- Open Access
Radiotherapy treatment planning with contrast-enhanced computed tomography: feasibility of dual-energy virtual unenhanced imaging for improved dose calculations
© Yamada et al.; licensee BioMed Central Ltd. 2014
- Received: 25 March 2014
- Accepted: 22 July 2014
- Published: 29 July 2014
In radiotherapy treatment planning, intravenous administration of an iodine-based contrast agent during computed tomography (CT) improves the accuracy of delineating target volumes. However, increased tissue attenuation resulting from the high atomic number of iodine may result in erroneous dose calculations because the contrast agent is absent during the actual procedure. The purpose of this proof-of-concept study was to present a novel framework to improve the accuracy of dose calculations using dual-energy virtual unenhanced CT in the presence of an iodine-based contrast agent.
Simple phantom experiments were designed to assess the feasibility of the proposed concept. By utilizing a “second-generation” dual-source CT scanner equipped with a tin filter for improved spectral separation, four CT datasets were obtained using both a water phantom and an iodine phantom: “true unenhanced” images with attenuation values of 2 ± 11 Hounsfield Units (HU), “enhanced” images with attenuation values of 274 ± 23 HU, and two series of “virtual unenhanced” images synthesized from dual-energy scans of the iodine phantom, each with a different combination of tube voltages. Two series of virtual unenhanced images demonstrated attenuation values of 12 ± 29 HU (with 80 kVp/140 kVp) and 34 ± 10 HU (with 100 kVp/140 kVp) after removing the iodine component from the contrast-enhanced images. Dose distributions of the single photon beams calculated from the enhanced images and two series of virtual unenhanced images were compared to those from true unenhanced images as a reference.
The dose distributions obtained from both series of virtual unenhanced images were almost equivalent to that from the true unenhanced images, whereas the dose distribution obtained from the enhanced images indicated increased beam attenuation caused by the high attenuation characteristics of iodine. Compared to the reference dose distribution from the true unenhanced images, the dose distribution pass rates from both series of virtual unenhanced images were greater than 90%, while those from the enhanced images were less than approximately 50–60%.
Dual-energy virtual unenhanced CT improves the accuracy of dose distributions in radiotherapy treatment planning by removing the iodine component from contrast-enhanced images.
- Radiotherapy treatment planning
- Dual-energy CT
- Virtual unenhanced CT
- Dose calculation
- Iodine contrast agent
- Tissue attenuation
- CT number
- Dual-source CT
- Tin filter
The use of computed tomography (CT) is now an established procedure in modern radiotherapy treatment planning. Cross-sectional CT data allow for the accurate delineation of surface contours and internal structures including target and critical organs. In addition, the pixel values, i.e., the CT numbers in Hounsfield Units (HU), provide tissue electron density information, which allows a pixel-by-pixel correction for tissue inhomogeneities when calculating dose distributions. Although other imaging modalities are becoming important tools in treatment planning, CT is still the fundamental and primary modality.
An inherent disadvantage of CT is its relatively lower contrast between lesions and surrounding tissue or vessels. Thus, diagnostic CT often requires the intravenous administration of an iodine-based contrast agent to enhance lesion-to-tissue contrast. Because the accurate delineation of target volumes (and organs at risk) is crucial in radiotherapy treatment planning, the use of an iodine-based contrast agent is necessary in situations in which contrast is likely to improve the accuracy of the target or normal structure delineations. However, there is a concern that the introduction of contrast agent may result in erroneous dose calculations . In an actual treatment situation, the patient does not receive contrast agent, and hence the tissue density during treatment will differ from that during a contrast-enhanced CT scan. Although several clinical studies on head and neck , lung , and prostate cancers  have shown that contrast media had little influence on dose calculations, this issue is still debated [5–7].
This study comprised two phantom experiments. The first experiment assessed dual-energy virtual unenhanced attenuation values of iodine solutions under two different combinations of tube voltages. The second experiment investigated the feasibility of dose calculation using virtual unenhanced imaging. All experiments were conducted using a dual-source CT scanner (SOMATOM Definition Flash, Siemens AG, Erlangen, Germany). A dedicated application “Liver VNC” (Siemens) was utilized to reconstruct virtual unenhanced images.
