Characterization of a GaAs photon-counting detector for mammography

Abstract. Purpose: The purpose of this study was to evaluate the potential of a prototype gallium arsenide (GaAs) photon-counting detector (PCD) for imaging of the breast. Approach: First, the contrast-to-noise ratio (CNR) using different aluminum/poly(methyl methacrylate) (PMMA) phantoms of different thicknesses were measured. Second, microcalcification detection accuracy using a receiver operating characteristic study with three observers reading an ensemble of images was measured. Finally, the feasibility of using a GaAs system with two energy bins for contrast-enhanced mammography was investigated. Results: For the first two studies, the GaAs detector was compared with a commercial mammography system. The CNR was estimated by imaging 18-, 36-, and 110-μm-thick aluminum targets placed on top of 6 cm of PMMA plates and was found to be similar or better over a range of exposures. We observed a similar performance of detecting microcalcifications with the GaAs detector over a range of clinically applicable dose levels with a small increase at lower dose levels. The results also showed that contrast-enhanced spectral mammography using a GaAs PCD is feasible and beneficial. Conclusions: Results from this study suggest that performance with this new detector seems either slightly improved or equivalent to a commercial mammography system that used an energy-integrated detector. No attempt at optimizing exposure techniques for the GaAs detector was performed. Further research is needed to determine optimal acquisition parameters for the GaAs detector and to develop more sophisticated material decomposition algorithms that promise to provide improved quantitative estimates of iodine uptake.

[1]  Matti Kauppinen,et al.  Framework for Photon Counting Quantitative Material Decomposition , 2020, IEEE Transactions on Medical Imaging.

[2]  Andreu Badal,et al.  A novel physical anthropomorphic breast phantom for 2D and 3D x‐ray imaging , 2017, Medical physics.

[3]  Wei Zhao,et al.  Experimental quantification of lesion detectability in contrast enhanced dual energy digital breast tomosynthesis , 2012, Medical Imaging.

[4]  Stephen J Glick,et al.  Investigation of energy weighting using an energy discriminating photon counting detector for breast CT. , 2013, Medical physics.

[5]  Alfonso G. Taboada,et al.  Dose-independent near-ideal DQE of a 75 μm pixel GaAs photon-counting spectral detector for breast imaging , 2019, Medical Imaging.

[6]  Nataly Wieberneit,et al.  Characterization of Cystic Lesions by Spectral Mammography: Results of a Clinical Pilot Study , 2016, Investigative radiology.

[7]  Andrey Makeev,et al.  Objective assessment of task performance: a comparison of two FFDM detectors using an anthropomorphic breast phantom , 2019, Journal of medical imaging.

[8]  Brandon D Gallas,et al.  One-shot estimate of MRMC variance: AUC. , 2006, Academic radiology.

[9]  Bahaa Ghammraoui,et al.  Investigating the feasibility of classifying breast microcalcifications using photon‐counting spectral mammography: A simulation study , 2017, Medical physics.

[10]  H. Ding,et al.  Quantitative contrast‐enhanced spectral mammography based on photon‐counting detectors: A feasibility study , 2017, Medical physics.

[11]  Hilde Bosmans,et al.  Experimental investigation on the choice of the tungsten/rhodium anode/filter combination for an amorphous selenium-based digital mammography system , 2006, European Radiology.

[12]  S. Glick,et al.  Feasibility of estimating volumetric breast density from mammographic x‐ray spectra using a cadmium telluride photon‐counting detector , 2018, Medical physics.

[13]  R. Klausz,et al.  Introduction of a comprehensive phantom for the quality control of contrast enhanced spectral mammography , 2018 .

[14]  J. Boone.  Normalized glandular dose (DgN) coefficients for arbitrary X-ray spectra in mammography: computer-fit values of Monte Carlo derived data. , 2002, Medical physics.

[15]  Mats Lundqvist,et al.  Comparison of radiologist performance with photon-counting full-field digital mammography to conventional full-field digital mammography. , 2012, Academic radiology.

[16]  B. Zheng,et al.  Tutorial on X-ray photon counting detector characterization. , 2017, Journal of X-ray science and technology.

[17]  M Danielsson,et al.  Detective quantum efficiency dependence on x-ray energy weighting in mammography. , 1999, Medical physics.

[18]  Taly Gilat Schmidt,et al.  Optimal "image-based" weighting for energy-resolved CT. , 2009, Medical physics.

[19]  Christian G. Graff,et al.  A new, open-source, multi-modality digital breast phantom , 2016, SPIE Medical Imaging.

[20]  Michael Scheel,et al.  Paper-based 3D printing of anthropomorphic CT phantoms: Feasibility of two construction techniques , 2018, European Radiology.

[21]  Hilde Bosmans,et al.  Effective detective quantum efficiency for two mammography systems: measurement and comparison against established metrics. , 2013, Medical physics.