Investigating the feasibility of classifying breast microcalcifications using photon-counting spectral mammography: A simulation study

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A dual-energy material decomposition method using photon-counting spectral mammography was investigated as a non-invasive diagnostic approach to differentiate between Type I calcifications, consisting of calcium oxalate dihydrate or weddellite compounds that are more often associated with benign lesions, and Type II calcifications containing hydroxyapatite that are predominantly associated with malignant tumors.


The study was carried out by numerical simulation to assess the feasibility of the proposed approach. A pencil-beam geometry was modeled, and the total number of x-rays transported through a breast embedded with microcalcifications of different types and sizes were simulated by a one-pixel detector. Material decomposition using two energy bins was then applied to characterize the simulated calcifications into hydroxyapatite and weddellite using maximum-likelihood estimation, taking into account the polychromatic source, and the energy dependent attenuation. Simulation tests were carried out for different dose levels, energy windows and calcification sizes for multiple noise realizations.


The results were analyzed using receiver operating characteristic (ROC) analysis. Classification between Type I and Type II calcifications achieved by analyzing a single microcalcification showed moderate accuracy. However, simultaneously analyzing several calcifications within the cluster provided area under the ROC curve of greater than 99% for radiation dose greater than 4.8 mGy mean glandular dose.


Simulation results indicated that photon-counting spectral mammography with dual energy material decomposition has the potential to be used as a non-invasive method for discrimination between Type I and Type II microcalcifications that can potentially improve early breast cancer diagnosis and reduce the number of negative breast biopsies. Additional studies using breast specimens and clinical data should be performed to further explore the feasibility of this approach.

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