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Dual-energy CT: minimal essentials for radiologists

Dual-energy CT: minimal essentials for radiologists Dual-energy CT, the object is scanned at two different energies, makes it possible to identify the characteristics of materials that cannot be evaluated on conventional single-energy CT images. This imaging method can be used to perform material decomposition based on differences in the material-attenuation coefficients at different energies. Dual-energy analyses can be classified as image data-based- and raw data-based analysis. The beam-hardening effect is lower with raw data-based analysis, resulting in more accurate dual-energy analysis. On virtual monochromatic images, the iodine contrast increases as the energy level decreases; this improves visualization of contrast-enhanced lesions. Also, the application of material decomposition, such as iodine- and edema images, increases the detectability of lesions due to diseases encountered in daily clinical practice. In this review, the minimal essentials of dual-energy CT scanning are presented and its usefulness in daily clinical practice is discussed. Keywords Dual-energy CT · Computed tomography · Material decomposition · Detectability Introduction imaging. In this review, the basics of dual-energy CT and its usefulness in daily clinical practice are discussed. Although the number of hospitals with dual-energy com- puted tomography (CT) scanners has increased, few facilities use the instruments in daily clinical practice. There are vari- X‑ray generation and energy spectrum ous analytical methods applicable to dual-energy CT, how- ever, its clinical benefits are not widely applied. The dual- In CT scanners, the x-rays are generated in the x-ray tube energy CT method scans the object at two different energies (Fig. 1a). To produce the x-ray beams, an electron stream (tube voltages); it can be used to perform material decom- emitted from the cathode is focused into a narrow beam position based on the difference in the material-attenuation that bombards a small focal spot on the tungsten target coefficients obtained at different energies. It also makes it anode [1]. The x-ray beams are composed of photons in a possible to identify the characteristics of materials that can- wide continuum of energies (kilo electron volt; keV); the not be evaluated on conventional single-energy CT scans. beams are referred to as “polychromatic x-rays” that form The ability to detect lesions encountered in clinical practice the x-ray spectrum (Fig.  1b). The maximum value of the is improved by applying virtual monochromatic images or photon energy in the x-ray spectrum matches the x-ray tube material decomposition, such as iodine- and edema images. kilovoltage (kV); if the tube voltage is 120 kV, the maximum Effective atomic number- and electron density analysis may energy of the spectrum is 120 keV (Fig. 2). The x-ray spec- reveal the properties of materials whose evaluation is dif- trum depends on the tube voltage; Fig. 2 shows x-ray spectra ficult on conventional single-energy CT scans. Dual-energy for x-ray tube voltages of 80, 100, 120, and 140 kV) [2]. CT scans may be useful in a wide range of specialties, The effective x-ray energy is often used as a representa- e.g. emergency medicine, radiation therapy, and autopsy tive value of a polychromatic x-ray photon spectrum; the effective energy is the energy of a polychromatic x-ray expressed as the energy of a monochromatic x-ray with * Fuminari Tatsugami equivalent interactions. Specifically, the effective energy is sa104@rg8.so-net.ne.jp measured using an absorber composed of aluminum (Al) or copper (Cu). The CT attenuation number expressed as Department of Diagnostic Radiology, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551, Japan Vol.:(0123456789) 1 3 548 Japanese Journal of Radiology (2022) 40:547–559 Scanning and analysis methods Principles of dual‑energy CT In general, a material has a different CT number at different energy levels [4–6]; the degree of this difference depends on the material’s elemental composition (Fig. 3). The CT number of a material relates to its linear attenuation coef- ficient [7 ] and is not unique for any given material. Materials can have a similar CT number even when their elemental composition is different. On conventional single-energy CT images, it is often difficult to distinguish between two materials (e.g. calcium and iodine) because there is a considerable overlap in their CT numbers [7]. Consequently, single-energy CT yields limited information on the material composition of tissues (Fig. 4). On dual-energy CT images, materials with different elemental compositions can be differentiated and quantified by comparing their CT number at the two different energy Fig. 1 When accelerated electrons emitted from the cathode bombard the tungsten target anode, x-ray beams are produced (a). The x-ray levels (Fig. 4). beams are composed of photons in a broad continuum of energies that form the x-ray spectrum (b) Types of dual‑energy CT scanners Vendors have produced scanners for clinical use that apply different dual-energy technologies [2 , 8]. Two independent x-rays are used at the fast tube-voltage switching, sequential scan, and dual-source CT system. Commonly, 70–100 kVp and 135–150 kVp are routinely set for dual-energy CT scan- ning. Some vendors use only one x-ray source; the beam is separated into low- and high-energy spectra at the level of the detector (dual-layer system) or at the tube output (split filter system). Fig. 2 The x-ray spectrum varies depending on the tube voltage. The maximum value of the x-ray spectrum (keV) is equal to the x-ray tube kilovoltage (kV) Hounsfield units (HU) at approximately 65–70 keV on vir - tual monochromatic images (VMIs) is equivalent to the HU on single-energy CT images acquired at 120 kV [3]. There- fore, VMIs acquired at 65–70 keV are almost equivalent to single-energy CT images obtained at 120 kV. Fig. 3 A material has different CT numbers at different energy lev - els. The degree of the difference depends on the material’s elemental composition 1 3 Japanese Journal of Radiology (2022) 40:547–559 549 the image-noise level on low- and high-tube voltage scans, should be almost the same. If the image quality of one scan is poor, the quality of the final image will also be poor. It is desirable to increase the tube current for low-voltage scans. The better these requirements are satisfied, the better is the accuracy of dual-energy analysis. Dual‑energy CT analysis methods Dual-energy analysis methods can be classified into image data-based analysis (Fig.  5) and raw data-based analysis (Fig. 6) [10]. Dual-energy scans are post-processed before (raw data-based analysis) or after (image-based analysis) the reconstruction of high- and low-energy images to create various dual-energy CT applications. For image-based analysis (Fig. 5), the x-ray paths for the Fig. 4 On conventional single-energy CT images, two materials can high- and low-tube voltages need not be perfectly matched as often not be distinguished due to considerable overlap in their CT long as the two reconstructed images are spatially matched. numbers. On dual-energy CT scans, materials with different elemen- tal compositions can be differentiated and quantified by comparing Dual-energy data are processed after the reconstruction of their CT numbers at two different energy levels the high- and low-energy images to create various dual- energy CT applications [11, 12]. The weighted average Common requirements for