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Evaluation of gold K-edge imaging using spectral computed tomography with a photon-counting detector: A Monte Carlo simulation study
Optik 140 (2017) 253–260
Contents lists available at ScienceDirect
Optik journal homepage: www.elsevier.de/ijleo
Original research article
Evaluation of gold K-edge imaging using spectral computed tomography with a photon-counting detector: A Monte Carlo simulation study Sooncheol Kang a , Jisoo Eom a , Burnyoung Kim b , Seungwan Lee a,b,∗ a b
Department of Medical Science, Konyang University, 158 Gwanjeodong-ro, Daejeon 35365, South Korea Department of Radiology Science, College of Medical Science, Konyang University, 158 Gwanjeodong-ro, Daejeon 35365, South Korea
a r t i c l e
i n f o
Article history: Received 25 January 2017 Accepted 16 April 2017 Keywords: Photon-counting detector Gold K-edge imaging Monte Carlo simulation
a b s t r a c t Energy-integrating detectors (EIDs) are hard to reflect information of multi-energy X-rays due to its detection mechanism. On the other hand, photon-counting detectors (PCDs) are able to selectively acquire spectral information using energy thresholds. This characteristic of the PCDs allows the K-edge imaging technique, which is able to increase the contrast of high atomic number materials, such as iodine, gadolinium, and gold. Especially, the characteristics of gold can provide benefits for clinical applications because gold has minimal toxicity and a high K-edge absorption energy of 80.7 keV. In this study, a spectral CT system using a cadmium zinc telluride (CZT)-based PCD was designed by a Monte Carlo simulation tool. Phantoms were simulated to obtain gold K-edge and conventional CT images, and different reconstruction filters were used for investigating the noise property. The obtained images were evaluated by measuring contrast-to-noise ratios (CNRs). The results of this study showed that the CNRs of gold K-edge CT images were higher than those of conventional CT images, and a noise suppression filter improved the CNRs of gold K-edge CT images. It was concluded that gold has a high performance as a contrast agent, and the gold K-edge CT imaging enable the excellent material decomposition. © 2017 Elsevier GmbH. All rights reserved.
1. Introduction In general, X-ray sources used for diagnosis generate polychromatic energy beams, and these X-ray photons interact with matters in accordance with their energy levels. This physical phenomenon indicates that transmitted X-ray photons have different information of the matters. However, energy-integrating detectors (EIDs) used in conventional computed tomography (CT) systems are hard to obtain spectral information of the transmitted X-ray photons due to its detection mechanism [1]. On the other hand, photon-counting detectors (PCDs) are able to measure spectral information using the multiple energy thresholds, which are operated by application specific integrated circuits (ASICs) [2,3]. The PCDs can also reduce the image noise caused by detector leakage current and arising in low energy levels (<20 keV) [4]. Especially, the PCDs based on cadmium telluride (CdTe) and cadmium zinc telluride (CZT) with the thicknesses of 2–3 mm have high detection
∗ Corresponding author at: Departments of Medical Science and Radiological Science, Konyang University, 158 Gwanjeodong-ro, Daejeon 35365, South Korea. E-mail address: [email protected] (S. Lee). http://dx.doi.org/10.1016/j.ijleo.2017.04.062 0030-4026/© 2017 Elsevier GmbH. All rights reserved.
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Fig. 1. Linear attenuation coefficient curves as a function of the incident X-ray energy for gold, iodine, skull, brain and PMMA.
