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. Author manuscript; available in PMC: 2022 Mar 12.
Published in final edited form as: Med Phys. 2022 Jan 27;49(3):1458–1467. doi: 10.1002/mp.15448

Simultaneous dual-contrast imaging using energy-integrating detector multi-energy CT: An in vivo feasibility study

Zhongxing Zhou 1, Liqiang Ren 1, Kishore Rajendran 1, Felix E Diehn 1, Joel G Fletcher 1, Cynthia H McCollough 1, Lifeng Yu 1
PMCID: PMC8917049  NIHMSID: NIHMS1779444  PMID: 35018658

Abstract

Purpose:

To demonstrate the feasibility of simultaneous dual-contrast imaging in a large animal using a newly developed dual-source energy-integrating detector (EID)-based multi-energy computed tomography (MECT) system.

Methods:

Two imaging tasks that may have potential clinical applications were investigated: head/neck (HN) CT angiography (CTA)/CT venography (CTV) with iodine and gadolinium, and small bowel imaging with iodine and bismuth in domestic swine. Dual-source X-ray beam configurations of 70 kV + Au120/Sn120 kV and 70 kV + Au140/Sn140 kV were used for the HN-CTA/CTV and small bowel imaging studies, respectively. A test bolus scan was performed for each study. The regions of interest (ROIs) in the carotid artery and jugular vein for HN-CTA/CTV imaging and abdominal aorta for small bowel imaging were used to determine the time-attenuation curves, based on which the timing for contrast injection and the CT scan was determined. In the HN-CTA/CTV study, an MECT scan was performed at the time point corresponding to the optimal arterial enhancement by iodine and the optimal venous enhancement by gadolinium. In the small bowel imaging study, an MECT scan was performed at the optimal time point to simultaneously capture the mesenteric arterial enhancement of iodine and the enteric enhancement of bismuth. Image-based material decomposition was performed to decompose different materials for each study. To quantitatively characterize contrast material separation and misclassification, two ROIs on left common carotid artery and left internal jugular vein in HN-CTA/CTV imaging and three ROIs on superior mesenteric artery, ileal lumen, and collapsed ileum (ileal wall) in small bowel imaging were placed to measure the mean concentration values and the standard deviations.

Results:

In the HN-CTA/CTV study, common carotid arteries containing iodine and internal/external jugular veins containing gadolinium were clearly delineated from each other. Fine vessels such as cephalic veins and branches of external jugular veins were noticeable but clear visualization was hindered by image noise in gadolinium-specific (CTV) images, as reviewed by a neuroradiologist. In the small bowel imaging study, the mesenteric arteries and collapsed bowel wall containing iodine and the small bowel loops containing bismuth were clearly distinctive from each other in the iodine- and bismuth-specific images after material decomposition, as reviewed by an abdominal radiologist. Quantitative analyses showed that the misclassifications between the two contrast materials were less than 1.7 and 0.1 mg/ml for CTA/CTV and small bowel imaging studies, respectively.

Conclusions:

Feasibility of simultaneous CTA/CTV imaging in head and neck with iodine and gadolinium and simultaneous imaging of arterial and enteric phases of small bowel with iodine and bismuth, using a dual-source EID-MECT system, was demonstrated in a swine study. Compared to iodine and gadolinium in CTA/CTV, better delineation and classification of iodine and bismuth in small bowel imaging were achieved mainly due to wider separation between the corresponding two K-edge energies.