dual‑energy CT scanning images at various tube voltages can be obtained by blend- ing high- and low-energy images (blended image). Iodine- For accurate dual-energy analysis, images acquired with two map images can be created by extracting the iodine (material decomposition); virtual non-contrast images by subtracting different energies (voltages) should be temporally and spa- tially matched. The following are common requirements for the iodine map images from the weighted average images. Dual-energy CT images created by image-based analysis dual-energy CT scanning [9]. (1) High- and low-energy data should be acquired simul- contain various artifacts, e.g. beam hardening-, motion-, and helical artifacts. Consequently, they are less accurate than taneously or with a small interval. A prolonged time gap results in a spatial mismatch between the two data sets due scans acquired with the raw-data based approach. For raw data-based analysis (Fig. 6), the x-ray paths for to patient movement, gastrointestinal peristalsis, or the flow of contrast material. (2) The energy difference between two the high- and low-tube voltages must match exactly. After material raw-data (iodine and water, or bone and water are data should be large. As dual-energy CT analysis is based on the contrast between the x-ray absorption of the two- the reference materials) are processed directly by material decomposition, image reconstruction is performed [11, 12]. energy data, a smaller energy difference results in a lower contrast-to-noise ratio. (3) The image quality, especially The human body is considered to contain a mixture of two Fig. 5 Image-based approach for dual-energy CT analysis. The x-ray paths at high- and low-tube voltages do not need to be perfectly matched. Dual- energy data are processed after the reconstruction of high- and low-energy images, then various applications are created. Dual- energy CT images created by image-based analysis contain various artifacts, e.g. beam hardening-, motion-, and helical artifacts 1 3 550 Japanese Journal of Radiology (2022) 40:547–559 Fig. 6 Raw data-based approach for dual-energy CT analysis. The x-ray paths at the high- and low-tube voltages must match exactly. Material raw data are processed directly by material decomposition, then image reconstruction is performed. The obtained CT applications have fewer beam-hardening effects and artifacts related to the CT reconstruction kernel than image-based analysis different materials, generally iodine and water, and the con- raw data-based analysis, beam hardening is corrected during tent of each material is calculated from the original raw-data the generation of material projection data from the origi- set. Raw data-based analysis has a greater variety of dual- nal projection data. Therefore, dual-energy CT images are energy CT applications than image-based analysis. VMI-, less affected by beam-hardening artifacts (Fig.  7), and their electron density-, and effective atomic-number analyses analysis is more accurate than image-based analysis [18]. require raw data analysis [13]. On the other hand, artifacts related to the CT recon- The choice between raw data- and image-based analysis struction kernel such as blaring and over- and undershoot- depends on the dual-energy CT hardware. Currently, raw ing appear after image reconstruction. In raw data-based data-based analysis is used with fast tube-voltage switching-, analysis, as dual-energy data are processed before image sequential scanning-, and dual-layer detector systems. Dual- reconstruction, various dual-energy CT applications are less source CT scanners are used for image-based analysis [10]. affected by these artifacts. Table  1 compares image- and raw data-based analyses. Advantages of raw data‑ over image‑based analysis Raw data-based analysis elicits lower beam-hardening Single energy‑like images effects and fewer artifacts related to the CT reconstruction kernel [14–16]. This results in more accurate CT number Virtual monochromatic images measurements in the scanned object. Beam hardening on CT scans is attributable to the prefer- Polychromatic x-ray beams delivered with single-energy CT ential attenuation of low- rather than high-energy x-ray pho- are composed of photons at many energy levels that form the tons as a polychromatic x-ray passes through the object. This x-ray spectrum. VMIs are images that simulate CT images can result in streaks and dark bands, particularly after pass- obtained with monochromatic x-rays of arbitrary energy. ing through highly attenuated areas such as sites of severe In dual-energy processing, the linear attenuation coef- calcification, sites with high concentrations of contrast mate- ficient (μ) within a certain voxel can be expressed by the rial, and metallic objects such as stents and coils [17]. In formula Fig. 7 CT image processed with image-based analysis (a) and raw data-based analysis (b). In image-based analysis, beam-hardening artifacts from facial bones degrade the image quality (arrowheads). As the CT image processed with raw data-based analysis rather than image-based analysis exhibits lower beam-hardening artifacts, the acquired CT number would be accurate 1 3 Japanese Journal of Radiology (2022) 40:547–559 551 Table 1 Comparison of image- and raw data-based analysis Analysis of dual-energy CT Image-based analysis Raw data-based analysis Scanning Projection-data at two energies that do not Projection-data at two energies must match need to match Postprocessing of dual-energy data After reconstruction Before reconstruction Dual-energy CT applications Limited applications Wide variety of applications Image quality Contains various artifacts Less affected by various artifacts insufficiency (Fig.  9). As the image noise is increased on (E) =  (E)c +  (E)c , 1 1 2 2 VMIs at lower keV settings, the application of a noise reduc- where the mass density of the two basis materials (c , c ) tion technique, e.g. iterative reconstruction, is recommended. 1 2 are estimated from material decomposition, and the linear When the energy level of VMIs increases (i.e., higher attenuation coefficients of the two basis materials [μ (E), than 80 keV), the contrast between tissues is reduced, ren- μ (E)] are known. The CT number at a certain energy level dering metallic artifacts less noticeable. Nonetheless, to (keV) is defined by the formula overcome severe artifacts from dense materials such as metallic clips, coils, and stents, we suggest the use of metal CT number(E) = 1000 (E) −  (E) ∕ (E), water water artifact reduction software (Fig. 10). where μ (E) is the linear attenuation coefficient of water. water Spectral HU curves Using the two formulae, the CT number at arbitrary energy levels (keV) can be obtained (Fig. 8). VMIs can be used to create spectral HU curves on a work- The CT attenuation number at approximately 65–70 keV station. By setting a region of interest (ROI) in a tissue and on VMIs is equivalent to the number on single-energy CT plotting the average CT number in the ROI at each mono- scans acquired at 120 kV [3]. Therefore, VMIs in this energy chromatic energy (e.g. from 40 to 140 keV) of the VMI, range are often selected as the standard images. Generally, spectral HU curves are obtained (Fig. 11). Since the shape of the image noise on VMIs obtained in this energy range is the curve varies with the mean attenuation characteristics in the lowest [3, 14]. the ROI tissue, this facilitates the characterization of specific As with single-energy CT scans performed at low-tube tissue types and is useful for component analysis and the voltage (e.g. 80 or 100 kVp), the iodine contrast increases acquisition of a differential diagnosis. as the energy level of the VMI decreases (i.e. energy levels The attenuation of soft tissue and of high atomic number lower than 60 keV); this improves visualization of contrast- materials such as iodine and bone are increased at lower enhanced lesions. By taking advantage of this characteristic, energies. The attenuation of water is zero at all energies; that VMIs at 40–50 keV generated from dual-energy CT scans of fat is decreased at lower energies (Fig. 11). The presence allow for a contrast material dose reduction of 40–60% of fat is suggested when the curve pattern in the ROI of a [19–21], this is especially important in patients with renal specific tissue indicates decreased attenuation at lower keV. Fig. 8 Virtual monochromatic images obtained at 40 (a), 70 (b), and attenuation number on approximately 65–70  keV virtual monochro- 140  keV (c) (window level/width; 30/580 HU). On dual-energy CT matic images is equivalent to single-energy CT scans acquired at scans, a monochromatic image, looking as if it had been acquired 120 kV. The iodine contrast increases as the energy level decreases with single energy (keV), can be synthesized arbitrarily. The CT 1 3 552 Japanese Journal of Radiology (2022) 40:547–559 Fig. 9 A 64-year-old woman with hepatocellular carcinoma. CT on the virtual monochromatic 70 keV image (a), whereas it is clearly images during the arterial phase were obtained with a low con- detected on the monochromatic 40 keV image (b), and the iodine map trast material dose (220 mgI/kg) due to renal insufficiency (eGFR, (c) –1 –2 21 ml  min 1.73  m ). Visualization of the liver lesion is insufficient Fig. 10 A 66-year-old man with hepatocellular carcinoma in the caudate lobe (arrows). On the 70 keV virtual monochromatic image (a), metal artifacts from the metallic coil implanted in the left inferior phrenic vein affect tumor detection. On the iodine map applied with metal artifact reduction software (b), the metal artifacts are reduced and the visibility of the tumor is considerably improved This observation helps in the diagnosis of fat-containing dis- eases, e.g. lipid-rich plaques, adrenal adenomas (Fig. 12), and angiomyolipomas. Material decomposition Material decomposition images yield qualitative and quan- titative information about the tissue composition. Two-, three-, and multi-material decomposition algorithms that can be applied to dual-energy CT are commercially avail- able. We present material decomposition images commonly used in clinical practice, i.e. iodine-, virtual non-contrast- enhanced-, and edema images, and the liver fat volume fraction. Fig. 11 Spectral HU curves are obtained by setting a region of inter- est in tissue and plotting the average CT number at each monochro- matic energy. The attenuation of high atomic number materials, such as iodine (insert, yellow circle) increases at lower energies, that of water is zero at all energies (insert, green circle), and that of fat decreases at lower energies (insert, red circle) 1 3 Japanese Journal of Radiology (2022) 40:547–559 553 Fig. 12 Axial monochromatic 70 keV images showing an adrenal adenoma (a) and an adrenal metastasis (b). Based on its CT number (HU = 19), the adenoma is not lipid-rich. At lower energy levels, the CT attenuation of the tumor decreases (a), suggesting that it contains fat. On the other hand, attenuation of the adrenal metastasis is increased at lower energy levels (b) The detectability of gastric and colorectal tumors is Iodine images improved on iodine images (Fig. 15), as is the differentia- tion between malignant and benign lesions [25, 26]. Iodine Using three-material decomposition, iodine images, i.e. images are also useful in patients with acute abdomen such iodine-enhanced images generated by subtracting water from as small-bowel ischemia or gastrointestinal bleeding. They contrast-enhanced dual-energy CT images, are prepared. increase the conspicuity of hypo-attenuating segments in the Iodine images, most commonly used to distinguish between bowel wall, thereby potentially improving the early detection enhanced and non-enhanced lesions, improve visualization of ischemia [27]. They can also help to identify subtle areas of hyper- and hypo-vascular masses. of contrast-medium extravasation for the accurate localiza- The three-material decomposition algorithm enables the tion of the source of gastrointestinal bleeding [28]. generation of a pulmonary blood volume (PBV) map that Contrast-enhanced dual-energy CT scans are valuable represents the iodine distribution in the lung parenchyma; it for the detection and denial of endoleaks after endovascu- can be used as an indicator of pulmonary perfusion [22, 23]. lar aortic repair (EVAR) [29, 30]. While VMIs obtained at PBV maps and iodine images help to identify pulmonary lower energy increase the vessel contrast, blooming- and embolism-associated perfusion defects (Fig. 13). Also, as metallic artifacts decrease the image quality. Iodine images, iodine images indicate the vascularity of pulmonary nodules, on the other hand, improve endoleak conspicuity without an they contribute to their characterization (Fig. 14) [24]. increase in blooming artifacts (Fig. 16). The superior lesion-to-parenchyma contrast on iodine images improves lesion conspicuity and the delineation of Virtual non‑contrast enhanced image lesion margins, thereby contributing to the reliable recog- nition of small lesions or only slightly attenuating tumors. Using three material decomposition, virtual non-contrast- The images also help to differentiate among enhanced-, enhanced (VNC) images can be generated by subtracting the non-enhanced-, and pseudo-enhanced tissue. Iodine-water iodine component from the contrast-enhanced dual-energy material decomposition on dual-energy CT images facili- CT image. Such VNC images facilitate the differentiation tates estimation of the iodine concentration (mg/ml) in tis- of calcifications or high-attenuation materials from iodine- sues [11]. enhanced tissues. The acquisition of VNC images may 1 3 554 Japanese Journal of Radiology (2022) 40:547–559 Fig. 13 A 67-year-old woman with pulmonary-tumor throm- botic microangiopathy. The tumor embolism was too small for its detection on the contrast- enhanced CT scan. Catheteriza- tion demonstrated tumor embo- lism. Iodine maps (a, b) show areas with decreased blood flow in the right lung (circle), a find- ing consistent with a defect on lung perfusion scintigraphy (c, d) (arrows) Fig. 14 A 76-year-old man with two pulmonary nodules in the right peripheral nodule (arrowhead) is not enhanced. Pathologically, the lung. On the 70 keV virtual monochromatic image (a), the degree of proximal nodule was identified as an adenocarcinoma and the periph- enhancement is similar for both nodules. The iodine map (b) shows eral nodule as an infarction. c PET-CT image (the maximum stand- that the nodule at the proximal site (arrow) is highly vascular; the ardized uptake value of the tumor was 6.4) obviate radiation exposure when unenhanced CT scans are However, the image quality of VNC images is decreased needed. by a rough texture and poor spatial resolution. When the iodine concentration is very high, incomplete iodine removal 1 3 Japanese Journal of Radiology (2022) 40:547–559 555 Fig. 15 A 71-year-old man with cancer of the ascending colon. Virtual monochromatic image at 70 keV (a) and iodine map (b) during the arterial phase are shown. The iodine map yields better conspicuity than the monochromatic 70 keV image. c