efficiency for X-ray photons in an 1–140 keV range in comparison with EIDs [5]. These characteristics of PCDs enable to implement novel X-ray imaging techniques, improve image quality and overcome the limitations of the EIDs. Recently, several studies showed the availability of PCDs and proposed the spectral X-ray imaging techniques, such as energy-weighting and multi-energy imaging, for computed tomography and mammography [6,7]. One of the spectral X-ray imaging techniques is K-edge imaging. The K-edge imaging technique is based on the attenuation property of a material, which is a sudden increase of attenuation coefficient at a specific energy level, called K-edge discontinuity, and this property is observed in high atomic number materials, such as contrast agents [8] (Fig. 1). The K-edge imaging technique can improve the contrast of a target material by obtaining the energy-selective information above the K-edge absorption energy of the target material, and this technique is able to implement by using the energy thresholds of PCDs [2,8]. Although iodine contrast agents are widely used for CT angiography and provide high contrast resolution, they still have the toxicity issues causing the malfunction of organs [9]. Also the K-edge images using the iodine contrast agents are limited to discriminate target materials from other tissues in thick objects, such as human patients due to the relatively low K-edge absorption energy of iodine, high tube voltages in human applications and beam hardening effect [8]. Unlike other contrast agents, gold has the K-edge absorption energy of 80.7 keV due to its high atomic number and has the excellent capability of material decomposition [10,11]. Also, gold nanoparticles (GNPs) improve contrast for a long time after delivery to target organs because they have a long circulation time. And the GNPs have minimal toxicity [12]. Moreover, the coated GNPs, such as polymer, PEG and gadolinium-coated GNPs, have been used for vascular imaging and tumor detection [13]. Therefore, it needs to improve the quality of CT images with the gold contrast agents and investigate the characteristics of the gold K-edge CT imaging. In this study, a spectral CT system using a CZT-based PCD was simulated to implement the gold K-edge CT imaging. We compared the gold K-edge CT images with conventional CT images in terms of contrast-to-noise ratio (CNR) and evaluated the characteristics of gold K-edge CT images. 2. Materials and methods 2.1. Simulation setup and spectral CT system In this study, Geant4 Application for Tomographic Emission (GATE) version 6.0 was used for Monte Carlo simulations. The interactions between X-ray photons and materials were simulated for considering electromagnetic processes, and the CT scanner module was used to obtain X-ray images [14]. The detector was designed in accordance with eValuator-3500 (eV Product, USA), which is based on CZT substances and has a size of 128 × 0.5 mm2 , a thickness of 3 mm and a pixel size of 0.5 × 0.5 mm2 . The PCDs have a limitation of pulse pile-up, which causes spectral distortion, under the high flux of photons (>1 × 106 /mm2 ·s) [3,5]. In this study, we assume that there is no spectral distortion induced by the pulse pile-up due to determining the feasibility of the gold K-edge CT imaging and evaluating its characteristics. For comparing gold K-edge CT images with conventional CT images, a silicon (Si) detector was also simulated with the specifications of the PCD. The focus-to-center of rotation distance and the focus-to-detector distance were 550 and 1000 mm, respectively. In order to identify the characteristics of the gold K-edge CT imaging, a cylindrical phantom was designed with a diameter of 80 mm and a height of 15 mm. The phantom consisted of polymethyl methacrylate (PMMA) and had four 20 mm diameter holes filled with the different concentrations of gold materials (Fig. 2). The X-ray spectrum for image acquisition was simulated at a tube voltage of 120 kVp with a tube current of 3.75 mA and a 2 mm aluminum filter by using the SRS-78 program (Fig. 3) [15]. Also, a head phantom was designed to simulate cerebral angiography. The phantom had a cylindrical shape with a diameter of 50 mm, which is similar to the long axis of head of a rat, and a height of 15 mm. The phantom was composed of
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255
Fig. 2. Schematic illustrations of the PMMA phantom at (a) side view and (b) top view.
Fig. 3. Simulated input X-ray spectrum used for obtaining the CT images of the PMMA phantom. (a) represents the energy window for the gold K-edge CT imaging (81–120 keV).
brain tissue (density = 1.04 g/cm3 ), which is surrounded by skull (density = 1.61 g/cm3 ), and had eight 6 mm diameter holes filled with the different concentrations of gold materials (Fig. 4). For obtaining the images of the head phantom, the X-ray spectrum was simulated at a tube voltage of 120 kVp with a tube current of 1.5 mA and a 2 mm aluminum filter (Fig. 5). 2.2. Data acquisition, image reconstruction and analysis The PCDs can acquire energy selective images using the energy windows defined by energy thresholds. A previous study showed that the K-edge imaging is feasible with the energy window located above the K-edge absorption energy of a target material [16]. In this study, an energy window of 81–120 keV was used to obtain gold K-edge CT images because the K-edge absorption energy of gold is 80.7 keV. Conventional CT images were obtained by using the full X-ray energy spectrum. To acquire tomographic images, 180 projections of the phantoms were obtained during a full 360 ◦ rotation, and the image reconstruction was performed by using a model-based filtered back-projection algorithm with the pixel-driven method. The pixel-driven method operates by connecting rays from an X-ray source to the centers of image pixels. The line integrals can be calculated by using the interpolation, which is based on the distances between the projected locations of rays on a detector plane and the centers of detector pixels [17]. The quality of K-edge images depends on noise property because the K-edge images are generated by the small number of photons, which is included in a specific energy window and increases the statistical noise in X-ray images. Thus, the hamming filter was used to improve the noise property of K-edge images, and the Ram-Lak filter was also used for comparison. The reconstructed images of the PMMA and head phantoms had arrays of 160 × 160 and 100 × 100 pixels, respectively.