Keywords: Computed tomography (CT), dual-energy CT, energy-integrating detector, material decomposition, multi-contrast imaging, multi-energy CT

1 |. INTRODUCTION

Simultaneous imaging of multiple contrast agents using multi-energy computed tomography (CT) (or spectral CT) has received noticeable attention in recent years.1–6 Many studies with the potential for future clinical applications have been performed, for example, multi-phase abdominal, renal, or cardiovascular CT by imaging iodine/gadolinium or iodine/tungsten,1–3 small bowel imaging with iodine/bismuth,2,4 and initial phantom studies for future CT imaging applications with iodine/gadolinium/bismuth or iodine/gadolinium/gold.5,6 A well-established implementation of multi-energy CT (MECT), namely dual-energy CT (DECT), acquires dual-energy data with two different X-ray spectra, allowing separation of up to three materials in a mixture when an additional physical constraint (e.g., volume or mass conservation) is incorporated.7–9 However, using DECT with energy-integrating detectors (EIDs), it is challenging to ensure stable and accurate material decomposition when the number of materials in a mixture is above two and one or more of the components have distinctive K-edges.10,11 For a contrast agent with a distinct K-edge in the relevant energy range, two basis materials (or two types of interactions, photoelectric and Compton) in DECT material decomposition cannot accurately represent the discontinuity in the linear attenuation of the contrast agent.10 To overcome this challenge, attempts have been made to implement MECT that can acquire more than two X-ray spectra simultaneously. Two directions have been explored: energy-resolved photon-counting detector CT (PCD-CT) and EID-based MECT (EID-MECT). The spectral performance in PCD-CT, however, may be severely degraded by non-ideal effects such as pulse pile-up, K-edge escape, and charge sharing.12,13 As a result, it remains to be seen if the spectral performance of PCD-CT has any advantages compared to EID-based DECT systems at optimized beam separation for typical dual-energy applications.14

In our previous work, we proposed a MECT system on a dual-source CT scanner using the split filter on one or both X-ray sources.15 Using the split filter, the X-ray photons emitted from the source are prefiltered by two different filter materials, and each filtered spectrum covers half of the detector rows along the longitudinal direction. With this design, three or four unique X-ray spectra can be acquired nearly simultaneously. This technique was recently implemented on a Siemens dual-source CT scanner (SOMATOM Definition Flash, Siemens Healthineers GmbH) by mounting a z-axis split-filter on one of the two tubes to enable triple-beam acquisition.16 Phantom studies were performed to evaluate the spectral performance and determine the optimal triple-beam configurations.17

In this work, we performed animal studies to evaluate the feasibility of two potential clinical applications of multi-contrast imaging using this newly developed MECT system: (1) simultaneous CT angiography (CTA)/CT venography (CTV) imaging in head and neck using iodine and gadolinium and (2) simultaneous imaging of arterial and enteric phases of small bowel using iodine and bismuth.

2 |. MATERIALS AND METHODS

2.1 |. EID-MECT system

The EID-MECT system with triple-beam configuration was implemented on a dual-source CT scanner platform (SOMATOM Definition Flash, Siemens Healthineers) by mounting a z-axis split filter (0.05 mm Au, 0.6 mm Sn) on the A-system (Tube A + Detector A) enabling triple-beam acquisition.16 To acquire data from each voxel element with all X-ray beam measurements, the helical pitch values are required to be less than 0.5. Tube A is operated at 120 or 140 kV, and Tube B is operated at 70 or 80 kV, resulting in four possible triple-beam configurations: 70 kV + Au120/Sn120 kV, 70 kV + Au140/Sn140 kV, 80 kV + Au120/Sn120 kV, and 80 kV + Au140/Sn140 kV. In a previous phantom study, the optimal triple-beam configuration was determined as 70 kV + Au120/Sn120 kV and 70 kV + Au140/Sn140 kV for iodine/gadolinium/water and iodine/bismuth/water imaging tasks, respectively. More details regarding the practical implementation and technical parameters can be found in the previous study.16

2.2 |. Animal preparation

The animal study was conducted in accordance with the Guide for Care and Use of Laboratory Animals issued by the National Research Council and with approval from Mayo Foundation Institutional Animal Care and Use Committee. Two 3-month-old female domestic pigs (~35 kg) were used in this study, one for head/neck (HN) CT CTA/CTV imaging with iodine and gadolinium, and the other for small bowel imaging with iodine and bismuth. Both pigs were managed in the same way in terms of anesthesia, sheath placement, and physiological monitoring. Anesthesia was induced using Xylazine (2 mg/kg) and Telazol (5 mg/kg), and maintained using isoflurane (1-3%) until the end of the scan session. Physiological parameters including respiration, anesthesia, heart rate, blood pressure, and body temperature were closely monitored. Two access sheaths were placed on the right hind leg of each pig, one of which was in the femoral artery for blood pressure readings, the other in the femoral vein for intravascular contrast injection. Both pigs were placed supine and feet first on the scanner table. Breath hold was achieved right before the start of each scan by suspending the ventilation. Non-contrast CT scans were acquired first to determine appropriate radiation dose level and scan range.