PET-CT image (the maximum standardized uptake value of the tumor was 6.1) Fig. 16 A 75-year-old man with endoleak after endovascular aortic are shown. The vessel contrast and the endoleak delineation (arrow) repair. Virtual monochromatic images at 70 keV (a), 40 keV (b), and are better on the 40 keV image and the iodine map than on the mono- a color image of the iodine map (c) obtained with CT angiography chromatic 70 keV image 1 3 556 Japanese Journal of Radiology (2022) 40:547–559 Fig. 17 A 77-year-old woman who received gastrografin orally. The virtual monochro- matic image at 70 keV (a) and the virtual non-contrast enhanced image (b) were obtained after unenhanced dual-energy CT. On the virtual non-contrast enhanced image (b), iodine in the small intestine is well removed. Iodine removal from the stomach is incomplete (dotted circle), suggesting that the iodine concentration was very high. During the virtual non-contrast reconstruction process, the volume of the cal- cification on the aortic wall was reduced (arrows) is commonly observed [31]. In addition, tiny- and not highly the bone marrow; these images have a high correlation with attenuated calcific areas may be lost during the VNC recon - fat-suppressed T2-weighted images [33, 35]. The diagnosis struction process [32] (Fig. 17). of early bone fractures on BME images requires less time than does magnetic resonance imaging during which patients Edema images must be still for a prolonged time. For the diagnosis and management of acute ischemic Edema images generated from dual-energy CT scans are stroke, the detection of edema in the gray matter is essen- useful for the detection of early bone fractures [33–35] and tial; edema maps generated from dual-energy CT scans were acute ischemic stroke [36, 37]. reported to be useful [36, 37]. “X-map”, an application to Under the presumption that the human body contains identify acute ischemic lesions on non-contrast dual-energy water and calcium, in patients with early bone fractures, CT scans [37], creates a virtual gray-matter- and water-con- edema images can help to identify bone marrow edema tent map using three-material decomposition. Lesions on the (BME) (Fig. 18). By reducing the calcium signal from bone, X-map clearly reflect the water content of cerebral edema water density images reflective of BME can be created. induced by acute ischemic stroke. There is a good correla- Lesions on BME images clearly reflect the water content in tion between findings on X-maps and on diffusion-weighted Fig. 18 A 13-year-old man with a distal femur fracture. It is difficult to detect bone marrow edema on the virtual monochromatic 70 keV image (a). On the edema image (b), bone marrow edema (arrow) is visualized in the same area as on the short TI inversion recovery image (c) 1 3 Japanese Journal of Radiology (2022) 40:547–559 557 Fig. 19 A 64-year-old woman with tuberous sclerosis, and focal hepatic steatosis and angiomyolipoma in the right lobe. A virtual monochromatic image obtained at 70 keV (a) and a color image of the fat map (b) are shown. The liver fat volume was 96.9% in the angiomyolipoma, 20.6% in the right-, and 7.8% in the left lobe of the liver images [37]. This method would be useful for the early number of a compound or mixture of materials. The electron development of treatment strategies in patients with acute density, on the other hand, represents the probability of an ischemic stroke. electron being present at a specic fi location. Highly accurate electron densities and effective atomic numbers have been Liver fat volume fraction and liver fibrosis calculated by raw data-based dual-energy analysis [13, 44], estimation but their clinical applicability requires further investigations. Because it is a promising method for obtaining electron Multi-material decomposition algorithms facilitate the density maps, dual-energy CT-based electron density imag- acquisition of the liver fat volume fraction (FVF) on dual- ing has attracted the interest of radiation oncologists. Dur- energy CT scans [38, 39]. It is presented as a volume % ing the planning of radiotherapy, electron density maps are on fat maps and calculated directly from non-contrast dual- generated from single-energy CT scans to determine the energy CT scans (Fig. 19). Fat maps from contrast-enhanced dose distribution in the target tissues [45]. However, the CT CT images are obtained after the creation of VNC images. number and the electron density of tissues are not accurately According to Hyodo et  al. [38], the liver FVF on non- correlated because the CT number depends on not only the enhanced- and dynamic contrast-enhanced dual-energy CT electron density but also the effective atomic number. Elec- images is comparable to the FVF determined by using MR tron-density maps obtained from dual-energy CT scans were spectroscopy. This method can be expected to yield accurate reported to be more accurate than the maps obtained with and reproducible findings for the diagnosis of hepatic stea- conventional radiotherapy planning methods [46, 47]. toses such as non-alcoholic- and alcoholic fatty liver disease. Validation of this method is required before its routine use in the clinical setting [40, 41]. Conclusions Estimating the degree of liver fibrosis has been attempted using dual-energy CT data [42, 43]. Extracellular volume This review presented the basics of dual-energy CT scanning fraction calculated from iodine density images is reported to and its usefulness in daily clinical practice. This technique be useful in estimating the degree of liver fibrosis [42]. Also, makes it possible to identify the characteristics of materi- CT texture analyses, such as gray-level intensity, skewness, als that cannot be evaluated on conventional single-energy kurtosis, and entropy at different energy levels are useful for CT images. We think that familiarity with a wide variety of the diagnosis of clinically significant hepatic fibrosis [43]. dual-energy CT applications and with their limitations facili- These parameters could be a promising biomarker of liver tates the accurate interpretation of CT findings and helps to fibrosis; however, further research is needed for use in clini- improve patient care in routine clinical practice. cal examinations. Declarations Eec ff tive atomic number and electron Conflict of interest K.A. is currently receiving a research grant from density analysis Canon Medical Systems Corp. For the remaining authors none were declared. Effective atomic number- and electron-density analyses are based on raw data-based dual-energy analysis. The effective Open Access This article is licensed under a Creative Commons atomic number (effective Z ) represents the average atomic Attribution 4.0 International License, which permits use, sharing, 1 3 558 Japanese Journal of Radiology (2022) 40:547–559 adaptation, distribution and reproduction in any medium or format, 16. Parakh A, Lennartz S, An C, Rajiah P, Yeh BM, Simeone FJ, as long as you give appropriate credit to the original author(s) and the et al. Dual-energy CT images: pearls and pitfalls. Radiographics. source, provide a link to the Creative Commons licence, and indicate 2021;41(1):98–119. if changes were made. The images or other third party material in this 17. Barrett JF, Keat N. 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Dual-energy CT: minimal essentials for radiologists

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Springer Journals
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Copyright © The Author(s) 2021
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1867-1071
