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Dual-Energy Computed Tomography

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1 Dual-Energy Computed Tomography
Reza Forghani, MD, PhD, Bruno De Man, PhD, Rajiv Gupta, MD, PhD  Neuroimaging Clinics  Volume 27, Issue 3, Pages (August 2017) DOI: /j.nic Copyright © 2017 The Authors Terms and Conditions

2 Fig. 1 Typical X-ray spectrum for X-ray tube voltages of 80 kVp and 140 kVp, including inherent X-ray tube filtration (generated with the XSpect simulator). The peaks represent characteristic lines of a tungsten anode, and the continuous spectrum is the result of bremsstrahlung. This example illustrates the polychromatic nature of the X-ray beams used for DECT scanning. For DECT scanning, it is desirable to achieve as much separation as possible between the low-energy and high-energy spectra. In addition, the tube voltage used must not be too low or too high. If it is too low, it will be excessively absorbed by the body, yielding little information; if it is too high, it will not yield useful information because of poor tissue contrast. In routine DECT, kVp (low-energy spectrum) and kVp (high-energy spectrum) are commonly used settings for this purpose, although there may be variations depending on the scanner model, filters used, or the specific clinical application at hand. (Courtesy of Reza Forghani, MD, PhD, Montreal, Quebec, Canada and Bruno De Man, PhD, Niskayuna, NY.) Neuroimaging Clinics  , DOI: ( /j.nic ) Copyright © 2017 The Authors Terms and Conditions

3 Fig. 2 Example of tissues with weak and strong spectral characteristics based on their elemental composition. Axial non-contrast-enhanced CT image of the neck acquired in dual-energy mode using a fast kVp switching scanner is shown (A). Region of interest analysis was performed comparing the spectral Hounsfield unit attenuation curves of muscle (green) to that of the thyroid gland (blue) (B). Most of the soft tissue in the human body, including muscle, is composed of low-Z materials such as oxygen (Z = 8), carbon (Z = 6), and hydrogen (Z = 1). As a result, there is little energy dependency of measured attenuation of muscle on an uninfused study (B; green curves). The thyroid gland, on the other hand, contains iodine (Z = 53) with strong energy dependence due to photoelectric effect. Note the marked energy-dependent increase in its attenuation at low energies approaching the K-edge of iodine (33.2 keV) (B; blue curves). Because most clinically used CT contrast agents are iodine based, iodine’s strong energy dependence can be exploited in a variety of clinical settings. Neuroimaging Clinics  , DOI: ( /j.nic ) Copyright © 2017 The Authors Terms and Conditions

4 Fig. 3 Dual-source DECT (Siemens AG). Schematic illustration of dual-source detector combination scanners with the 2 imaging chains in a nearly orthogonal configuration, allowing the same slice to be scanned simultaneously at the 2 energies. Yellow is used to illustrate the low-energy spectrum, and blue, the high-energy spectrum. Typically, kVp (low energy spectrum) and kVp (high energy spectrum) are used depending on the model, but other combinations may be used for specific applications. Because there are 2 separate source-detector pairs, a filter can be placed to harden the high-energy spectrum. For some higher generation dual-source scanners, it is possible to use a higher kVp for the lower spectrum (90 or 100 instead of 80 kVp) in conjunction with a filter. Because of the limited space in the CT gantry, there is only sufficient space for a smaller second detector, which in turns places restrictions on the usable field of view of the dual-energy CT mode, as shown in the illustration. (Courtesy of Reza Forghani, MD, PhD, Montreal, Quebec, Canada and Bruno De Man, PhD, Niskayuna, NY.) Neuroimaging Clinics  , DOI: ( /j.nic ) Copyright © 2017 The Authors Terms and Conditions