2.3 |. CTA/CTV imaging task

A series of test bolus scans were performed to determine the time-attenuation curves of intra-arterial and intravenous contrast enhancement in the swine head/neck region (scan technique: 80 kV and 200 mAs, CTDIvol/scan = 3.59 mGy). At a constant injection rate of 5 ml/s, 40 ml iohexol (Omnipaque 350, GE Healthcare, Princeton, NJ) and 20 ml saline flush were sequentially administered into the right femoral vein. Following the initiation of contrast injection, 50 single-energy CT (SECT) scans were performed at the same position enclosing both common carotid arteries and internal/external jugular veins at a time interval of 2 s. After reconstructions, a representative slice was identified, and two regions of interest (ROIs) were drawn: one on the right common carotid artery (Figure 1a) and the other on left internal jugular vein (Figure 1b) to measure the average CT number. All reconstructed images from these 50 SECT scans were processed by an analysis tool (DynEva, Siemens Healthineers). The images were carefully reviewed and the ROIs in the carotid artery and jugular vein were manually placed on the image with highest vascular enhancements. The same ROIs were automatically propagated to the rest images to plot the enhancement curves without image registration. As the scans were performed on the neck region, motions caused by breathing did not cause any issue for quantitative analysis. The ROI size was determined to occupy about 70% of the vessel diameter. The measurements were performed on all 50 scans to derive the time-dependent arterial and venous enhancement curves, as illustrated in Figure 1c. The time-enhancement curves were then used to design the single-scan, dual-contrast MECT scanning protocol for simultaneously acquiring two phases of vascular enhancement, with iodine and gadolinium corresponding to the arterial enhancement (CTA) and venous enhancement (CTV), respectively. The scanning protocol is illustrated in Figure 1d, where 80 ml gadobutrol (Gadavist, Bayer Healthcare, Whippany, NJ) followed by 40 ml saline flush, and 40 ml iohexol followed by 20 ml saline flush were sequentially injected with a 12-s time interval between initiations of the two contrast injections. The amounts of volume of gadobutrol and iohexol were determined based on previous phantom and animal studies to provide sufficient contrast enhancements. A MECT scan was performed 12 s after the initiation of the iodine contrast injection. This scanning time point corresponds to the optimal arterial enhancement by iodine contrast (injected 12 s ago) and the optimal venous enhancement by gadolinium contrast (injected 12 + 12 = 24 s ago). The triple-beam configuration, 70 kV + Au120/Sn120 kV, was used to achieve the best iodine and gadolinium separation and quantification.17 Data acquisition and image reconstruction parameters in the above MECT scan are summarized in Table 1.

FIGURE 1.

FIGURE 1

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CT images (window/level = 400/40) acquired at peak contrast enhancement in (a) common carotid artery and (b) internal jugular vein, respectively, during the test bolus scan; (c) Enhancement curves for arterial and venous phases, indicating peak enhancements at 14 and 26 s, respectively; (d) Dual-contrast (iodine and gadolinium) imaging protocol with one single multi-energy computed tomography scan to capture optimal enhancement of iodine at arterial phase (CTA) and gadolinium at venous phase (CTV) simultaneously

TABLE 1.

