**3.3 Dual energy imaging methods**

136 Imaging of the Breast – Technical Aspects and Clinical Implication

The ability to determine material composition from dual energy techniques fundamentally results from the fact that the linear attenuation coefficient of X-ray absorption, ((E)), for an element has a unique functional dependence on photon energy. Over the range of x-ray photon energies used, the attenuation coefficient is dominated by two major attenuation processes: the photoelectric effect and Compton scattering. A major simplifying factor of the analysis is that each of these two processes has a fixed and unique functional dependence on

where p(E) is the linear attenuation as a function of energy due to the photoelectric effect and c(E) is the linear attenuation as a function of energy due to the Compton scattering

A consequence of this relationship is that the energy dependence of any material's attenuation coefficient can be expressed as the linear combination of any two other materials. Therefore, each material can be characterized by two density values, pA p*B*, which are derived from the attenuation measured at two different kVp spectra, A(E), B(E). As in,

The important consequence for image formation is that these two material density values are available to encode the pixel values apart from or in combination with Hounsfield units in the case of CT imaging. Materials with similar density can now be differentiated based on average atomic number. Of particular interest is the use of contrast agents with atomic numbers significantly different from the usual materials present in the body as these agents will show up on images in high contrast to the normal materials of the body. Moreover, because the dual energy analysis makes explicit use of the energy dependence of the attenuation, the beam hardening artifacts are absent here, a distinct advantage over conventional CT. Also, in the dual energy technique as opposed to the conventional approach, the accuracy of the CT number associated with pixels is not affected by the beam hardening corrections which must approximate the energy dependent attenuation with data

Dual energy imaging was used in CT scanning as long ago as 1976 (Alvarez and Macovski 1976) when it was also being used for the exact determination of the atomic number of elements (Rutherford, Pullan et al. 1976). It has been used for mammography as well. Johns et al. described the first applications of dual energy imaging to mammography (Johns, Drost et al. 1983). Later work optimized the method to get the best SNR with minimum dose (Johns and Yaffe 1985). Since that time, several articles were published about optimization of parameters in dual energy breast imaging. Boone at al. (Boone, Shaber et al. 1990) analyzed detector parameters, effects of X-ray parameters and filtrations and the effect of scatter on the quality of the dual energy images. Kappadath et al. (Kappadath, Shaw et al. 2004) used digital subtraction techniques and a method they developed called DEDM (Dual Energy

Dual energy techniques have also been used to improve Computed Tomography (CT) imaging. While 3D CT scans and the use of Iodine (I) as a contrast agent have, on their own,

Digital Mammography) to improve the visibility of micro calcifications.

μ(E) = xμ�(E) + yμ�(E) (1)

μ(E) = xμ�(E) + yμ�(E) = p�μ�(E) + p��(E) (2)

energy that can serve as a linear basis set for any material. That is,

effect and x and y are material specific constants.

from a single energy value.

**3.2 Dual energy imaging applications** 

Generally dual energy imaging is implemented by use of X-ray tube voltage switching to obtain two images; one at low and one at high kVp values. To avoid motion artifacts between the two images quick changes in tube voltage are necessary.

Different methods and detectors have also been developed for dual energy imaging. Coello et al. (Coello, Dinten et al. 2007) built a system where, instead of switching voltages, a filter wheel containing multiple filter materials is rotated in front of the X-ray tube, providing different X-ray spectra. This paper also provides an excellent overview of the theory of dual energy imaging and its optimization for best signal to noise ratio and image contrast.