5 Fig. 4 Single-source DECT with rapid kVp switching: GSI (GE Healthcare). Schematic illustration of this type of a single source-detector combination system. Yellow is used to illustrate the low-energy spectrum, and blue, the high energy spectrum, typically 80/140 kVp. DECT projection data are acquired by very fast switching between low- and high-energy spectra combined with fast sampling capabilities of a proprietary, garnet-based scintillator detector with low afterglow for spectral separation at each successive axial or spiral view. (Courtesy of Reza Forghani, MD, PhD, Montreal, Quebec, Canada and Bruno De Man, PhD, Niskayuna, NY.) Neuroimaging Clinics  , DOI: ( /j.nic ) Copyright © 2017 The Authors Terms and Conditions

6 Fig. 5 Layered or sandwich detector DECT (Philips Healthcare). Schematic illustration of this type of a single source-detector combination system in which spectral separation is achieved at the level of the detector. This system takes advantage of the polychromatic nature of the beam produced at the source and highly specialized detectors that consist of 2 layers having maximal sensitivity for different energies. The first layer (yellow) preferentially absorbs the low-energy photons, by design approximately 50% of the total incident photon flux. The second layer (blue) absorbs the remaining high-energy photons. (Courtesy of Reza Forghani, MD, PhD, Montreal, Quebec, Canada and Bruno De Man, PhD, Niskayuna, NY.) Neuroimaging Clinics  , DOI: ( /j.nic ) Copyright © 2017 The Authors Terms and Conditions

7 Fig. 6 Single-source DECT with beam filtration at the source: TwinBeam DECT (Siemens AG). Schematic illustration of this type of a single source-detector combination system in which a split filter consisting of gold and tin is placed at the output of the tube, resulting in separation of the beam into low- and high-energy spectra. The corresponding halves of the detector are then used for detection of the low- and high-energy spectra. (Courtesy of Reza Forghani, MD, PhD, Montreal, Quebec, Canada and Bruno De Man, PhD, Niskayuna, NY.) Neuroimaging Clinics  , DOI: ( /j.nic ) Copyright © 2017 The Authors Terms and Conditions

8 Fig. 7 Sequential scanning approaches to DECT scanning. This is one of the earliest and technologically most straightforward ways to obtain DECT scans. With this approach, the spectral data at 2 different energies are acquired sequentially at the same table position, or a range of table positions using different tube voltages. Although simpler to implement, this approach has significant limitations because of the delay between the acquisition of low- and high-energy data, as discussed in the text. One way to minimize the delay between the acquisition of low- and high-energy data is by alternating scanning of high and low kVp data for each gantry rotation, instead of scanning the entire volume with multiple rotations at one energy followed by the other. (Courtesy of Reza Forghani, MD, PhD, Montreal, Quebec, Canada and Bruno De Man, PhD, Niskayuna, NY.) Neuroimaging Clinics  , DOI: ( /j.nic ) Copyright © 2017 The Authors Terms and Conditions

9 Fig. 8 Schematic illustration of a photon counting scanner, one of the most advanced spectral CT systems currently under development. These scanners use photon counting detectors to resolve the energy of individual photons or photon bins. Theoretically, these highly specialized and efficient detectors would count each individual incident X-ray photon and measure its energy. Narrow selectable subranges (or bins) of the spectrum can then be used to detect and classify materials based on their spectral response, enabling robust multienergy material characterization. (Courtesy of Reza Forghani, MD, PhD, Montreal, Quebec, Canada and Bruno De Man, PhD, Niskayuna, NY.) Neuroimaging Clinics  , DOI: ( /j.nic ) Copyright © 2017 The Authors Terms and Conditions

10 Fig. 9 Examples of abdominal images obtained with a full field-of-view photon-counting CT scanner prototype developed by GE Healthcare and installed at Rabin Medical Center, Israel in Two different slices are shown in 2 different representations: (A, C) monochromatic images at 70 keV and (B, D) effective Z images. Different Z numbers are mapped to different colors. The images were obtained with a 32-slice helical scan, 1-second gantry rotation, 140 kVp and 140 mA. (Courtesy of Dr Ofer Benjaminov, Rabin Medical Center, Israel; with permission.) Neuroimaging Clinics  , DOI: ( /j.nic ) Copyright © 2017 The Authors Terms and Conditions


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