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Fig. 4. Schematic illustrations of the head phantom at (a) side view and (b) top view.
Fig. 5. Simulated input X-ray spectrum used for obtaining the CT images of the head phantom. (a) represents the energy window for the gold K-edge CT imaging (81–120 keV).
The CNR was measured in order to evaluate and compare the image quality of gold K-edge and conventional CT images. For the PMMA phantom, the CNR was calculated between PMMA and gold materials with the regions of interest (ROIs) of 10 × 10 pixels. We also calculated the CNR between brain and gold materials with the ROIs of 5 × 5 pixels for the head phantom. The CNR is defined by the following equation: CNR =
|t − b | (t )2 + (b )2
,
(1)
where t and b are the mean values of target and background materials. t and b are the standard deviations of target and background materials. 3. Results Fig. 6 shows the conventional and gold K-edge CT images of the PMMA phantom. The contrast of gold materials increased in the K-edge CT image compared with the conventional CT image. The CNR increased as a function of the concentration of gold, and the gold K-edge CT imaging improved the CNR in comparison to the conventional CT imaging (Fig. 7). The CNRs of the gold K-edge CT images were approximately 1.74, 1.3 and 1.31 times higher than those of the conventional CT images for 100, 150 and 200 mg/ml gold materials, respectively. But, there was little difference in CNR between the conventional and
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Fig. 6. (a) Conventional CT image using a Si detector and (b) gold K-edge CT image using a CZT-based PCD with an energy window of 81–120 keV. All images are displayed in a same gray scale.
Fig. 7. CNRs of gold materials of the PMMA phantom for the conventional and gold K - edge CT images.
Table 1 CNR improvements between the conventional and gold K-edge CT images for the PMMA phantom. Gold concentration
CNR improvement
50 mg/ml
100 mg/ml
150 mg/ml
200 mg/ml
1.00
1.74
1.30
1.31
gold K-edge CT images for the 50 mg/ml gold material. The CNR improvements for the PMMA phantom are summarized in Table 1. To evaluate the noise property of the gold K-edge CT imaging, the projections of the head phantom were reconstructed with the Ram-Lak and hamming filters (Fig. 8). Similar to the results of the PMMA phantom, the gold K-edge CT imaging improved the contrast of gold materials for the head phantom. The reconstructed values of brain tissue and skull in the gold K-edge CT images were significantly lower than those in the conventional CT images. We could observe that the image noise was suppressed by the hamming filter. Fig. 9 shows the CNRs between brain tissue and gold materials for the conventional and gold K-edge CT imaging with the different reconstruction filters. For the concentrations of 50–200 mg/ml, the CNRs of the gold K-edge CT images were approximately 1.03–1.42 and 1.07–1.54 times higher than those of the conventional CT images for the Ram-Lak and hamming filters, respectively. However, in the gold K-edge CT images, the CNRs of the 25 mg/ml gold material decreased by factors of 0.51–0.54 compared to the conventional CT images. The CNR improvements for the head phantom are summarized in Table 2.
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Fig. 8. Conventional CT images reconstructed with the (a) Ram-Lak and (c) hamming filters. Gold K-edge CT images reconstructed with the (b) Ram-Lak and (d) hamming filters. All images are displayed in a same gray scale.
Fig. 9. CNRs between brain tissue and gold materials for the head phantom reconstructed with the Ram-Lak and hamming filters. The white and gray bars represent the results for the Ram-Lak and hamming filters, respectively.
4. Discussion The PCDs have an ability to distinguish the energy of X-ray photons and can reflect attenuation information of materials for each X-ray photons. These characteristics enable the acquisition of the energy-selective X-ray images, which are defined by energy windows.