Assessment of virtual unenhanced attenuation values
We prepared a phantom comprising eight polypropylene syringes, each containing a 10-mL mixture of water and an iodine-based contrast agent (Iopamidol, 300 mgI/mL) at different dilutions (4.50%, 2.00%, 1.00%, 0.50%, 0.25%, 0.13%, 0.06%, and 0.00% by weight). The phantom was placed at the isocenter of the CT scanner, and scanned using both single-energy and dual-energy helical modes. For the single-energy scan, only one X-ray tube was operated at 120 kVp and 100 mAs. For the dual-energy scan, two combinations of tube settings, each using the tin filter for the high-energy beam, were tested: (i) 80 kVp with 100 mAs and 140 kVp with 39 mAs (referred to as the “80/Sn140-kVp protocol”); and (ii) 100 kVp with 100 mAs and 140 kVp with 77 mAs (referred to as the “100/Sn140-kVp protocol”). The slice thickness and reconstructed field-of-view for both scans were 5 mm and 150 mm, respectively. The images were reconstructed with standard body kernels (B35f for single-energy scans and D26f for dual-energy scans). Two series of virtual unenhanced images (i.e., 80/Sn140-kVp and 100/Sn140-kVp protocols) were synthesized from the corresponding dual-energy data. In addition, “mixed” images were synthesized using a linear weighting of the low- and high-kVp images. In diagnostic dual-energy applications, the mixed images are used as representative of dual-energy data, because they are similar to traditional single-energy (i.e., 120 kVp) images. Circular regions-of-interest (ROIs) were positioned within the syringes to obtain mean attenuation values in HU. The size of the ROIs was chosen to encompass an approximately 80% area of the syringes. The scans were repeated three times, and the mean attenuation values and standard deviation of the three measurements were calculated for comparisons.
Feasibility of dose calculation using virtual unenhanced CT
These four CT datasets were transferred to a Pinnacle3 treatment planning system (version 8.0 m; Philips, Madison, WI, USA) for dose calculations. The dose distribution of a single photon beam from a Siemens Oncor Impression Plus system was calculated using a collapsed cone convolution algorithm with a dose grid size of 2 mm. Two beam energies (4 MV and 10 MV) and two field sizes (4 × 4 cm2 and 10 × 10 cm2) were tested for each dataset. The beam was planned to deliver 100 monitor units at a 10-cm depth at the center of the phantom. Although the phantom was carefully prepared, it was impossible to avoid introducing small air bubbles at the top of the phantom. Therefore, the posterior field was chosen to minimize the effects of these small bubbles on the dose calculations. The dose distributions obtained from the enhanced and virtual unenhanced (both the 80/Sn140-kVp and 100/Sn140-kVp protocols) images were quantitatively compared to those from the true unenhanced images using MapCHECK (Sun Nuclear, Melbourne, FL, USA) analysis software. For the analysis, the calculated planar dose distribution in the sagittal on-axis plane for each dataset was imported into the software; the distribution obtained from the true unenhanced images was used as a reference, and the remaining three were the subjects being tested. The assessment was performed based on the percent-dose-difference and distance-to-agreement at a 10% dose threshold. A set of acceptance criteria (2% and 2 mm) satisfying the guideline  was used, and the percentage of points passing the acceptance criteria was evaluated.
