Color Coding of Contrast Material/Virtual Non-Contrast Images
The ability to map iodine content in soft tissue organs can be used to study the contrast enhancement of focal lesions, e.g. in the liver or kidney. The CT scan is obtained in normal venous phase. The iodine-related enhancement is color-coded in the image and superimposed with the normal CT image.
Additionally, a virtual non-contrast image can be derived from the contrast picture. It looks very similar to a true non-contrast image except that image noise is higher and spatial resolution is reduced. These images are mostly sufficient to determine the contrast enhancement of focal lesions. Because enhancement is determined in one dataset, misregistration, e.g. due to different respiratory positions, is impossible. An initial clinical study has shown that measured density values of virtual non-contrast images agree well with true non-contrast images, although the noise is somewhat higher (1).
Pulmonary Perfusion and Ventilation Imaging
If a three material decomposition is applied for iodine, soft tissue, and air, the perfusion of lung parenchyma can be mapped by iodine content. Shortly after arrival of the contrast bolus, the Dual Energy technique enables acquisition of a pulmonary angiogram and assessment of perfusion of the lung parenchyma in the same dataset. Initial studies have confirmed that occlusive embolism causes segmental perfusion defects, and that patchy perfusion patterns are observed in recurrent pulmonary embolism (2). Also, there is good agreement between perfusion scintigraphy with technetium-labeled macroaggregated albumin and Dual Energy perfusion maps (3).
If xenon gas is administered instead, ventilation of the lung parenchyma can be visualized. A short inhalation with a limited concentration avoids narcotic effects, but monitoring is necessary. Combining ventilation and perfusion imaging with information about the morphology and structure of the lung parenchyma may make it possible to use Dual Energy CT to perform a comprehensive workup of complex pulmonary diseases.
Dual Energy in Angiography
Another option is to use the spectral properties of iodine to differentiate it from other dense materials in the dataset. In angiography, an image can be acquired rapidly and easily with maximum intensity projections (MIPs), similar to magnetic resonance angiography (MRA).
With Dual Energy CT, it is possible to identify bone by its spectral behavior and to erase it from an angiogram. Then, the iodine in the vessels remains the only dense material in the dataset and a MIP can be calculated from a CT angiogram to closely resemble an MRA. Additionally, it is possible to detect those voxels that contain both calcium and iodine and add them back to the dataset. Calcified plaques of atherosclerotic vessels can thereby be switched on and off in the dataset to visualize both the residual lumen and the plaque distribution. This works very reliably both in supraaortic and runoff angiograms, providing an excellent overview of the vasculature and making it fast and easy to exclude relevant stenoses in a single image (4, 5).
Differentiation of Kidney Stones
An application that does not require contrast material is the differentiation of renal calculi. The three most frequent and clinically relevant types of renal stones are: calcified stones (74%), uric acid (15%) and struvite stones (11%).
Calcium and struvite stones can only be removed mechanically or crushed by an extracorporeal shock wave lithotripsy (ESWL), while uric acid calculi can be dissolved with Allopurinol and urine alkalization. While calcium and struvite (i.e. magnesium ammonium phosphate) contain ions with spectral properties, the spectral behavior of uric acid is rather weak.
A clinical in vitro and in vivo study has demonstrated the reliability of differentiating stones using this approach (6). Thus, it is possible to reliably differentiate uric acid stones from other types of renal calculi and to plan treatment accordingly without extracting the stone. It is even possible to detect uric acid in gout tophi (7).
Differentiation of Tendons and Ligaments
Our initial experience has shown that tendons and ligaments have weak spectral properties, presumably due to the densely packed collagen. It is possible to identify thick tendons and ligaments in Dual Energy CT datasets and to display them separately, for example, to visualize the tendons of the wrist and identify ruptures. However, signal-to-noise ratio is not sufficient to depict thin ligaments; thus the clinical value of this application is limited.
1. Graser A, Johnson TR, Hecht EM, et al. Dual-energy CT in patients suspected of having renal masses: can virtual nonenhanced images replace true nonenhanced images? Radiology 2009; 252:433-440.
2. Thieme SF, Johnson TR, Lee C, et al. Dual-energy CT for the assessment of contrast material distribution in the pulmonary parenchyma. AJR Am J Roentgenol 2009; 193:144-149.
3. Thieme SF, Becker CR, Hacker M, Nikolaou K, Reiser MF, Johnson TRC. Dual Energy CT for the Assessment of Lung Perfusion – Correlation to Scintigraphy. Eur J Radiol 2008; 66.
4. Morhard D, Fink C, Graser A, Reiser MF, Becker C, Johnson TR. Cervical and cranial computed tomographic angiography with automated bone removal: dual energy computed tomography versus standard computed tomography. Invest Radiol 2009; 44:293-297.
5. Sommer WH, Johnson TR, Becker CR, et al. The value of dual-energy bone removal in maximum intensity projections of lower extremity computed tomography angiography. Invest Radiol 2009; 44:285-292.
6. Graser A, Johnson TR, Bader M, et al. Dual energy CT characterization of urinary calculi: initial in vitro and clinical experience. Invest Radiol 2008; 43:112-119.
7. Johnson TR, Weckbach S, Kellner H, Reiser MF, Becker CR. Clinical image: Dual-energy tomographic molecular imaging of gout. Arthritis Rheum 2007; 56:2809.computed