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Table 2 CNR improvements between the conventional and gold K-edge CT images for the head phantom. Filters
Ram-lak filter Hamming filter
Gold concentration 25 mg/ml
50 mg/ml
75 mg/ml
100 mg/ml
125 mg/ml
150 mg/ml
175 mg/ml
200 mg/ml
0.54 0.51
1.42 1.54
1.03 1.07
1.16 1.22
1.23 1.35
1.24 1.25
1.29 1.34
1.30 1.32
In this study, we simulated a spectral CT system with a CZT-based PCD using a Monte Carlo simulation tool in order to implementing the gold K-edge CT imaging. The gold K-edge CT images were obtained with the different concentrations of gold. The CNRs between gold and background materials were measured for evaluating and comparing the image quality with the conventional CT images. The results showed that the CNRs increased with an increase of the concentration of gold, and the K-edge CT imaging technique improved the CNRs compared to the conventional CT imaging technique. These results demonstrated that the gold-based contrast agents have a potential to improve the image quality of CT images and the diagnostic accuracy. The CNR improvement was due to the limited energy window located above the K-edge absorption energy of gold. The limited energy window reflected a sudden increase of the attenuation coefficients of gold in CT images. However, the limited energy window degrades the noise property because the noise in X-ray images is mainly determined by the statistical noise, and the statistical noise is inversely related to the square root of the number of incident photons [18]. The results showed that the hamming filter increased the CNRs of gold K-edge CT images compared to the Ram-Lak filter. This finding demonstrated that the quality of gold K-edge CT images is highly dependent on the noise property, and the noise suppression technologies are able to improve the performance of the gold K-edge CT imaging. The contrast of 25 mg/ml gold in the K-edge CT images was similar with that in the conventional CT images because the linear attenuation coefficients of 25 mg/ml gold in an energy range of 81–120 keV are lower than the brain tissue. This result would be helpful to determine the minimum concentration of gold-based contrast agents for clinical applications. In practice, the pulse pile-up causes the inaccurate recording of X-ray photon energies, leading to the spectral distortion [19]. This effect may influence the results of the gold K-edge imaging based on the PCD in clinical applications. Therefore, the compensation methods for the pulse pile-up, such as fast readout electronics and correction models, should be considered to validate our results in a clinical CT system [5,20]. 5. Conclusion The PCDs allow the energy-selective X-ray imaging, yielding the enhancement of image quality and the improvement of material decomposition efficiency. This study demonstrates the feasibility of the gold K-edge CT imaging and shows the characteristics of the technique. In conclusion, the gold-based contrast agents can be used for implementing the K-edge CT imaging, and the technique is able to improve the image quality with noise suppression techniques. In addition, this study can help to determine the minimum concentration of gold-based contrast agents. Acknowledgments This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (Grant No. NRF-2016R1C1B1010642). References [1] E. Roessl, R. Proksa, K-edge imaging in x-ray computed tomography using multi-bin photon counting detectors, Phys. Med. Biol. 52 (2007) 4679–4696. [2] T. Takahashi, S. Watanabe, Recent progress in CdTe and CdZnTe detectors, IEEE Trans. Nucl. Sci. 48 (2001) 950–959. [3] K. Taguchi, J.S. Iwanczyk, Vision 20/20: Single photon counting x-ray detectors in medical imaging, Med. Phys. 40 (2013) 100901. [4] K. Spartiotis, et al., A photon counting CdTe gamma- and X-ray camera: nucl, Instrum. Methods Phys. Res. Sect. A 550 (2005) 267–277. [5] L. Abbene, G. Gerardi, F. Principato, Digital performance improvements of a CdTe pixel detector for high flux energy-resolved X-ray imaging: nucl, Instrum. Methods Phys. Res. Sect. A 777 (2015) 54–62. [6] P.M. Shikhaliev, Beam hardening artefacts in computed tomography with photon counting, charge integrating and energy weighting detectors: a simulation study, Phys. Med. Biol. 50 (2005) 5813–5827. [7] Y. Lee, S. Lee, S. Kang, J. Eom, Dose optimization for dual-energy contrast-enhanced digital mammography based on an energy-resolved photon-counting detector: a Monte Carlo simulation study, Radiat. Phys. Chem. 132 (2017) 46–51. [8] J.P. Schlomka, et al., Experimental feasibility of multi-energy photon-counting K-edge imaging in pre-clinical computed tomography, Phys. Med. Biol. 53 (2008) 4031–4047. [9] M. Andreucci, R. Solomon, A. Tasanarong, Side effects of radiographic contrast media: pathogenesis, risk factors, and prevention, Biomed. Res. Int. 2014 (2014) 741018–741021. [10] L.E. Cole, R.D. Ross, J.M. Tilley, T. Vargo-Gogola, R.K. Roeder, Gold nanoparticles as contrast agents in x-ray imaging and computed tomography, Nanomedicine 10 (2015) 321–341. [11] B. Jo, H.S. Im, H.J. Kim, T.J. Son, H.J. Kim, The potential of spectral-CT for material decomposition with gold-nanoparticle and iodine contrast, IFMBE Proc. 51 (2015) 22–25. [12] Q.Y. Cai, et al., Colloidal gold nanoparticles as a blood-pool contrast agent for X-ray computed tomography in mice, Invest. Radiol. 42 (2007) 797–806. [13] R. Popovtzer, et al., Targeted gold nanoparticles enable molecular CT imaging for cancer, Nano Lett. 8 (2008) 4593–4596.