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10.1007/s11604-021-01233-2
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Abstract

Dual-energy CT, the object is scanned at two different energies, makes it possible to identify the characteristics of materials that cannot be evaluated on conventional single-energy CT images. This imaging method can be used to perform material decomposition based on differences in the material-attenuation coefficients at different energies. Dual-energy analyses can be classified as image data-based- and raw data-based analysis. The beam-hardening effect is lower with raw data-based analysis, resulting in more accurate dual-energy analysis. On virtual monochromatic images, the iodine contrast increases as the energy level decreases; this improves visualization of contrast-enhanced lesions. Also, the application of material decomposition, such as iodine- and edema images, increases the detectability of lesions due to diseases encountered in daily clinical practice. In this review, the minimal essentials of dual-energy CT scanning are presented and its usefulness in daily clinical practice is discussed. Keywords Dual-energy CT · Computed tomography · Material decomposition · Detectability Introduction imaging. In this review, the basics of dual-energy CT and its usefulness in daily clinical practice are discussed. Although the number of hospitals with dual-energy com- puted tomography (CT) scanners has increased, few facilities use the instruments in daily clinical practice. There are vari- X‑ray generation and energy spectrum ous analytical methods applicable to dual-energy CT, how- ever, its clinical benefits are not widely applied. The dual- In CT scanners, the x-rays are generated in the x-ray tube energy CT method scans the object at two different energies (Fig. 1a). To produce the x-ray beams, an electron stream (tube voltages); it can be used to perform material decom- emitted from the cathode is focused into a narrow beam position based on the difference in the material-attenuation that bombards a small focal spot on the tungsten target coefficients obtained at different energies. It also makes it anode [1]. The x-ray beams are composed of photons in a possible to identify the characteristics of materials that can- wide continuum of energies (kilo electron volt; keV); the not be evaluated on conventional single-energy CT scans. beams are referred to as “polychromatic x-rays” that form The ability to detect lesions encountered in clinical practice the x-ray spectrum (Fig.  1b). The maximum value of the is improved by applying virtual monochromatic images or photon energy in the x-ray spectrum matches the x-ray tube material decomposition, such as iodine- and edema images. kilovoltage (kV); if the tube voltage is 120 kV, the maximum Effective atomic number- and electron density analysis may energy of the spectrum is 120 keV (Fig. 2). The x-ray spec- reveal the properties of materials whose evaluation is dif- trum depends on the tube voltage; Fig. 2 shows x-ray spectra ficult on conventional single-energy CT scans. Dual-energy for x-ray tube voltages of 80, 100, 120, and 140 kV) [2]. CT scans may be useful in a wide range of specialties, The effective x-ray energy is often used as a representa- e.g. emergency medicine, radiation therapy, and autopsy tive value of a polychromatic x-ray photon spectrum; the effective energy is the energy of a polychromatic x-ray expressed as the energy of a monochromatic x-ray with * Fuminari Tatsugami equivalent interactions. Specifically, the effective energy is sa104@rg8.so-net.ne.jp measured using an absorber composed of aluminum (Al) or copper (Cu). The CT attenuation number expressed as Department of Diagnostic Radiology, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima 734-8551, Japan Vol.:(0123456789) 1 3 548 Japanese Journal of Radiology (2022) 40:547–559 Scanning and analysis methods Principles of dual‑energy CT In general, a material has a different CT number at different energy levels [4–6]; the degree of this difference depends on the material’s elemental composition (Fig. 3). The CT number of a material relates to its linear attenuation coef- ficient [7 ] and is not unique for any given material. Materials can have a similar CT number even when their elemental composition is different. On conventional single-energy CT images, it is often difficult to distinguish between two materials (e.g. calcium and iodine) because there is a considerable overlap in their CT numbers [7]. Consequently, single-energy CT yields limited information on the material composition of tissues (Fig. 4). On dual-energy CT images, materials with different elemental compositions can be differentiated and quantified by comparing their CT number at the two different energy Fig. 1 When accelerated electrons emitted from the cathode bombard the tungsten target anode, x-ray beams are produced (a). The x-ray levels (Fig. 4). beams are composed of photons in a broad continuum of energies that form the x-ray spectrum (b) Types of dual‑energy CT scanners Vendors have produced scanners for clinical use that apply different dual-energy technologies [2 , 8]. Two independent x-rays are used at the fast tube-voltage switching, sequential scan, and dual-source CT system. Commonly, 70–100 kVp and 135–150 kVp are routinely set for dual-energy CT scan- ning. Some vendors use only one x-ray source; the beam is separated into low- and high-energy spectra at the level of the detector (dual-layer system) or at the tube output (split filter system). Fig. 2 The x-ray spectrum varies depending on the tube voltage. The maximum value of the x-ray spectrum (keV) is equal to the x-ray tube kilovoltage (kV) Hounsfield units (HU) at approximately 65–70 keV on vir - tual monochromatic images (VMIs) is equivalent to the HU on single-energy CT images acquired at 120 kV [3]. There- fore, VMIs acquired at 65–70 keV are almost equivalent to single-energy CT images obtained at 120 kV. Fig. 3 A material has different CT numbers at different energy lev - els. The degree of the difference depends on the material’s elemental composition 1 3 Japanese Journal of Radiology (2022) 40:547–559 549 the image-noise level on low- and high-tube voltage scans, should be almost the same. If the image quality of one scan is poor, the quality of the final image will also be poor. It is desirable to increase the tube current for low-voltage scans. The better these requirements are satisfied, the better is the accuracy of dual-energy analysis. Dual‑energy CT analysis methods Dual-energy analysis methods can be classified into image data-based analysis (Fig.  5) and raw data-based analysis (Fig. 6) [10]. Dual-energy scans are post-processed before (raw data-based analysis) or after (image-based analysis) the reconstruction of high- and low-energy images to create various dual-energy CT applications. For image-based analysis (Fig. 5), the x-ray paths for the Fig. 4 On conventional single-energy CT images, two materials can high- and low-tube voltages need not be perfectly matched as often not be distinguished due to considerable overlap in their CT long as the two reconstructed images are spatially matched. numbers. On dual-energy CT scans, materials with different elemen- tal compositions can be differentiated and quantified by comparing Dual-energy data are processed after the reconstruction of their CT numbers at two different energy levels the high- and low-energy images to create various dual- energy CT applications [11, 12]. The weighted average Common