Attenuation measurements of iodine solutions at different iodine concentrations
Iodine concentration [%w/w]
Attenuation value [HU]
Single-energy (120 kVp)
Dual-energy (80 kVp/Sn140 kVp)
Dual-energy (100 kVp/Sn140 kVp)
-11.3 ± 1.3
-10.4 ± 0.1
-23.0 ± 1.0
-10.7 ± 0.6
-21.0 ± 0.6
-3.9 ± 0.5
-6.9 ± 0.1
-26.8 ± 0.9
-8.0 ± 0.4
-24.5 ± 1.5
4.7 ± 0.5
0.1 ± 0.2
-25.1 ± 0.8
-1.6 ± 0.4
-24.1 ± 0.7
16.4 ± 0.4
11.1 ± 1.1
-26.6 ± 1.8
7.9 ± 0.8
-25.3 ± 1.1
40.5 ± 0.5
33.5 ± 0.2
-25.8 ± 1.1
27.2 ± 0.4
-25.7 ± 1.1
91.1 ± 0.4
78.5 ± 0.4
-27.1 ± 1.1
65.8 ± 0.6
-28.4 ± 0.4
192.3 ± 0.3
168.7 ± 0.3
-29.1 ± 0.3
143.0 ± 0.3
-32.5 ± 1.3
444.1 ± 0.7
397.9 ± 0.4
-28.7 ± 0.3
340.1 ± 0.3
-35.1 ± 1.9
Attenuation measurements of water and iodine phantoms
Attenuation values [HU]
Water phantom/true unenhanced image
Iodine phantom/enhanced image
Iodine phantom/virtual unenhanced (80/Sn140-kVp) image
Iodine phantom/virtual unenhanced (100/Sn140-kVp) image
Pass rates of dose calculations based on the enhanced and virtual unenhanced CT images
Field size [cm2]
Pass rate [%]
80 kVp/Sn140 kVp
100 kVp/Sn140 kVp
10 × 10
4 × 4
10 × 10
4 × 4
The use of a contrast agent during CT for treatment planning offers the potential benefit of a much higher accuracy in delineating target and critical volumes. However, there is a significant concern that the high atomic number of iodine may introduce errors into dose calculations; the calculated dose may be underestimated, resulting in the delivery of a higher dose than prescribed. This scenario would occur in organs containing an increased iodine concentration. In fact, Shibamoto et al. found that the administration of a contrast agent influenced treatment planning at the upper abdomen, especially when the beams passed through organs with high iodine concentrations such as the liver, spleen, and kidneys . Our present results support their findings. The iodine phantom used in this study presented almost uniformly distributed attenuation values of approximately 270 HU (Figure 4b; Figure 5; Table 2), which approximates that of organs in the upper abdomen on contrast-enhanced CT. As shown in Figures 6, 7 and 8(b), the dose distributions obtained from the enhanced images show increased beam attenuation compared to those from the true unenhanced images (a). The corresponding error maps (Figures 6, 7 and 8e) show that the calculated dose obtained from the enhanced images tends to differ from that based on the true unenhanced images as the beam passes through the phantom from the bottom to the top. In Figure 7, for instance, the dose distribution (a) obtained using the true unenhanced images shows a delivery of 72 cGy at the 10-cm depth of the central axis; in contrast, the dose error was at least 4 cGy when the enhanced images were used (e). In this case, the use of the enhanced images leads to erroneous dose delivery greater than 5% of the prescribed dose. This error is not negligible and would be problematic for treatment planning, especially in the upper abdomen as Shibamoto et al. reported .
Our novel approach to solve this issue is to remove the iodine component from contrast-enhanced CT using dual-energy virtual unenhanced imaging. Dual-energy virtual unenhanced imaging has recently become a promising technique in diagnostic CT to reduce the radiation dose by negating the need for an unenhanced scan [9–11]. Although the clinical potential of dual-energy CT in the field of radiation oncology has not been well investigated to date, several studies have shown that dual-energy CT allows for an accurate estimation of electron density for treatment planning [19–21]. Our study reveals an additional important aspect of its application that could improve the accuracy of radiotherapy treatment planning. Figure 3 shows that virtual unenhanced CT can remove the iodine component from a contrast-enhanced CT image within a wide range of iodine concentrations at CT number levels greater than the water density, in accordance with previous reports [9–14], including a similar phantom study of iodine solutions . Thus, our study aimed to improve the accuracy of dose calculations from contrast-enhanced CT by removing their iodine components, and the results successfully demonstrated the feasibility of our proposed method. As shown in Figures 6, 7 and 8, the dose distributions obtained from virtual unenhanced images (c and d) were almost equivalent to those from true unenhanced images (a). The differences in dose calculations between true unenhanced and virtual unenhanced images were extremely close to 0 cGy (f and g), except at the beam edges and dose build-up regions (near the bottom of the phantom), which both have high dose gradients. In addition, the use of the 100/Sn140-kVp protocol further improved the accuracy of dose distributions at the dose build-up region. The pass rates of dose calculations (Table 3) from the virtual unenhanced images were greater than 90%, whereas those from the enhanced images were less than approximately 50–60% and thus no longer acceptable.