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[14] S. Jan, et al., GATE V6: a major enhancement of the GATE simulation platform enabling modeling of CT and radiotheraphy, Phys. Med. Biol. 56 (2011) 881–901. [15] K. Carney, B.J. Gilmore, G.W.A. Fogarty, L. Desponds, Catalogue of Diagnostic X-ray Spectra and Other Data Report No 78, Institute of Physics and Engineering in Medicine, 1997. [16] S.-W. Lee, et al., Feasibility of photon-counting K-edge imaging in X-ray and computed tomographic systems: monte carlo simulation studies, J. Korean Phys. Soc. 59 (2011) 2833–2839. [17] B. De Man, S. Basu, Distance-driven projection and backprojection in three dimensions, Phys. Med. Biol. 49 (2004) 2463–2475. [18] G.F. Knoll, Radiation Detection and Measurement, Wiley, New York, 2010. [19] A.S. Wang, D. Harrison, V. Lobastov, J.E. Tkaczyk, Pulse pileup statistics for energy discriminating photon counting x-ray detectors, Med. Phys. 38 (2011) 4265–4275. [20] K. Taguchi, E.C. Frey, X. Wang, J.S. Iwanczyk, W.C. Barder, An analytical model of the effects of pulse pileup on the energy spectrum recorded by energy resolved photon counting x-ray detectors, Med. Phys. 37 (2010) 3957–3969.
Contents lists available at ScienceDirect
Optik journal homepage: www.elsevier.de/ijleo
Original research article
Evaluation of gold K-edge imaging using spectral computed tomography with a photon-counting detector: A Monte Carlo simulation study Sooncheol Kang a , Jisoo Eom a , Burnyoung Kim b , Seungwan Lee a,b,∗ a b
Department of Medical Science, Konyang University, 158 Gwanjeodong-ro, Daejeon 35365, South Korea Department of Radiology Science, College of Medical Science, Konyang University, 158 Gwanjeodong-ro, Daejeon 35365, South Korea
a r t i c l e
i n f o
Article history: Received 25 January 2017 Accepted 16 April 2017 Keywords: Photon-counting detector Gold K-edge imaging Monte Carlo simulation
a b s t r a c t Energy-integrating detectors (EIDs) are hard to reflect information of multi-energy X-rays due to its detection mechanism. On the other hand, photon-counting detectors (PCDs) are able to selectively acquire spectral information using energy thresholds. This characteristic of the PCDs allows the K-edge imaging technique, which is able to increase the contrast of high atomic number materials, such as iodine, gadolinium, and gold. Especially, the characteristics of gold can provide benefits for clinical applications because gold has minimal toxicity and a high K-edge absorption energy of 80.7 keV. In this study, a spectral CT system using a cadmium zinc telluride (CZT)-based PCD was designed by a Monte Carlo simulation tool. Phantoms were simulated to obtain gold K-edge and conventional CT images, and different reconstruction filters were used for investigating the noise property. The obtained images were evaluated by measuring contrast-to-noise ratios (CNRs). The results of this study showed that the CNRs of gold K-edge CT images were higher than those of conventional CT images, and a noise suppression filter improved the CNRs of gold K-edge CT images. It was concluded that gold has a high performance as a contrast agent, and the gold K-edge CT imaging enable the excellent material decomposition. © 2017 Elsevier GmbH. All rights reserved.
