; D017610:Calcium Compounds / Q000737:chemistry; D017886:Durapatite / Q000737:chemistry; D005260:Female; D017709:Fractals; D006801:Humans; D008327:Mammography / Q000379:methods*; D008954:Models, Biological; D010087:Oxides / Q000737:chemistry
chemical_list: D017610:Calcium Compounds; D010087:Oxides; D017886:Durapatite; C016538:lime
keywords: Breast cancer; Breast tissue; Fractal; Microcalcification; Model; Simulation