Optimization of contrast‐enhanced breast imaging: Analysis using a cascaded linear system model

Purpose: Contrast‐enhanced (CE) breast imaging involves the injection contrast agents (i.e., iodine) to increase conspicuity of malignant lesions. CE imaging may be used in conjunction with digital mammography (DM) or digital breast tomosynthesis (DBT) and has shown promise in improving diagnostic specificity. Both CE‐DM and CE‐DBT techniques require optimization as clinical diagnostic tools. Physical factors including x‐ray spectra, subtraction technique, and the signal from iodine contrast, must be considered to provide the greatest object detectability and image quality. We developed a cascaded linear system model (CLSM) for the optimization of CE‐DM and CE‐DBT employing dual energy (DE) subtraction or temporal (TE) subtraction. Methods: We have previously developed a CLSM for DBT implemented with an a‐Se flat panel imager (FPI) and filtered backprojection (FBP) reconstruction algorithm. The model is used to track image quality metrics — modulation transfer function (MTF) and noise power spectrum (NPS) — at each stage of the imaging chain. In this study, the CLSM is extended for CE breast imaging. The effect of x‐ray spectrum (varied by changing tube potential and the filter) and DE and TE subtraction techniques on breast structural noise was measured was studied and included as a deterministic source of noise in the CLSM. From the two‐dimensional (2D) and three‐dimensional (3D) MTF and NPS, the ideal observer signal‐to‐noise ratio (SNR), also known as the detectability index (d′), may be calculated. Using d′ as a FOM, we discuss the optimization of CE imaging for the task of iodinated contrast object detection within structured backgrounds. Results: Increasing x‐ray energy was determined to decrease the magnitude of structural noise and not its correlation. By performing DE subtraction, the magnitude of the structural noise was further reduced at the expense of increased stochastic (quantum and electronic) noise. TE subtraction exhibited essentially no residual structural noise at the expense of increased quantum noise, even over that of the DE case. For DE subtraction, optimization of dose weighting to the HE view (fh) results in the minimization of quantum noise. Both subtraction weighting factor (wSub) and the iodine contrast signal were dependent on the LE and HE x‐ray spectra. To best detect a 5 mm Gaussian lesion with 5 mg/ml of iodine within a 4 cm thick breast, it was found that the high energy (HE) view should be acquired with a tube potential of 47 kVp (W/Ti spectrum) and the low energy (LE) view with a potential of 23 kVp (W/Rh spectrum). Due to the complete removal of structural noise, TE subtraction produced much higher d′ than DE subtraction both as a function of mean glandular dose and iodine concentration. Conclusions: We have shown the effect of increasing x‐ray energy as well as projection domain subtraction on breast structural noise. Further, we have exhibited the utility of the CLSM for DE and TE subtraction CE imaging in the optimization of imaging parameters such as x‐ray energy, fh, and wSub as well as guiding the understanding of their effects on image contrast and noise.

[1]  Arthur E Burgess,et al.  Signal detection in power-law noise: effect of spectrum exponents. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.

[2]  David A. Scaduto,et al.  Optimization of clinical protocols for contrast enhanced breast imaging , 2013, Medical Imaging.

[3]  Shiva Abbaszadeh,et al.  Evaluating noise reduction techniques while considering anatomical noise in dual-energy contrast-enhanced mammography. , 2013, Medical physics.

[4]  Felix Diekmann,et al.  Dual-energy contrast-enhanced digital mammography: initial clinical results of a multireader, multicase study , 2012, Breast Cancer Research.

[5]  John M Boone,et al.  Characterizing anatomical variability in breast CT images. , 2008, Medical physics.

[6]  Nooshin Kiarashi,et al.  Task-based strategy for optimized contrast enhanced breast imaging: analysis of six imaging techniques for mammography and tomosynthesis , 2012, Medical Imaging.

[7]  R P Velthuizen,et al.  On the statistical nature of mammograms. , 1999, Medical physics.

[8]  Bo Zhao,et al.  Imaging performance of an amorphous selenium digital mammography detector in a breast tomosynthesis system. , 2008, Medical physics.

[9]  Corinne Balleyguier,et al.  Contrast-enhanced digital mammography. , 2009, European journal of radiology.