1. Introduction In general, X-ray sources used for diagnosis generate polychromatic energy beams, and these X-ray photons interact with matters in accordance with their energy levels. This physical phenomenon indicates that transmitted X-ray photons have different information of the matters. However, energy-integrating detectors (EIDs) used in conventional computed tomography (CT) systems are hard to obtain spectral information of the transmitted X-ray photons due to its detection mechanism [1]. On the other hand, photon-counting detectors (PCDs) are able to measure spectral information using the multiple energy thresholds, which are operated by application specific integrated circuits (ASICs) [2,3]. The PCDs can also reduce the image noise caused by detector leakage current and arising in low energy levels (<20 keV) [4]. Especially, the PCDs based on cadmium telluride (CdTe) and cadmium zinc telluride (CZT) with the thicknesses of 2–3 mm have high detection
∗ Corresponding author at: Departments of Medical Science and Radiological Science, Konyang University, 158 Gwanjeodong-ro, Daejeon 35365, South Korea. E-mail address: [email protected] (S. Lee). http://dx.doi.org/10.1016/j.ijleo.2017.04.062 0030-4026/© 2017 Elsevier GmbH. All rights reserved.
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Fig. 1. Linear attenuation coefficient curves as a function of the incident X-ray energy for gold, iodine, skull, brain and PMMA.
efficiency for X-ray photons in an 1–140 keV range in comparison with EIDs [5]. These characteristics of PCDs enable to implement novel X-ray imaging techniques, improve image quality and overcome the limitations of the EIDs. Recently, several studies showed the availability of PCDs and proposed the spectral X-ray imaging techniques, such as energy-weighting and multi-energy imaging, for computed tomography and mammography [6,7]. One of the spectral X-ray imaging techniques is K-edge imaging. The K-edge imaging technique is based on the attenuation property of a material, which is a sudden increase of attenuation coefficient at a specific energy level, called K-edge discontinuity, and this property is observed in high atomic number materials, such as contrast agents [8] (Fig. 1). The K-edge imaging technique can improve the contrast of a target material by obtaining the energy-selective information above the K-edge absorption energy of the target material, and this technique is able to implement by using the energy thresholds of PCDs [2,8]. Although iodine contrast agents are widely used for CT angiography and provide high contrast resolution, they still have the toxicity issues causing the malfunction of organs [9]. Also the K-edge images using the iodine contrast agents are limited to discriminate target materials from other tissues in thick objects, such as human patients due to the relatively low K-edge absorption energy of iodine, high tube voltages in human applications and beam hardening effect [8]. Unlike other contrast agents, gold has the K-edge absorption energy of 80.7 keV due to its high atomic number and has the excellent capability of material decomposition [10,11]. Also, gold nanoparticles (GNPs) improve contrast for a long time after delivery to target organs because they have a long circulation time. And the GNPs have minimal toxicity [12]. Moreover, the coated GNPs, such as polymer, PEG and gadolinium-coated GNPs, have been used for vascular imaging and tumor detection [13]. Therefore, it needs to improve the quality of CT images with the gold contrast agents and investigate the characteristics of the gold K-edge CT imaging. In this study, a spectral CT system using a CZT-based PCD was simulated to implement the gold K-edge CT imaging. We compared the gold K-edge CT images with conventional CT images in terms of contrast-to-noise ratio (CNR) and evaluated the characteristics of gold K-edge CT images. 2. Materials and methods 2.1. Simulation setup and spectral CT system In this study, Geant4 Application for Tomographic Emission (GATE) version 6.0 was used for Monte Carlo simulations. The interactions between X-ray photons and materials were simulated for considering electromagnetic processes, and the CT scanner module was used to obtain X-ray images [14]. The detector was designed in accordance with eValuator-3500 (eV Product, USA), which is based on CZT substances and has a size of 128 × 0.5 mm2 , a thickness of 3 mm and a pixel size of 0.5 × 0.5 mm2 . The PCDs have a limitation of pulse pile-up, which causes spectral distortion, under the high flux of photons (>1 × 106 /mm2 ·s) [3,5]. In this study, we assume that there is no spectral distortion induced by the pulse pile-up due to determining the feasibility of the gold K-edge CT imaging and evaluating its characteristics. For comparing gold K-edge CT images with conventional CT images, a silicon (Si) detector was also simulated with the specifications of the PCD. The focus-to-center of rotation distance and the focus-to-detector distance were 550 and 1000 mm, respectively. In order to identify the characteristics of the gold K-edge CT imaging, a cylindrical phantom was designed with a diameter of 80 mm and a height of 15 mm. The phantom consisted of polymethyl methacrylate (PMMA) and had four 20 mm diameter holes filled with the different concentrations of gold materials (Fig. 2). The X-ray spectrum for image acquisition was simulated at a tube voltage of 120 kVp with a tube current of 3.75 mA and a 2 mm aluminum filter by using the SRS-78 program (Fig. 3) [15]. Also, a head phantom was designed to simulate cerebral angiography. The phantom had a cylindrical shape with a diameter of 50 mm, which is similar to the long axis of head of a rat, and a height of 15 mm. The phantom was composed of
S. Kang et al. / Optik 140 (2017) 253–260
255
Fig. 2. Schematic illustrations of the PMMA phantom at (a) side view and (b) top view.