Data acquisition and image reconstruction parameters in multi-energy computed tomography scan

Imaging task HN-CTA/CTV imaging (I/Gd) Small bowel imaging (I/Bi)
Collimation 64 × 0.6 mm
Voltage (kV) 70kV+Au120/Sn120 kV 70kV+Au140/Sn140 kV
CTDIvola (mGy) 12
Pitch 0.4
Rotation time (s) 0.33
Scan/reconstruction FOV (mm) 500/215 500/275
Slice-thickness/increment (mm) 1.5/0.75 3.0/2.0
Reconstruction kernel Qr40f Qr36f
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a

CTDIvol, volume CT dose index measured with a 32-cm CTDI phantom.

2.4 |. Small bowel imaging task

A 600 ml homogeneous bismuth-saline solution (180 ml Pepto-Bismol + 420 ml normal saline) was orally administered to the pig through a gastric tube. With about 2.5 h delay after bismuth administration, a series of test bolus scans were performed to determine the timing of peak arterial enhancement in the abdomen. The test bolus scans consist of 15 SECT axial scans (scan technique: 120 kV and 100 mAs, CTDIvol/scan = 6.75 mGy) at an interval of 2 s after injection of 40 ml iohexol and 20 ml saline (5 ml/s). Figure 2 shows the enhancement curve that was determined at the abdominal aorta and a single-scan, dual-contrast MECT imaging protocol, with the timing of iodine injection determined from the enhancement curve.

FIGURE 2.

FIGURE 2

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(a) A CT image (window/level = 400/40) acquired at peak enhancement in abdominal aorta. (b) Enhancement curve for arterial enhancement determined by the average contrast enhancement measured with the circular ROI as shown in (a), indicating peak enhancement at 14 s. (c) Dual-contrast (iodine and bismuth) imaging protocol with one single multi-energy computed tomography scan to capture arterial enhancement of small bowel wall (iodine) and enteric enhancement of small bowel lumen (bismuth) simultaneously

With another delay of half hour (approximately 3 h after feeding the bismuth solution) for iodine washout, a MECT scan was performed 13 s after the initiation of the iodine injection via the right femoral vein (40 ml bolus of iohexol followed by 20 ml saline flush, flow rate of 5 ml/s). The MECT scan simultaneously captured the arterial enhancement in the aorta and small bowel mesenteric arteries (iodine) and luminal enteric opacification (bismuth), as demonstrated in Figure 2c. The data acquisition and image reconstruction parameters are summarized in Table 1.

2.5 |. Material decomposition and image analysis

A generic image-based material decomposition method was employed to delineate and quantify three basis materials.15 Iodine, gadolinium, and soft tissue were selected as basis materials in HN-CTA/CTV imaging, whereas iodine, bismuth, and soft tissue were selected in small bowel imaging. The coefficient and variance-covariance matrices were determined beforehand in a separate phantom scan.17

For the HN-CTA/CTV task, images were reviewed by a neuroradiologist (F.E.D.) with 12 years of experience. The same radiologist was asked to confirm the separation of arterial phase represented by iodine enhancement on iodine-specific image and venous phase by gadolinium enhancement on gadolinium-specific images. To quantitatively evaluate the separation and the misclassification between two contrast materials, two ROIs, one for iodinated opacification and the other for gadolinium opacification were drawn on right common carotid artery and left internal jugular vein, respectively. Note that a 3D noise reduction filter18 was applied to MECT images to suppress noise magnification during material decomposition of iodine and gadolinium. For the small bowel imaging task, images were reviewed by an abdominal radiologist (J.G.F.) with 21 years of experience. The same radiologist was asked to confirm the separation of mesenteric arteries containing iodine on iodine-specific images and small bowel lumen containing bismuth on bismuth-specific images. Three ROIs, two of them for iodinated opacification and the other one for bismuth opacification were drawn on superior mesenteric artery, collapsed ileum (ileal wall), and ileal lumen, respectively. For each ROI, mean CT number or concentration (± standard deviation) was measured on both MECT and material-specific images in both studies.

