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MO‐FG‐CAMPUS‐IeP1‐02: Dose Reduction in Contrast‐Enhanced Digital Mammography Using a Photon‐Counting Detector
Author(s) -
Lee S,
Kang S,
Eom J
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 - 10.1118/1.4957334
Subject(s) - imaging phantom , cadmium zinc telluride , monte carlo method , mammography , detector , digital mammography , medical imaging , photon counting , contrast to noise ratio , photon energy , materials science , photon , optics , nuclear medicine , image quality , physics , mathematics , medicine , computer science , radiology , statistics , artificial intelligence , breast cancer , cancer , image (mathematics)
Purpose: Photon‐counting detectors (PCDs) allow multi‐energy X‐ray imaging without additional exposures and spectral overlap. This capability results in the improvement of accuracy of material decomposition for dual‐energy X‐ray imaging and the reduction of radiation dose. In this study, the PCD‐based contrast‐enhanced dual‐energy mammography (CEDM) was compared with the conventional CDEM in terms of radiation dose, image quality and accuracy of material decomposition. Methods: A dual‐energy model was designed by using Beer‐Lambert's law and rational inverse fitting function for decomposing materials from a polychromatic X‐ray source. A cadmium zinc telluride (CZT)‐based PCD, which has five energy thresholds, and iodine solutions included in a 3D half‐cylindrical phantom, which composed of 50% glandular and 50% adipose tissues, were simulated by using a Monte Carlo simulation tool. The low‐ and high‐energy images were obtained in accordance with the clinical exposure conditions for the conventional CDEM. Energy bins of 20–33 and 34–50 keV were defined from X‐ray energy spectra simulated at 50 kVp with different dose levels for implementing the PCD‐based CDEM. The dual‐energy mammographic techniques were compared by means of absorbed dose, noise property and normalized root‐mean‐square error (NRMSE). Results: Comparing to the conventional CEDM, the iodine solutions were clearly decomposed for the PCD‐based CEDM. Although the radiation dose for the PCD‐based CDEM was lower than that for the conventional CEDM, the PCD‐based CDEM improved the noise property and accuracy of decomposition images. Conclusion: This study demonstrates that the PCD‐based CDEM allows the quantitative material decomposition, and reduces radiation dose in comparison with the conventional CDEM. Therefore, the PCD‐based CDEM is able to provide useful information for detecting breast tumor and enhancing diagnostic accuracy in mammography.