requirements for dual‑energy CT scanning images at various tube voltages can be obtained by blend- ing high- and low-energy images (blended image). Iodine- For accurate dual-energy analysis, images acquired with two map images can be created by extracting the iodine (material decomposition); virtual non-contrast images by subtracting different energies (voltages) should be temporally and spa- tially matched. The following are common requirements for the iodine map images from the weighted average images. Dual-energy CT images created by image-based analysis dual-energy CT scanning [9]. (1) High- and low-energy data should be acquired simul- contain various artifacts, e.g. beam hardening-, motion-, and helical artifacts. Consequently, they are less accurate than taneously or with a small interval. A prolonged time gap results in a spatial mismatch between the two data sets due scans acquired with the raw-data based approach. For raw data-based analysis (Fig. 6), the x-ray paths for to patient movement, gastrointestinal peristalsis, or the flow of contrast material. (2) The energy difference between two the high- and low-tube voltages must match exactly. After material raw-data (iodine and water, or bone and water are data should be large. As dual-energy CT analysis is based on the contrast between the x-ray absorption of the two- the reference materials) are processed directly by material decomposition, image reconstruction is performed [11, 12]. energy data, a smaller energy difference results in a lower contrast-to-noise ratio. (3) The image quality, especially The human body is considered to contain a mixture of two Fig. 5 Image-based approach for dual-energy CT analysis. The x-ray paths at high- and low-tube voltages do not need to be perfectly matched. Dual- energy data are processed after the reconstruction of high- and low-energy images, then various applications are created. Dual- energy CT images created by image-based analysis contain various artifacts, e.g. beam hardening-, motion-, and helical artifacts 1 3 550 Japanese Journal of Radiology (2022) 40:547–559 Fig. 6 Raw data-based approach for dual-energy CT analysis. The x-ray paths at the high- and low-tube voltages must match exactly. Material raw data are processed directly by material decomposition, then image reconstruction is performed. The obtained CT applications have fewer beam-hardening effects and artifacts related to the CT reconstruction kernel than image-based analysis different materials, generally iodine and water, and the con- raw data-based analysis, beam hardening is corrected during tent of each material is calculated from the original raw-data the generation of material projection data from the origi- set. Raw data-based analysis has a greater variety of dual- nal projection data. Therefore, dual-energy CT images are energy CT applications than image-based analysis. VMI-, less affected by beam-hardening artifacts (Fig.  7), and their electron density-, and effective atomic-number analyses analysis is more accurate than image-based analysis [18]. require raw data analysis [13]. On the other hand, artifacts related to the CT recon- The choice between raw data- and image-based analysis struction kernel such as blaring and over- and undershoot- depends on the dual-energy CT hardware. Currently, raw ing appear after image reconstruction. In raw data-based data-based analysis is used with fast tube-voltage switching-, analysis, as dual-energy data are processed before image sequential scanning-, and dual-layer detector systems. Dual- reconstruction, various dual-energy CT applications are less source CT scanners are used for image-based analysis [10]. affected by these artifacts. Table  1 compares image- and raw data-based analyses. Advantages of raw data‑ over image‑based analysis Raw data-based analysis elicits lower beam-hardening Single energy‑like images effects and fewer artifacts related to the CT reconstruction kernel [14–16]. This results in more accurate CT number Virtual monochromatic images measurements in the scanned object. Beam hardening on CT scans is attributable to the prefer- Polychromatic x-ray beams delivered with single-energy CT ential attenuation of low- rather than high-energy x-ray pho- are composed of photons at many energy levels that form the tons as a polychromatic x-ray passes through the object. This x-ray spectrum. VMIs are images that simulate CT images can result in streaks and dark bands, particularly after pass- obtained with monochromatic x-rays of arbitrary energy. ing through highly attenuated areas such as sites of severe In dual-energy processing, the linear attenuation coef- calcification, sites with high concentrations of contrast mate- ficient (μ) within a certain voxel can be expressed by the rial, and metallic objects such as stents and coils [17]. In formula Fig. 7 CT image processed with image-based analysis (a) and raw data-based analysis (b). In image-based analysis, beam-hardening artifacts from facial bones degrade the image quality (arrowheads). As the CT image processed with raw data-based analysis rather than image-based analysis exhibits lower beam-hardening artifacts, the acquired CT number would be accurate 1 3 Japanese Journal of Radiology (2022) 40:547–559 551 Table 1 Comparison of image- and raw data-based analysis Analysis of dual-energy CT Image-based analysis Raw data-based analysis Scanning Projection-data at two energies that do not Projection-data at two energies must match need to match Postprocessing of dual-energy data After reconstruction Before reconstruction Dual-energy CT applications Limited applications Wide variety of applications Image quality Contains various artifacts Less affected by various artifacts insufficiency (Fig.  9). As the image noise is increased on (E) =  (E)c +  (E)c , 1 1 2 2 VMIs at lower keV settings, the application of a noise reduc- where the mass density of the two basis materials (c , c ) tion technique, e.g. iterative reconstruction, is recommended. 1 2 are estimated from material decomposition, and the linear When the energy level of VMIs increases (i.e., higher attenuation coefficients of the two basis materials [μ (E), than 80 keV), the contrast between tissues is reduced, ren- μ (E)] are known. The CT number at a certain energy level dering metallic artifacts less noticeable. Nonetheless, to (keV) is defined by the formula overcome severe artifacts from dense materials such as metallic clips, coils, and stents, we suggest the use of metal CT number(E) = 1000 (E) −  (E) ∕ (E), water water artifact reduction software (Fig. 10). where μ (E) is the linear attenuation coefficient of water. water Spectral HU curves Using the two formulae, the CT number at arbitrary energy levels (keV) can be obtained (Fig. 8). VMIs can be used to create spectral HU curves on a work- The CT attenuation number at approximately 65–70 keV station. By setting a region of interest (ROI) in a tissue and on VMIs is equivalent to the number on single-energy CT plotting the average CT number in the ROI at each mono- scans acquired at 120 kV [3]. Therefore, VMIs in this energy chromatic energy (e.g. from 40 to 140 keV) of the VMI, range are often selected as the standard images. Generally, spectral HU curves are obtained (Fig. 11). Since the shape of the image noise on VMIs obtained in this energy range is the curve varies with the mean attenuation characteristics in the lowest [3, 14]. the ROI tissue, this facilitates the characterization of specific As with single-energy CT scans performed at low-tube tissue types and is useful for component