3 |. RESULTS

3.1 |. Dual-contrast HN-CTA/CTV imaging with iodine and gadolinium

Figure 3a–c shows axial MECT images of the swine neck reconstructed from the triple-beam acquisition: 70 kV,Au120 kV, and Sn120 kV, respectively. All grayscale images were displayed with routine soft-tissue window settings (window/level = 400/40 HU). The corresponding 3D volumetric rendering of both arteries and veins from the MECT images was displayed in Figure 3d. Before material decomposition, both contrast materials (iodine and gadolinium) were visible but indistinguishable. For instance, iodine-enhanced common carotid arteries (closed arrows) and gadolinium-enhanced internal/external jugular veins (open arrows) could not be differentiated from each other (see Figure 3a–d). After material decomposition, 3D volumetric rendering of iodine-specific (CTA) and gadolinium-specific (CTV) images were presented in Figures 3e and 3f, respectively. To provide a sufficient range for window/level adjustment in the display, the concentrations of gadolinium (Figure 3e) and iodine (Figure 3f) were scaled up 20 times after material decomposition. The color coded coronal maximum intensity projection (MIP) image (Figure 3g) showing both contrast materials were generated for better distinction between veins and arteries, with iodine labeled in red (arteries corresponding to Figure 3e, indicated by closed arrows) and gadolinium in green (veins corresponding to Figure 3f). As shown in Figure 3g, common carotid arteries containing iodine and internal/external jugular veins containing gadolinium could be clearly delineated from each other. Fine vessels such as cephalic veins and branches of external jugular veins could be visualized but clarity was negatively impacted by image noise in gadolinium-specific (CTV) images. The distinct iodine and gadolinium separation were confirmed by the radiologist on material-specific images. As per the radiologist, the simultaneous contrast agents did not take away any visibility of normal anatomy when he assessed this exam type. To quantitatively characterize contrast material separation and misclassification, two ROIs, one on the left common carotid artery (dotted red region, marked by #1) and the other on the left internal jugular vein (dotted green region, marked by #2) were drawn at the locations as indicated by Figure 3a to measure the mean values as well as the standard deviations from one single region of interest (Table 2), indicating misclassification of one contrast agent on the material-specific image containing the other contrast agent was less than 1.7 mg/ml.

FIGURE 3.

FIGURE 3

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Multi-energy computed tomography (MECT) images of the swine neck acquired at (a) 70 kV, (b) Au120 kV and (c) Sn120 kV after gadolinium and iodine injection (window/level: 400/40 HU); (d) 3D volumetric rendering of both arteries and veins from the MECT images; 3D rendering of (e) iodine-specific and (f) gadolinium-specific images after material decomposition, and (g) the color coded coronal maximum intensity projection (MIP) image with iodine labelled in red (arteries) and gadolinium in green (veins); the display window/level settings for (d–f) were optimized for best demonstration of main structures and fine details

TABLE 2.

Quantitative results measured on MECT images (unit: HU) and material-specific images (unit: mg/ml) in the head/neck CT angiography/CT venography imaging task

ROI MECT image: 70 kV (HU) MECT image: Au120 kV (HU) MECT image: Sn120 kV (HU) Iodine-specific image (mg/ml) Gadolinium-specific image (mg/ml)
#1 (common carotid artery) 574.4 ± 58.6 320.0 ± 20.1 243.1 ± 29.7 8.3 ± 0.8 1.7 ± 0.4
#2 (internal jugular vein) 434.1 ± 29.8 291.3 ± 24.2 240.9 ± 24.4 0.8 ± 0.7 9.6 ± 0.8
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3.2 |. Dual-contrast small bowel imaging with iodine and bismuth