The virtual unenhanced imaging results in potentially unstable CT numbers when the differences between attenuation values at low- and high-kVp are small. Therefore, the “first-generation” dual-source CT scanner minimized spectral overlap by performing the low-energy scan at 80 kVp . However, the use of an 80-kVp beam brought about an inappropriately low photon rate at the detectors, especially in the abdominal scan, due to a low penetration. Thus, the resultant virtual unenhanced images suffered from increased image noise and artifacts. Although the tin filter could improve spectral separation, the use of an 80-kVp beam would still be problematic. The virtual unenhanced attenuation values of iodine syringes with the 80/Sn140-kVp protocol were indeed more stable than those obtained with the 100/Sn140-kVp protocol at high iodine concentrations (Table 1); this experiment was performed with a small phantom. In fact, the virtual unenhanced (80/Sn140-kVp) images of the iodine phantom, which was used in the second experiment, suffer from increased noise and dark-band artifacts (Figure 4,c). The attenuation profile with the 80/Sn140-kVp protocol (Figure 5, green line) fluctuated greatly at the center of the phantom, due to the dark-band artifacts. In contrast, the virtual unenhanced attenuation values using the 100/Sn140-kVp protocol were stable qualitatively (Figure 4d) and quantitatively (Figure 5, blue line). The mean attenuation values of the virtual unenhanced (100/Sn140-kVp) and true unenhanced images were 34.1 ± 9.9 HU and 1.6 ± 11.0 HU, respectively. This small difference had no effect on dose calculations as shown in Figures 6, 7 and 8.
The current dual-source virtual unenhanced CT has several known potential limitations, which were investigated by Barrett, et al. . For radiotherapy treatment planning, its relatively smaller field-of-view and susceptibility to motion warrants consideration. The effective field-of-view that can remove iodine components from contrast-enhanced images is limited to 322 mm or less in diameter. This is problematic in larger patients or in more superficial radiotherapy targets because the contrast-enhanced tissue that is located outside the region will remain “enhanced” after the iodine-removal process. This limitation arises from the current scanner configuration, and therefore, it can be alleviated in the future. Also notable is the relatively higher susceptibility to motion in virtual unenhanced imaging, which arises from the 95° offset of the source-detector systems. The angle offset causes one detector to see a different motion compared to the other detector, and this difference is amplified by the subtraction process. A shorter gantry rotation time can reduce motion artifacts, but the potential for the artifact remains, particularly in the upper-abdominal organs, lung bases, and cardiovascular systems. Another potential limitation of virtual unenhanced imaging is the underestimation of attenuation values of high atomic number materials such as bone. In previous reports [9–11, 14], clinical virtual unenhanced images visually demonstrated highly attenuating bone, resembling the normal CT appearance; the iodine removal process would affect the virtual unenhanced attenuation value, depending on the parameters of iodine removal (e.g., “standard tissue” and “fat” CT numbers, “beam-hardening correction” option for iodine, and “relative contrast enhancement ratio” value between low- and high-energy images in “Liver VNC” application). We expect that this underestimation of bone attenuation has little influence on the dose calculation because bone (especially cortical bone) encompasses a relatively small volume within the trunk; however, further investigations evaluating the accuracy and the impact of bone virtual unenhanced attenuation values on dose calculations, optimizing the processing parameters, and (if necessary) developing a correction scheme are needed.