analysis and the voltage (e.g. 80 or 100 kVp), the iodine contrast increases acquisition of a differential diagnosis. as the energy level of the VMI decreases (i.e. energy levels The attenuation of soft tissue and of high atomic number lower than 60 keV); this improves visualization of contrast- materials such as iodine and bone are increased at lower enhanced lesions. By taking advantage of this characteristic, energies. The attenuation of water is zero at all energies; that VMIs at 40–50 keV generated from dual-energy CT scans of fat is decreased at lower energies (Fig. 11). The presence allow for a contrast material dose reduction of 40–60% of fat is suggested when the curve pattern in the ROI of a [19–21], this is especially important in patients with renal specific tissue indicates decreased attenuation at lower keV. Fig. 8 Virtual monochromatic images obtained at 40 (a), 70 (b), and attenuation number on approximately 65–70  keV virtual monochro- 140  keV (c) (window level/width; 30/580 HU). On dual-energy CT matic images is equivalent to single-energy CT scans acquired at scans, a monochromatic image, looking as if it had been acquired 120 kV. The iodine contrast increases as the energy level decreases with single energy (keV), can be synthesized arbitrarily. The CT 1 3 552 Japanese Journal of Radiology (2022) 40:547–559 Fig. 9 A 64-year-old woman with hepatocellular carcinoma. CT on the virtual monochromatic 70 keV image (a), whereas it is clearly images during the arterial phase were obtained with a low con- detected on the monochromatic 40 keV image (b), and the iodine map trast material dose (220 mgI/kg) due to renal insufficiency (eGFR, (c) –1 –2 21 ml  min 1.73  m ). Visualization of the liver lesion is insufficient Fig. 10 A 66-year-old man with hepatocellular carcinoma in the caudate lobe (arrows). On the 70 keV virtual monochromatic image (a), metal artifacts from the metallic coil implanted in the left inferior phrenic vein affect tumor detection. On the iodine map applied with metal artifact reduction software (b), the metal artifacts are reduced and the visibility of the tumor is considerably improved This observation helps in the diagnosis of fat-containing dis- eases, e.g. lipid-rich plaques, adrenal adenomas (Fig. 12), and angiomyolipomas. Material decomposition Material decomposition images yield qualitative and quan- titative information about the tissue composition. Two-, three-, and multi-material decomposition algorithms that can be applied to dual-energy CT are commercially avail- able. We present material decomposition images commonly used in clinical practice, i.e. iodine-, virtual non-contrast- enhanced-, and edema images, and the liver fat volume fraction. Fig. 11 Spectral HU curves are obtained by setting a region of inter- est in tissue and plotting the average CT number at each monochro- matic energy. The attenuation of high atomic number materials, such as iodine (insert, yellow circle) increases at lower energies, that of water is zero at all energies (insert, green circle), and that of fat decreases at lower energies (insert, red circle) 1 3 Japanese Journal of Radiology (2022) 40:547–559 553 Fig. 12 Axial monochromatic 70 keV images showing an adrenal adenoma (a) and an adrenal metastasis (b). Based on its CT number (HU = 19), the adenoma is not lipid-rich. At lower energy levels, the CT attenuation of the tumor decreases (a), suggesting that it contains fat. On the other hand, attenuation of the adrenal metastasis is increased at lower energy levels (b) The detectability of gastric and colorectal tumors is Iodine images improved on iodine images (Fig. 15), as is the differentia- tion between malignant and benign lesions [25, 26]. Iodine Using three-material decomposition, iodine images, i.e. images are also useful in patients with acute abdomen such iodine-enhanced images generated by subtracting water from as small-bowel ischemia or gastrointestinal bleeding. They contrast-enhanced dual-energy CT images, are prepared. increase the conspicuity of hypo-attenuating segments in the Iodine images, most commonly used to distinguish between bowel wall, thereby potentially improving the early detection enhanced and non-enhanced lesions, improve visualization of ischemia [27]. They can also help to identify subtle areas of hyper- and hypo-vascular masses. of contrast-medium extravasation for the accurate localiza- The three-material decomposition algorithm enables the tion of the source of gastrointestinal bleeding [28]. generation of a pulmonary blood volume (PBV) map that Contrast-enhanced dual-energy CT scans are valuable represents the iodine distribution in the lung parenchyma; it for the detection and denial of endoleaks after endovascu- can be used as an indicator of pulmonary perfusion [22, 23]. lar aortic repair (EVAR) [29, 30]. While VMIs obtained at PBV maps and iodine images help to identify pulmonary lower energy increase the vessel contrast, blooming- and embolism-associated perfusion defects (Fig. 13). Also, as metallic artifacts decrease the image quality. Iodine images, iodine images indicate the vascularity of pulmonary nodules, on the other hand, improve endoleak conspicuity without an they contribute to their characterization (Fig. 14) [24]. increase in blooming artifacts (Fig. 16). The superior lesion-to-parenchyma contrast on iodine images improves lesion conspicuity and the delineation of Virtual non‑contrast enhanced image lesion margins, thereby contributing to the reliable recog- nition of small lesions or only slightly attenuating tumors. Using three material decomposition, virtual non-contrast- The images also help to differentiate among enhanced-, enhanced (VNC) images can be generated by subtracting the non-enhanced-, and pseudo-enhanced tissue. Iodine-water iodine component from the contrast-enhanced dual-energy material decomposition on dual-energy CT images facili- CT image. Such VNC images facilitate the differentiation tates estimation of the iodine concentration (mg/ml) in tis- of calcifications or high-attenuation materials from iodine- sues [11]. enhanced tissues. The acquisition of VNC images may 1 3 554 Japanese Journal of Radiology (2022) 40:547–559 Fig. 13 A 67-year-old woman with pulmonary-tumor throm- botic microangiopathy. The tumor embolism was too small for its detection on the contrast- enhanced CT scan. Catheteriza- tion demonstrated tumor embo- lism. Iodine maps (a, b) show areas with decreased blood flow in the right lung (circle), a find- ing consistent with a defect on lung perfusion scintigraphy (c, d) (arrows) Fig. 14 A 76-year-old man with two pulmonary nodules in the right peripheral nodule (arrowhead) is not enhanced. Pathologically, the lung. On the 70 keV virtual monochromatic image (a), the degree of proximal nodule was identified as an adenocarcinoma and the periph- enhancement is similar for both nodules. The iodine map (b) shows eral nodule as an infarction. c PET-CT image (the maximum stand- that the nodule at the proximal site (arrow) is highly vascular; the ardized uptake value of the tumor was 6.4) obviate radiation exposure when unenhanced CT scans are However, the image quality of VNC images is decreased needed. by a rough texture and poor spatial resolution. When the iodine concentration is very high, incomplete iodine removal 1 3 Japanese Journal of Radiology (2022) 40:547–559 555 Fig. 15 A 71-year-old man with cancer of the ascending colon. Virtual monochromatic image at 70 keV (a) and iodine map (b) during the arterial phase are shown. The iodine map yields better conspicuity than the monochromatic 