Figure 4a–c shows the MECT images acquired at 70 kV, Au140 kV, and Sn140 kV from a single MECT scan, capturing both arterial enhancement of iodine in small bowel wall and the enteric enhancement of bismuth in small bowel lumen. Prior to material decomposition, both contrast materials (iodine and bismuth) were visible but not completely distinguishable. For example, the collapsed iodine-enhanced bowel wall (closed arrow) and the adjacent bismuth-enhanced small bowel loop (open arrow) were not clearly differentiable from each other (see Figure 4a–c). After three-material decomposition, however, notable distinction between these two structures was revealed in the iodine-specific (Figure 4d) and bismuth-specific (Figure 4e) images. Fused color image showing both contrast materials was then generated to provide a better representation of the distinction between two contrast materials, as displayed in Figure 4f. The distinct iodine and bismuth separation were also confirmed by the radiologist on material-specific images. As per the radiologist, the simultaneous contrast agents did not take away any visibility of normal anatomy when he assessed this exam type. To further quantitatively characterize contrast material separation and misclassification, three ROIs (superior mesenteric artery, ileal lumen, and collapsed ileum) were drawn on Figure 4a to measure the mean values as well as the standard deviations from one single ROI (Table 3), indicating misclassification of one contrast agent on the material-specific image containing the other contrast agent was less than 0.1 mg/ml.

FIGURE 4.

FIGURE 4

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Multi-energy computed tomography images of the swine small bowel acquired at (a) 70 kV (b) Au140 kV and (c) Sn140 kV after oral administration of bismuth and intravenous injection of iodine; (d) iodine-specific, (e) bismuth-specific, and (e) fused color images after material decomposition. Note that iodine-specific images (d) show iodine contrast within the aorta, renal cortex and collecting systems, and collapsed bowel wall (closed arrow). Iodine enhancement in a collapsed small bowel wall is seen despite no bismuth within the lumen (closed arrow). The collapsed iodine-enhanced bowel wall (closed arrow) and the adjacent bismuth-enhanced small bowel loop (open arrow) were not completely differentiable in (a–c) but clearly separated from each other in (d–f). Three ROIs drawn for quantitative analysis on: (1) superior mesenteric artery (dotted purple region, marked by #1), (2) ileal lumen (dotted green region, marked by #2), and (3) collapsed ileum (ileal wall) (dotted red region, marked by #3)

TABLE 3.

Quantitative results measured on MECT images (unit: HU) and material-specific images (unit: mg/ml) in small bowel imaging task

ROI MECT image: 70 kV (HU) MECT image: Au140 kV (HU) MECT image: Sn140 kV (HU) Iodine-specific image (mg/ml) Bismuth-specific image (mg/ml)
#1: Superior mesenteric artery 1255.8 ± 27.4 537.3 ± 13.3 392.8 ± 13.0 27.4 ± 1.0 0.5 ± 0.9
#2: Ileal lumen 637.8 ± 37.6 477.0 ± 33.4 497.9.1 ± 34.3 0.1 ± 0.7 22.6 ± 1.9
#3: Collapsed ileum (ileal wall) 529.1 ± 20.0 202.2 ± 9.3 155.2 ± 14.0 9.5 ± 0.7 0.0 ± 0.8
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4 |. DISCUSSIONS

We previously implemented an EID-based triple-beam MECT technique to simultaneously image and differentiate multiple contrasts in a single scan.16 With a phantom study, the optimal triple-beam configuration was determined to be task-dependent with 70 kV + Au120/Sn120 kV, 70 kV + Au140/Sn140 kV, and 70 kV + Au120/Sn120 kV for iodine/gadolinium/water, iodine/bismuth/water, and iodine/gadolinium/bismuth/water material decomposition tasks, respectively, which provided the technical evidence of the selections of the optimal triple-beam configurations in the current study.16 This study was conducted to evaluate the feasibility using the newly developed EID-based MECT system for two potential clinical applications of dual-contrast imaging: (1) simultaneous CTA/CTV imaging of head and neck using iodine and gadolinium, and (2) small bowel imaging with iodine highlighting the bowel wall and bismuth highlighting the bowel lumen. Specifically, in the CTA/CTV study, an MECT scan could achieve spatially registered images of arteries and veins from a single CT scan, providing a more complete description of the vascular system. In the small bowel study, the arterial enhancement of iodine in the mesenteric arteries and collapsed bowel wall and the enteric enhancement of luminal bismuth could be successfully delineated in material-specific images. The dual-contrast MECT imaging requires only one scan for both imaging tasks, making it possible to perfectly align the anatomical structures that would not be achievable in conventional multi-phase examinations with two or more SECT scans.