This proof-of-concept study is very preliminary, and therefore has several limitations. First, we only conducted simple phantom experiments and did not perform any clinical investigations. Second, the optimal acquisition and reconstruction parameters suitable for applying virtual unenhanced images to radiotherapy treatment planning were not investigated. These limitations are practical in nature; the dual-energy CT scanner used in this study is currently not available for radiotherapy treatment planning. Third, as mentioned above, the reliability of virtual unenhanced attenuation values of high atomic number materials such as bone has not been investigated. Further investigation of these issues is needed to confirm the clinical potential of virtual unenhanced CT in radiotherapy treatment planning.
We have proposed a novel strategy to improve the accuracy of radiotherapy treatment planning using dual-energy virtual unenhanced CT. The introduction of contrast agents can improve the delineation of the target and risk organs. The iodine component can be subsequently removed from contrast-enhanced CT images to provide virtual unenhanced images to perform more accurate dose calculations. Our results have successfully provided the first proof-of-concept.
This study was supported in part by a Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research (No. 25460751). The authors gratefully acknowledge the assistance of the staff at the Trauma and Acute Critical Care Center (TACCC) of Osaka University Hospital, especially Mr. Takeo Azuma, a senior radiological technologist.
- Ramm U, Damrau M, Mose S, Manegold KH, Rahl CG, Böttcher HD: Influence of CT contrast agents on dose calculations in a 3D treatment planning system. Phys Med Biol 2001, 46: 2631-2635.View ArticlePubMedGoogle Scholar
- Liauw SL, Amdur RJ, Mendenhall WM, Palta J, Kim S: The effect of intravenous contrast on intensity-modulated radiation therapy dose calculations for head and neck cancer. Am J Clin Oncol 2005, 28: 456-459.View ArticlePubMedGoogle Scholar
- Lees J, Holloway L, Fuller M, Forstner D: Effect of intravenous contrast on treatment planning system dose calculations in the lung. Australas Phys Eng Sci Med 2005, 28: 190-195.View ArticlePubMedGoogle Scholar
- Weber DC, Rouzaud M, Miralbell R: Bladder opacification does not significantly influence dose distribution in conformal radiotherapy of prostate cancer. Radiother Oncol 2001, 59: 95-97.View ArticlePubMedGoogle Scholar
- Shibamoto Y, Naruse A, Fukuma H, Ayakawa S, Sugie C, Tomita N: Influence of contrast materials on dose calculation in radiotherapy planning using computed tomography for tumors at various anatomical regions: a prospective study. Radiother Oncol 2007, 84: 52-55.View ArticlePubMedGoogle Scholar
- Zabel-du Bois A, Ackermann B, Hauswald H, Schramm O, Sroka-Perez G, Huber P, Debus J, Milker-Zabel S: Influence of intravenous contrast agent on dose calculation in 3-D treatment planning for radiosurgery of cerebral arteriovenous malformations. Strahlenther Onkol 2009, 185: 318-324.View ArticlePubMedGoogle Scholar
- Wertz H, Jäkel O: Influence of iodine contrast agent on the range of ion beams for radiotherapy. Med Phys 2004, 31: 767-773.View ArticlePubMedGoogle Scholar
- Johnson TR, Krauß B, Sedlmair M, Grasruck M, Bruder H, Morhard D, Fink C, Weckbach S, Lenhard M, Schmidt B, Flohr T, Reiser MF, Becker CR: Material differentiation by dual energy CT: initial experience. Eur Radiol 2007, 17: 1510-1517.View ArticlePubMedGoogle Scholar
