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TH‐AB‐209‐11: Breast Microcalcification Classification Using Spectral X‐Ray Coherent Scatter Computed Tomography
Author(s) -
Ghammraoui B,
M Popescu L,
Badano A
Publication year - 2016
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4958102
Subject(s) - microcalcification , imaging phantom , contrast (vision) , materials science , receiver operating characteristic , projection (relational algebra) , optics , physics , nuclear medicine , mammography , mathematics , medicine , algorithm , statistics , breast cancer , cancer
Purpose: To investigate the ability of Coherent Scatter Computed Tomography (CSCT) to distinguish non‐invasively between type I calcifications, consisting of calcium oxalate dihydrate (CO) compounds which are more often associated with benign lesions, and type II calcifications containing hydroxyapatite (HA) which are predominantly associated with malignant tumors. Methods: The coherent scatter cross sections of HA and CO were measured using an energy dispersive x‐ray diffractometer. The measured cross sections were introduced into MC‐GPU Monte Carlo simulation code for studying the applicability of CSCT to discriminate between the two types of microcalcifications within the whole breast. Simulations were performed on a virtual phantom with inserted HA and CO spots of different sizes and placed in regions of interest having different background compositions. We considered a polychromatic x‐ray source and an energy resolving photon counting detector. We applied an algorithm that estimates scatter components in projection space in order to obtain material‐specific images of the breast. As material components adipose, glandular, HA and CO were used. The relative contrast of HA and CO components were used for type I and type II microcalcification discrimination. Results: The reconstructed CSCT images showed material‐specific component‐contrast values, with the highest CO or HA component contrast corresponding generally to the actual CO or HA feature, respectively. The discrimination performance varies with the x‐ray intensity, calcification size, and background composition. The results were summarized using receiver operating characteristic (ROC) analysis with the area under the curve (AUC) taken as an overall indicator of discrimination performance and showing high AUC values up to unity. Conclusion: The simulation results obtained for a uniform breast imaging phantom indicate that CSCT has potential to be used as a non‐invasive method for discrimination between type I and type II microcalcifications.