70 keV image. c PET-CT image (the maximum standardized uptake value of the tumor was 6.1) Fig. 16 A 75-year-old man with endoleak after endovascular aortic are shown. The vessel contrast and the endoleak delineation (arrow) repair. Virtual monochromatic images at 70 keV (a), 40 keV (b), and are better on the 40 keV image and the iodine map than on the mono- a color image of the iodine map (c) obtained with CT angiography chromatic 70 keV image 1 3 556 Japanese Journal of Radiology (2022) 40:547–559 Fig. 17 A 77-year-old woman who received gastrografin orally. The virtual monochro- matic image at 70 keV (a) and the virtual non-contrast enhanced image (b) were obtained after unenhanced dual-energy CT. On the virtual non-contrast enhanced image (b), iodine in the small intestine is well removed. Iodine removal from the stomach is incomplete (dotted circle), suggesting that the iodine concentration was very high. During the virtual non-contrast reconstruction process, the volume of the cal- cification on the aortic wall was reduced (arrows) is commonly observed [31]. In addition, tiny- and not highly the bone marrow; these images have a high correlation with attenuated calcific areas may be lost during the VNC recon - fat-suppressed T2-weighted images [33, 35]. The diagnosis struction process [32] (Fig. 17). of early bone fractures on BME images requires less time than does magnetic resonance imaging during which patients Edema images must be still for a prolonged time. For the diagnosis and management of acute ischemic Edema images generated from dual-energy CT scans are stroke, the detection of edema in the gray matter is essen- useful for the detection of early bone fractures [33–35] and tial; edema maps generated from dual-energy CT scans were acute ischemic stroke [36, 37]. reported to be useful [36, 37]. “X-map”, an application to Under the presumption that the human body contains identify acute ischemic lesions on non-contrast dual-energy water and calcium, in patients with early bone fractures, CT scans [37], creates a virtual gray-matter- and water-con- edema images can help to identify bone marrow edema tent map using three-material decomposition. Lesions on the (BME) (Fig. 18). By reducing the calcium signal from bone, X-map clearly reflect the water content of cerebral edema water density images reflective of BME can be created. induced by acute ischemic stroke. There is a good correla- Lesions on BME images clearly reflect the water content in tion between findings on X-maps and on diffusion-weighted Fig. 18 A 13-year-old man with a distal femur fracture. It is difficult to detect bone marrow edema on the virtual monochromatic 70 keV image (a). On the edema image (b), bone marrow edema (arrow) is visualized in the same area as on the short TI inversion recovery image (c) 1 3 Japanese Journal of Radiology (2022) 40:547–559 557 Fig. 19 A 64-year-old woman with tuberous sclerosis, and focal hepatic steatosis and angiomyolipoma in the right lobe. A virtual monochromatic image obtained at 70 keV (a) and a color image of the fat map (b) are shown. The liver fat volume was 96.9% in the angiomyolipoma, 20.6% in the right-, and 7.8% in the left lobe of the liver images [37]. This method would be useful for the early number of a compound or mixture of materials. The electron development of treatment strategies in patients with acute density, on the other hand, represents the probability of an ischemic stroke. electron being present at a specic fi location. Highly accurate electron densities and effective atomic numbers have been Liver fat volume fraction and liver fibrosis calculated by raw data-based dual-energy analysis [13, 44], estimation but their clinical applicability requires further investigations. Because it is a promising method for obtaining electron Multi-material decomposition algorithms facilitate the density maps, dual-energy CT-based electron density imag- acquisition of the liver fat volume fraction (FVF) on dual- ing has attracted the interest of radiation oncologists. Dur- energy CT scans [38, 39]. It is presented as a volume % ing the planning of radiotherapy, electron density maps are on fat maps and calculated directly from non-contrast dual- generated from single-energy CT scans to determine the energy CT scans (Fig. 19). Fat maps from contrast-enhanced dose distribution in the target tissues [45]. However, the CT CT images are obtained after the creation of VNC images. number and the electron density of tissues are not accurately According to Hyodo et  al. [38], the liver FVF on non- correlated because the CT number depends on not only the enhanced- and dynamic contrast-enhanced dual-energy CT electron density but also the effective atomic number. Elec- images is comparable to the FVF determined by using MR tron-density maps obtained from dual-energy CT scans were spectroscopy. This method can be expected to yield accurate reported to be more accurate than the maps obtained with and reproducible findings for the diagnosis of hepatic stea- conventional radiotherapy planning methods [46, 47]. toses such as non-alcoholic- and alcoholic fatty liver disease. Validation of this method is required before its routine use in the clinical setting [40, 41]. Conclusions Estimating the degree of liver fibrosis has been attempted using dual-energy CT data [42, 43]. Extracellular volume This review presented the basics of dual-energy CT scanning fraction calculated from iodine density images is reported to and its usefulness in daily clinical practice. This technique be useful in estimating the degree of liver fibrosis [42]. Also, makes it possible to identify the characteristics of materi- CT texture analyses, such as gray-level intensity, skewness, als that cannot be evaluated on conventional single-energy kurtosis, and entropy at different energy levels are useful for CT images. We think that familiarity with a wide variety of the diagnosis of clinically significant hepatic fibrosis [43]. dual-energy CT applications and with their limitations facili- These parameters could be a promising biomarker of liver tates the accurate interpretation of CT findings and helps to fibrosis; however, further research is needed for use in clini- improve patient care in routine clinical practice. cal examinations. Declarations Eec ff tive atomic number and electron Conflict of interest K.A. is currently receiving a research grant from density analysis Canon Medical Systems Corp. For the remaining authors none were declared. Effective atomic number- and electron-density analyses are based on raw data-based dual-energy analysis. The effective Open Access This article is licensed under a Creative Commons atomic number (effective Z ) represents the average atomic Attribution 4.0 International License, which permits use, sharing, 1 3 558 Japanese Journal of Radiology (2022) 40:547–559 adaptation, distribution and reproduction in any medium or format, 16. Parakh A, Lennartz S, An C, Rajiah P, Yeh BM, Simeone FJ, as long as you give appropriate credit to the original author(s) and the et al. Dual-energy CT images: pearls and pitfalls. Radiographics. source, provide a link to the Creative Commons licence, and indicate 2021;41(1):98–119. if changes were made. The images or other third party material in this 17. Barrett JF, Keat N. 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Journal

Japanese Journal of Radiology – Springer Journals

Published: Jun 1, 2022

Keywords: Dual-energy CT; Computed tomography; Material decomposition; Detectability

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