Literature DB >> 28332199

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

Bahaa Ghammraoui1, Stephen J Glick1.   

Abstract

PURPOSE: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Entities:  

Keywords:  breast microcalcifications; material decomposition; photon-counting detector; spectral mammography

Mesh:

Year:  2017        PMID: 28332199     DOI: 10.1002/mp.12230

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  5 in total

1.  Photon counting performance of amorphous selenium and its dependence on detector structure.

Authors:  Jann Stavro; Amir H Goldan; Wei Zhao
Journal:  J Med Imaging (Bellingham)       Date:  2018-10-30

2.  Classification of breast microcalcifications using dual-energy mammography.

Authors:  Bahaa Ghammraoui; Andrey Makeev; Ahmed Zidan; Alaadin Alayoubi; Stephen J Glick
Journal:  J Med Imaging (Bellingham)       Date:  2019-03-12

3.  Exploring CNN potential in discriminating benign and malignant calcifications in conventional and dual-energy FFDM: simulations and experimental observations.

Authors:  Andrey Makeev; Gabriela Rodal; Bahaa Ghammraoui; Andreu Badal; Stephen J Glick
Journal:  J Med Imaging (Bellingham)       Date:  2021-05-13

4.  Characterization of a GaAs photon-counting detector for mammography.

Authors:  Bahaa Ghammraoui; Spyridon Gkoumas; Stephen J Glick
Journal:  J Med Imaging (Bellingham)       Date:  2021-06-22

5.  Deep learning can be used to train naïve, nonprofessional observers to detect diagnostic visual patterns of certain cancers in mammograms: a proof-of-principle study.

Authors:  Jay Hegdé
Journal:  J Med Imaging (Bellingham)       Date:  2020-02-04
  5 in total

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