[10]  Bo Zhao,et al.  Image artifacts in digital breast tomosynthesis: investigation of the effects of system geometry and reconstruction parameters using a linear system approach. , 2008, Medical physics.

[11]  John M Lewin,et al.  Dual-energy contrast-enhanced digital subtraction mammography: feasibility. , 2003, Radiology.

[12]  A. Burgess,et al.  Human observer detection experiments with mammograms and power-law noise. , 2001, Medical physics.

[13]  Ann-Katherine Carton,et al.  Dual-energy subtraction for contrast-enhanced digital breast tomosynthesis , 2007, SPIE Medical Imaging.

[14]  N Allec,et al.  Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography. , 2012, Physics in medicine and biology.

[15]  Gene Gindi,et al.  Impact of subtraction and reconstruction strategies on dual-energy contrast enhanced breast tomosynthesis with interleaved acquisition , 2013, Medical Imaging.

[16]  Wei Zhao,et al.  A 3D linear system model for the optimization of dual-energy contrast-enhanced digital breast tomosynthesis , 2011, Medical Imaging.

[17]  J A Rowlands,et al.  Digital radiology using active matrix readout of amorphous selenium: theoretical analysis of detective quantum efficiency. , 1997, Medical physics.

[18]  J. S. Laughlin,et al.  Absorbed radiation dose in mammography. , 1979, Radiology.

[19]  Ann-Katherine Carton,et al.  Anatomical noise in contrast-enhanced digital mammography. Part II. Dual-energy imaging. , 2013, Medical physics.

[20]  John A. Rowlands,et al.  Investigation of lag and ghosting in amorphous selenium flat-panel x-ray detectors , 2002, SPIE Medical Imaging.

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

[22]  Ann-Katherine Carton,et al.  Optimization of a Dual-Energy Contrast-Enhanced Technique for a Photon Counting Digital Breast Tomosynthesis System , 2008, Digital Mammography / IWDM.

[23]  Ann-Katherine Carton,et al.  Quantification for contrast-enhanced digital breast tomosynthesis , 2006, SPIE Medical Imaging.

[24]  John A. Rowlands,et al.  Investigation of imaging performance of amorphous selenium flat-panel detectors for digital mammography , 2001, SPIE Medical Imaging.

[25]  Arthur E. Burgess,et al.  Mammographic structure: data preparation and spatial statistics analysis , 1999, Medical Imaging.

[26]  Bo Zhao,et al.  Characterization of a direct full-field flat-panel digital mammography detector , 2003, SPIE Medical Imaging.

[27]  John J Heine,et al.  Spectral analysis of full field digital mammography data. , 2002, Medical physics.

[28]  Wei Zhao,et al.  Imaging performance of amorphous selenium based flat-panel detectors for digital mammography: characterization of a small area prototype detector. , 2003, Medical physics.

[29]  J. Boone,et al.  An accurate method for computer-generating tungsten anode x-ray spectra from 30 to 140 kV. , 1997, Medical physics.

[30]  J H Siewerdsen,et al.  Generalized DQE analysis of radiographic and dual-energy imaging using flat-panel detectors. , 2005, Medical physics.

[31]  Wojciech Zbijewski,et al.  Cascaded systems analysis of noise and detectability in dual-energy cone-beam CT. , 2012, Medical physics.

[32]  Grace J Gang,et al.  Analysis of Fourier-domain task-based detectability index in tomosynthesis and cone-beam CT in relation to human observer performance. , 2011, Medical physics.

[33]  Ian A. Cunningham,et al.  Cascaded models and the DQE of flat-panel imagers: noise aliasing, secondary quantum noise, and reabsorption , 2002, SPIE Medical Imaging.

[34]  Beverly A. Lau,et al.  A scatter correction method for contrast-enhanced dual-energy digital breast tomosynthesis , 2015, Physics in medicine and biology.

[35]  Mehran Ebrahimi,et al.  Anatomical noise in contrast-enhanced digital mammography. Part I. Single-energy imaging. , 2013, Medical physics.

[36]  Wei Zhao,et al.  Three-dimensional linear system analysis for breast tomosynthesis. , 2008, Medical physics.