Fig. 3. Simulated input X-ray spectrum used for obtaining the CT images of the PMMA phantom. (a) represents the energy window for the gold K-edge CT imaging (81–120 keV).
brain tissue (density = 1.04 g/cm3 ), which is surrounded by skull (density = 1.61 g/cm3 ), and had eight 6 mm diameter holes filled with the different concentrations of gold materials (Fig. 4). For obtaining the images of the head phantom, the X-ray spectrum was simulated at a tube voltage of 120 kVp with a tube current of 1.5 mA and a 2 mm aluminum filter (Fig. 5). 2.2. Data acquisition, image reconstruction and analysis The PCDs can acquire energy selective images using the energy windows defined by energy thresholds. A previous study showed that the K-edge imaging is feasible with the energy window located above the K-edge absorption energy of a target material [16]. In this study, an energy window of 81–120 keV was used to obtain gold K-edge CT images because the K-edge absorption energy of gold is 80.7 keV. Conventional CT images were obtained by using the full X-ray energy spectrum. To acquire tomographic images, 180 projections of the phantoms were obtained during a full 360 ◦ rotation, and the image reconstruction was performed by using a model-based filtered back-projection algorithm with the pixel-driven method. The pixel-driven method operates by connecting rays from an X-ray source to the centers of image pixels. The line integrals can be calculated by using the interpolation, which is based on the distances between the projected locations of rays on a detector plane and the centers of detector pixels [17]. The quality of K-edge images depends on noise property because the K-edge images are generated by the small number of photons, which is included in a specific energy window and increases the statistical noise in X-ray images. Thus, the hamming filter was used to improve the noise property of K-edge images, and the Ram-Lak filter was also used for comparison. The reconstructed images of the PMMA and head phantoms had arrays of 160 × 160 and 100 × 100 pixels, respectively.
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Fig. 4. Schematic illustrations of the head phantom at (a) side view and (b) top view.
Fig. 5. Simulated input X-ray spectrum used for obtaining the CT images of the head phantom. (a) represents the energy window for the gold K-edge CT imaging (81–120 keV).
The CNR was measured in order to evaluate and compare the image quality of gold K-edge and conventional CT images. For the PMMA phantom, the CNR was calculated between PMMA and gold materials with the regions of interest (ROIs) of 10 × 10 pixels. We also calculated the CNR between brain and gold materials with the ROIs of 5 × 5 pixels for the head phantom. The CNR is defined by the following equation: CNR =
|t − b | (t )2 + (b )2
,
(1)
where t and b are the mean values of target and background materials. t and b are the standard deviations of target and background materials. 3. Results Fig. 6 shows the conventional and gold K-edge CT images of the PMMA phantom. The contrast of gold materials increased in the K-edge CT image compared with the conventional CT image. The CNR increased as a function of the concentration of gold, and the gold K-edge CT imaging improved the CNR in comparison to the conventional CT imaging (Fig. 7). The CNRs of the gold K-edge CT images were approximately 1.74, 1.3 and 1.31 times higher than those of the conventional CT images for 100, 150 and 200 mg/ml gold materials, respectively. But, there was little difference in CNR between the conventional and
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Fig. 6. (a) Conventional CT image using a Si detector and (b) gold K-edge CT image using a CZT-based PCD with an energy window of 81–120 keV. All images are displayed in a same gray scale.
Fig. 7. CNRs of gold materials of the PMMA phantom for the conventional and gold K - edge CT images.
