Optimization of beam parameters and iodine quantification in dual-energy contrast enhanced digital breast tomosynthesis

Dual-Energy Contrast Enhanced Digital Breast Tomosynthesis (DE CEDBT) is a promising technique for breast cancer detection, which combines the strengths of functional and 3D imaging. In the present study, we first focused on the optimization of the acquisition parameters for the low and high-energy projections, which leads to a trade-off between image quality in the recombined slices and the Average Glandular Dose (AGD) delivered to the patient. Optimized parameters were found and experimentally validated on phantom images. Then, we addressed the problem of iodine quantification in the recombined slices. In DE CEDBT, iodine quantification is limited by the z-resolution, due to the restricted angle acquisition inherent to tomosynthesis. We evaluated the lesion thickness above which determination of iodine volumetric concentration is possible. For lesions below this thickness, estimation of iodine concentration is possible if a priori information or a model on the shape of the lesion is available. Iodine quantification for lesions located near the breast boundary is also challenging, due to scatter border effects and variation of the breast thickness in this region. A scatter correction algorithm based on a deconvolution scheme and a thickness compensation algorithm were applied on the low and high-energy projections. Corrected images showed a more accurate quantification of iodine.

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

[2]  J A Seibert,et al.  Monte Carlo simulation of the scattered radiation distribution in diagnostic radiology. , 1988, Medical physics.

[3]  Lubomir M. Hadjiiski,et al.  A comparative study of limited-angle cone-beam reconstruction methods for breast tomosynthesis. , 2006, Medical physics.

[4]  P M Joseph,et al.  The effects of scatter in x-ray computed tomography. , 1982, Medical physics.

[5]  Stephen J. Glick,et al.  A computer simulation for evaluating dual-energy contrast-enhanced breast tomosynthesis , 2007, SPIE Medical Imaging.

[6]  Serge Muller,et al.  Dual-energy contrast enhanced digital breast tomosynthesis: concept, method, and evaluation on phantoms , 2007, SPIE Medical Imaging.

[7]  R. Paola,et al.  Correlation Between Contrast Enhancement in Dynamic Magnetic Resonance Imaging of the Breast and Tumor Angiogenesis , 1994, Investigative radiology.

[8]  John M Boone,et al.  Evaluation of scatter effects on image quality for breast tomosynthesis , 2007, SPIE Medical Imaging.

[9]  J E Holden,et al.  Correction for scattered radiation and other background signals in dual-energy computed tomography material thickness measurements. , 1988, Medical physics.

[10]  G. Gasparini,et al.  Clinical significance of determination of surrogate markers of angiogenesis in breast cancer. , 2001, Critical reviews in oncology/hematology.

[11]  J. H. Hubbell,et al.  Relativistic atomic form factors and photon coherent scattering cross sections , 1979 .

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

[13]  Serge Muller,et al.  Dual-energy contrast enhanced digital mammography using a new approach for breast tissue canceling , 2007, SPIE Medical Imaging.

[14]  Serge Muller,et al.  Development of contrast digital mammography. , 2002, Medical physics.

[15]  D. Jaffray,et al.  Cone-beam computed tomography with a flat-panel imager: magnitude and effects of x-ray scatter. , 2001, Medical physics.

[16]  A. Kak,et al.  Simultaneous Algebraic Reconstruction Technique (SART): A Superior Implementation of the Art Algorithm , 1984, Ultrasonic imaging.

[17]  J A Seibert,et al.  X-ray scatter removal by deconvolution. , 1988, Medical physics.

[18]  John Kaufhold,et al.  Thickness-dependent scatter correction algorithm for digital mammography , 2002, SPIE Medical Imaging.