[37]  A Fenster,et al.  A spatial-frequency dependent quantum accounting diagram and detective quantum efficiency model of signal and noise propagation in cascaded imaging systems. , 1994, Medical physics.

[38]  William Vennart,et al.  ICRU Report 54: Medical imaging—the assessment of image quality: ISBN 0-913394-53-X. April 1996, Maryland, U.S.A. , 1997 .

[39]  K. Hoffmann,et al.  Generalizing the MTF and DQE to include x-ray scatter and focal spot unsharpness: application to a new microangiographic system. , 2005, Medical physics.

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

[41]  Wei Zhao,et al.  Ghosting caused by bulk charge trapping in direct conversion flat-panel detectors using amorphous selenium. , 2005, Medical physics.

[42]  Rebecca Fahrig,et al.  Cascaded systems analysis of the 3D NEQ for cone-beam CT and tomosynthesis , 2008, SPIE Medical Imaging.

[43]  J H Siewerdsen,et al.  Anatomical background and generalized detectability in tomosynthesis and cone-beam CT. , 2010, Medical physics.

[44]  W. S. Snyder,et al.  Report of the task group on reference man , 1979, Annals of the ICRP.

[45]  Thomas Mertelmeier,et al.  Experimental validation of a three-dimensional linear system model for breast tomosynthesis. , 2008, Medical physics.

[46]  John M. Boone Spectral modeling and compilation of quantum fluence in radiography and mammography , 1998, Medical Imaging.

[47]  Bo Zhao,et al.  Optimization of detector operation and imaging geometry for breast tomosynthesis , 2007, SPIE Medical Imaging.

[48]  Wei Zhao,et al.  The Effect of Amorphous Selenium Thickness on Imaging Performance of Contrast Enhanced Digital Breast Tomosynthesis , 2012, Digital Mammography / IWDM.

[49]  Erik Fredenberg,et al.  Evaluation of photon-counting spectral breast tomosynthesis , 2011, Medical Imaging.

[50]  Jeffrey H Siewerdsen,et al.  Cascaded systems analysis of noise reduction algorithms in dual-energy imaging. , 2008, Medical physics.

[51]  Nooshin Kiarashi,et al.  A quantitative metrology for performance characterization of five breast tomosynthesis systems based on an anthropomorphic phantom. , 2016, Medical physics.

[52]  Wei Zhao,et al.  Breast Structural Noise in Digital Breast Tomosynthesis and Its Dependence on Reconstruction Methods , 2010, Digital Mammography / IWDM.

[53]  J A Rowlands,et al.  Effects of characteristic x rays on the noise power spectra and detective quantum efficiency of photoconductive x-ray detectors. , 2001, Medical physics.

[54]  Serge Muller,et al.  Digital Mammography Using Iodine-Based Contrast Media: Initial Clinical Experience With Dynamic Contrast Medium Enhancement , 2005, Investigative radiology.

[55]  Serge Muller,et al.  Evaluation of tumor angiogenesis of breast carcinoma using contrast-enhanced digital mammography. , 2006, AJR. American journal of roentgenology.

[56]  Felix Diekmann,et al.  Evaluation of contrast-enhanced digital mammography. , 2011, European journal of radiology.

[57]  Erik Fredenberg,et al.  Contrast-enhanced spectral mammography with a photon-counting detector. , 2010, Medical physics.

[58]  Wei Zhao,et al.  The effect of angular dose distribution on the detection of microcalcifications in digital breast tomosynthesis. , 2011, Medical physics.

[59]  Wei Zhao,et al.  Nonuniform angular dose distribution in digital breast tomosynthesis for increased conspicuity of small high contrast objects , 2009, Medical Imaging.

[60]  R Speller,et al.  Quantitative contrast-enhanced mammography for contrast medium kinetics studies. , 2009, Physics in medicine and biology.

[61]  J H Siewerdsen,et al.  Optimization of dual-energy imaging systems using generalized NEQ and imaging task. , 2006, Medical physics.

[62]  J. H. Hubbell,et al.  Tables of X-Ray Mass Attenuation Coefficients and Mass Energy-Absorption Coefficients 1 keV to 20 MeV for Elements Z = 1 to 92 and 48 Additional Substances of Dosimetric Interest , 1995 .