To date, dual- and multi-contrast MECT imaging has shown encouraging results in phantom and animal studies for multiple clinical applications.1–6,19–25 For example, iodine-filled lumen and gadolinium-enhanced polyp were successfully differentiated in a colon phantom study.19 For the application of biphasic liver imaging, simultaneous imaging of iodine-based and gadolinium-based contrast agents was evaluated in computer simulation, experimental phantom, and exploratory swine studies.3,17,20,21 A proof-of-concept study with a canine model of chronic myocardial infarction was performed to demonstrate the simultaneous visualization of iodine-enhanced first-pass images and delayed gadolinium-enhanced images.22 In a study using rats, iodine-enhanced peritoneal compartments and gadolinium-enhanced vasculatures could be simultaneously imaged.23 Other combinations of the two or more contrast agents for various imaging tasks have been also actively investigated such as using iodine and bismuth for small bowel imaging24 and iodine, gadolinium, and bismuth in phantom and animal studies.2,6 The feasibility of simultaneous imaging of two contrast materials (iodine and tungsten) was demonstrated for abdominal CTA/CTV in a rabbit using a clinical DECT scanner.25 However, there are two major differences between our study and the iodine/tungsten study.24 First, compared to the tungsten cluster contrast medium, we used gadolinium-based material as the second contrast medium, which is widely used in magnetic resonance imaging and some special applications in CT imaging,26 while the biological properties of tungsten as a potential CT contrast agent are still not well understood.27 The larger difference in K-edge energies between iodine (33.2 keV) and tungsten (69.5 keV) than iodine and gadolinium (50.2 keV) may lead to better noise properties in material decomposition of iodine and tungsten. Second, the material decomposition in the iodine/tungsten study was performed directly on a commercial software with two-material decomposition where the tungsten and water were assigned into a single basis material map, which led to only a qualitative analysis in that study. In contrast, three-material decomposition was used in our study with iodine, gadolinium, and soft tissue as basis materials. As a result, more accurate quantification of each contrast material was achieved, which was enabled by the novel triple-beam data acquisition in the proposed EID-MECT system.10,11,25

The total time required for CTA/CTV imaging task between dual-contrast method and single-contrast method is expected to be comparable if we adopt the bolus tracking technique28 instead of the test bolus technique. Comparison between protocols has been made in our previous work of dual-contrast biphasic liver imaging with iodine and gadolinium,21 where the total time required for both single-contrast and dual-contrast method is approximately 29.5 s. Regarding the small bowel imaging, the imaging protocol may be further optimized by determining the best amount of bismuth contrast material and delay time after its administration.

Small bowel imaging with iodine and bismuth in swine was recently reported by our group using a whole body PCD-CT system.29 Like the current study, the PCD-CT study also demonstrated a clear distinction between small bowel loops containing bismuth and the enhancing bowel wall containing iodine in the material specific maps. Using PCD-CT, optimal tube voltage and threshold settings, 140 kV and [25, 50, 75, 90] keV, were determined to utilize the K-edge of bismuth (90.5 keV) while providing a balanced spectral separation. The EID-MECT system, however, was shown to be more dose efficient for this particular imaging task at equal total radiation dose and optimal beam spectra selection, as demonstrated in a previous phantom study.16

Despite the many advantages over a PCD-CT system, such as minimal hardware changes, negligible implementation cost, and flexible dose distribution among different beams,15 the implemented EID-based MECT system is not without limitations. One limitation is the helical pitch, which must be less than 0.5 to make sure the split beam acquisition provides sufficient data for accurate image reconstruction. This is also the case for commercial implantation of the twin-beam geometry on single-source scanners. The second limitation is the cross-scattering between the two sources and between the two split-filtered X-ray beams. The negative effect of cross-scattering may become more obvious in relatively bigger patients. Another limitation is that the split filter significantly reduces the radiation output capacity of the system. The tube current – exposure time product (mAs) required to provide sufficient radiation output is higher than in systems without the filter, so there may be more stringent patient size limitations.