Table 1 CNR improvements between the conventional and gold K-edge CT images for the PMMA phantom. Gold concentration
CNR improvement
50 mg/ml
100 mg/ml
150 mg/ml
200 mg/ml
1.00
1.74
1.30
1.31
gold K-edge CT images for the 50 mg/ml gold material. The CNR improvements for the PMMA phantom are summarized in Table 1. To evaluate the noise property of the gold K-edge CT imaging, the projections of the head phantom were reconstructed with the Ram-Lak and hamming filters (Fig. 8). Similar to the results of the PMMA phantom, the gold K-edge CT imaging improved the contrast of gold materials for the head phantom. The reconstructed values of brain tissue and skull in the gold K-edge CT images were significantly lower than those in the conventional CT images. We could observe that the image noise was suppressed by the hamming filter. Fig. 9 shows the CNRs between brain tissue and gold materials for the conventional and gold K-edge CT imaging with the different reconstruction filters. For the concentrations of 50–200 mg/ml, the CNRs of the gold K-edge CT images were approximately 1.03–1.42 and 1.07–1.54 times higher than those of the conventional CT images for the Ram-Lak and hamming filters, respectively. However, in the gold K-edge CT images, the CNRs of the 25 mg/ml gold material decreased by factors of 0.51–0.54 compared to the conventional CT images. The CNR improvements for the head phantom are summarized in Table 2.
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Fig. 8. Conventional CT images reconstructed with the (a) Ram-Lak and (c) hamming filters. Gold K-edge CT images reconstructed with the (b) Ram-Lak and (d) hamming filters. All images are displayed in a same gray scale.
Fig. 9. CNRs between brain tissue and gold materials for the head phantom reconstructed with the Ram-Lak and hamming filters. The white and gray bars represent the results for the Ram-Lak and hamming filters, respectively.
4. Discussion The PCDs have an ability to distinguish the energy of X-ray photons and can reflect attenuation information of materials for each X-ray photons. These characteristics enable the acquisition of the energy-selective X-ray images, which are defined by energy windows.
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Table 2 CNR improvements between the conventional and gold K-edge CT images for the head phantom. Filters
Ram-lak filter Hamming filter
Gold concentration 25 mg/ml
50 mg/ml
75 mg/ml
100 mg/ml
125 mg/ml
150 mg/ml
175 mg/ml
200 mg/ml
0.54 0.51
1.42 1.54
1.03 1.07
1.16 1.22
1.23 1.35
1.24 1.25
1.29 1.34
1.30 1.32
In this study, we simulated a spectral CT system with a CZT-based PCD using a Monte Carlo simulation tool in order to implementing the gold K-edge CT imaging. The gold K-edge CT images were obtained with the different concentrations of gold. The CNRs between gold and background materials were measured for evaluating and comparing the image quality with the conventional CT images. The results showed that the CNRs increased with an increase of the concentration of gold, and the K-edge CT imaging technique improved the CNRs compared to the conventional CT imaging technique. These results demonstrated that the gold-based contrast agents have a potential to improve the image quality of CT images and the diagnostic accuracy. The CNR improvement was due to the limited energy window located above the K-edge absorption energy of gold. The limited energy window reflected a sudden increase of the attenuation coefficients of gold in CT images. However, the limited energy window degrades the noise property because the noise in X-ray images is mainly determined by the statistical noise, and the statistical noise is inversely related to the square root of the number of incident photons [18]. The results showed that the hamming filter increased the CNRs of gold K-edge CT images compared to the Ram-Lak filter. This finding demonstrated that the quality of gold K-edge CT images is highly dependent on the noise property, and the noise suppression technologies are able to improve the performance of the gold K-edge CT imaging. The contrast of 25 mg/ml gold in the K-edge CT images was similar with that in the conventional CT images because the linear attenuation coefficients of 25 mg/ml gold in an energy range of 81–120 keV are lower than the brain tissue. This result would be helpful to determine the minimum concentration of gold-based contrast agents for clinical applications. In practice, the pulse pile-up causes the inaccurate recording of X-ray photon energies, leading to the spectral distortion [19]. This effect may influence the results of the gold K-edge imaging based on the PCD in clinical applications. Therefore, the compensation methods for the pulse pile-up, such as fast readout electronics and correction models, should be considered to validate our results in a clinical CT system [5,20]. 5. Conclusion The PCDs allow the energy-selective X-ray imaging, yielding the enhancement of image quality and the improvement of material decomposition efficiency. This study demonstrates the feasibility of the gold K-edge CT imaging and shows the characteristics of the technique. In conclusion, the gold-based contrast agents can be used for implementing the K-edge CT imaging, and the technique is able to improve the image quality with noise suppression techniques. 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