- Barrett T, Bowden DJ, Shaida N, Godfrey EM, Taylor A, Lomas DJ, Shaw AS: Virtual unenhanced second generation dual-source CT of the liver: is it time to discard the conventional unenhanced phase? Eur J Radiol 2012, 81: 1438-1445.View ArticlePubMedGoogle Scholar
- Toepker M, Moritz T, Krauss B, Weber M, Euller G, Mang T, Wolf F, Herold CJ, Ringl H: Virtual non-contrast in second-generation, dual-energy computed tomography: reliability of attenuation values. Eur J Radiol 2012, 81: e398-405.View ArticlePubMedGoogle Scholar
- Sommer CM, Schwarzwaelder CB, Stiller W, Schindera ST, Stampfl U, Bellemann N, Holzschuh M, Schmidt J, Weitz J, Grenacher L, Kauczor HU, Radeleff BA: Iodine removal in intravenous dual-energy CT-cholangiography: is virtual non-enhanced imaging effective to replace true non-enhanced imaging? Eur J Radiol 2012, 81: 692-699.View ArticlePubMedGoogle Scholar
- Kawai T, Shibamoto Y, Hara M, Arakawa T, Nagai K, Ohashi K: Can dual-energy CT evaluate contrast enhancement of ground-glass attenuation? Phantom and preliminary clinical studies. Acad Radiol 2011, 18: 682-689.View ArticlePubMedGoogle Scholar
- Kawai T, Takeuchi M, Hara M, Ohashi K, Suzuki H, Yamada K, Sugimura Y, Shibamoto Y: Accuracy of iodine removal using dual-energy CT with or without a tin filter: an experimental phantom study. Acta Radiol 2013, 54: 954-960.View ArticlePubMedGoogle Scholar
- Kaufmann S, Sauter A, Spira D, Gatidis S, Ketelsen D, Heuschmid M, Claussen CD, Thomas C: Tin-filter enhanced dual-energy-CT: image quality and accuracy of CT numbers in virtual noncontrast imaging. Acad Radiol 2013, 20: 596-603.View ArticlePubMedGoogle Scholar
- De Cecco CN, Darnell A, Macías N, Ayuso JR, Rodríguez S, Rimola J, Pagés M, García-Criado Á, Rengo M, Laghi A, Ayuso C: Virtual unenhanced images of the abdomen with second-generation dual-source dual-energy computed tomography: image quality and liver lesion detection. Invest Radiol 2013, 48: 1-9.View ArticlePubMedGoogle Scholar
- Primak AN, Ramirez Giraldo JC, Liu X, Yu L, McCollough CH: Improved dual-energy material discrimination for dual-source CT by means of additional spectral filtration. Med Phys 2009, 36: 1359-1369.PubMed CentralView ArticlePubMedGoogle Scholar
- Primak AN, Giraldo JC, Eusemann CD, Schmidt B, Kantor B, Fletcher JG, McCollough CH: Dual-source dual-energy CT with additional tin filtration: dose and image quality evaluation in phantoms and in vivo. AJR Am J Roentgenol 2010, 195: 1164-1174.PubMed CentralView ArticlePubMedGoogle Scholar
- Van Dyk J, Barnett RB, Cygler JE, Shragge PC: Commissioning and quality assurance of treatment planning computers. Int J Radiat Oncol Biol Phys 1993, 26: 261-273.View ArticlePubMedGoogle Scholar
- Ogata T, Ueguchi T, Yagi M, Yamada S, Tanaka C, Ogihara R, Isohashi F, Yoshioka Y, Tomiyama N, Ogawa K, Koizumi M: Feasibility and accuracy of relative electron density determined by virtual monochromatic CT value subtraction at two different energies using the gemstone spectral imaging. Radiat Oncol 2013, 8: 83.PubMed CentralView ArticlePubMedGoogle Scholar
- Yagi M, Ueguchi T, Koizumi M, Ogata T, Yamada S, Takahashi Y, Sumida I, Akino Y, Konishi K, Isohashi F, Tomiyama N, Yoshioka Y, Ogawa K: Gemstone spectral imaging: determination of CT to ED conversion curves for radiotherapy treatment planning. J Appl Clin Med Phys 2013, 14: 173-186.PubMedGoogle Scholar
- Saito M: Potential of dual-energy subtraction for converting CT numbers to electron density based on a single linear relationship. Med Phys 2012, 39: 2021-2030.View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.