As shown in Tables 2 and 3, the misclassification of contrast agents for head/neck CTA/CTV imaging using iodine and gadolinium is higher than that of small bowel imaging using iodine and bismuth. This is expected since the noise properties in material decomposition of the two imaging tasks are quite different. The K-edge energies of iodine, gadolinium and bismuth are 33.2, 50.2, and 90.5 keV, respectively. The larger difference in K-edge energies between iodine and bismuth has led to a better differentiation of materials and noise properties in material decomposition.8 Here we should note that although comparing independent measurements of each contrast material would make the results more convincing, assessment of contrast material concentration accuracy needs to be performed in phantoms because it may not be reliable or reproducible in animal imaging due to the inherent variations of the kinetic dynamics of blood circulation among different injections and scans. In fact, we have done quantitative comparisons in a previously published study of phantom experiments, in which the quantification accuracy of iodine, gadolinium, and bismuth was evaluated and compared to the nominal concentration values.16 For dual-contrast HN-CTA/CTV imaging with iodine and gadolinium, the calcium is not one of the basis materials (iodine, gadolinium, and soft tissue) and is assigned across three basis matier maps after material decomposition. The calcification would not introduce additional source of error and can be differentiated from iodine/gadolinium as it would show up in both contrast material maps. Instead, iodine and gadolinium would be only displayed in its corresponding material maps.

The recommended dose of gadobutrol for adult is 0.1 ml/kg body weight for MRI. In our study, 2.3 ml/kg body weight gadobutrol was injected for head/neck CTA/CTV imaging of a swine (~35 kg). The relatively high dose of gadobutrol is one potential limitation of our study, which may become a concern due to contrast toxicity. But to achieve equivalent X-ray attenuation doses to iodine-based contrast agents, higher gadolinium concentrations are necessary.2,19,30,31 Because the primary aim of this study is to demonstrate the feasibility of separating iodine and gadolinium in vivo, we did not examine the lowest possible contrast dose, but employed a high dose of gadobutrol for dual-contrast HN-CTA/CTV imaging. Although researchers have identified that the risk of gadolinium release can be reduced by using macrocyclic agents, the safety of which is still under investigation.32 There is a potential risk of gadolinium for patients with nephrogenic systemic fibrosis (NSF). Although a causative relationship between gadolinium and NSF has not been firmly established, research have shown that gadolinium plays a role in the development of NSF in some patients with long term or high exposures.33,34 Gadolinium has not been proven to be a viable CT contrast yet, and the potential adverse effects of simultaneous administration of iodine and gadolinium at CT-specific contrast doses is currently unknown. A thorough investigation is needed to determine whether the benefits of such a dual-contrast approach outweigh the risks for head/neck CTA/CTV imaging in patients.

5 |. CONCLUSION

In an animal study, simultaneous CTA/CTV imaging of head and neck using iodine and gadolinium and simultaneous imaging of arterial and enteric phases of small bowel using iodine and bismuth were demonstrated to be feasible on a newly developed EID-based MECT system.

ACKNOWLEDGMENTS

Research reported in this publication was supported by the National Institutes of Health under award numbers R21 EB024071, R01 EB016966 and C06 RR018898. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Dr. Zhongxing Zhou was supported by the Mayo Radiology Research Fellowship Program. The research CT system used in this work was provided by Siemens Healthcare GmbH; it is not commercially available. The authors would like to thank Drs. Thomas Allmendinger, Ahmed Halaweish, Bernhard Schmidt, and Thomas Flohr from Siemens Healthcare GmbH, who provided technical support with regards to the installation and calibration of the split filter. The authors thank Jill Anderson and Amy Benike for their support in the animal study. The authors also acknowledge Mayo Clinic’s X-ray Imaging Core for supplies and services for this study.

Funding information

National Institutes of Health, Grant/Award Numbers: R21 EB024071, R01 EB016966, C06 RR018898

CONFLICT OF INTEREST

McCollough and Fletcher receive industry grant support from Siemens. No other potential conflicts of interest were declared.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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