Dual Energy CT
Computed tomography derives images from attenuation of an X-ray beam as it passes through tissue. At typical diagnostic imaging X-ray photon energy levels, there are two main interactions which result in attenuation of the X-ray photon beam: the photoelectric effect, in which a photon is absorbed and an electron is ejected, and Compton scatter, in which a photon collides with a free electron and is deflected. The probability of a photoelectric effect interaction is proportional to the cube of the atomic number and inversely proportional to the cube of the energy level of the incident photon. The probability of a photoelectric effect interaction (and the associated attenuation associated with the effect) increases at levels where the photon energy matches the energy of the free electrons of the tissue, with the highest probability occurring at what is called the “K edge” of a material, where the photon energy is at the energy level of the electrons in the inner-most atomic shell (K shell) of the tissue.
Standard CT uses one polychromatic spectrum to generate images. Tissue composed of different materials can sometimes have same or similar CT numbers at a given energy level. Spectral CT addresses this by using spectra of varying energy levels, allowing for differentiation of materials which have different attenuation characteristics at these different energy levels. In clinical practice, this is done with two different energy spectra (hence the term “dual energy CT”) of low energy and high energy (often 80 kVp and 140 kVp).
There are multiple methods by which this can be accomplished: (1) dual-source, dual-energy, in which there are two X-ray sources producing two different spectra; (2) single-source, dual-energy, in which a single X-ray source either alternates between low- and high-energy production or is filtered into high- and low-energy components before entering the patient; and (3) detector-based, which uses filtering at the detector level to separate high-energy from low-energy data.
Following acquisition, image data can be reconstructed in several different ways, including:
Virtual monochromatic images: an image set is created from the predicted attenuation of a beam at a given energy level
Blended images: an image set is created by blending the low- and high-energy data at a specified ratio
Material decomposition algorithms can also be used to create additional images (for example, removing the contribution of iodine to produce virtual noncontrast images, or removing the contribution of calcium for bone removal).
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