X-Ray Generation and Basics of Spectral Computed Tomography¹

Computed tomography (CT) relies on the passage and attenuation of X-ray photons to create an image. X-ray production begins after an electrical potential (kilovolt peak [kVp]) propels electrons through an X-ray tube, where they interact with a target anode. X-ray photons are then emitted with a spectrum of energies. The spectrum of X-ray energies is directly related to the original kVp applied. This conventional form of CT is termed polychromatic.

Greater kVp leads to increased photon intensity and therefore improved image quality, but this must be balanced against kVp's exponential relationship to patient radiation dose. Cardiac CT is usually set at 80-120 kVp.

After a spectrum of X-rays are produced, they are passed through the body, where they are attenuated before being processed into an image. Varying degrees of attenuation lead to varying degrees of pixel intensity, expressed as Hounsfield units (HUs). The HUs are not dependent solely on material-specific characteristics. That is, different materials can have a similar appearance on CT at a particular energy. For example, calcium and iodinated contrast have similar attenuation at 120 kVp, making them sometimes indistinguishable. However, when exposed to a lower-energy X-ray beam, iodinated contrast exhibits a higher attenuation does than calcium.

Multienergy computed tomography (MECT; also known as dual-energy computed tomography or spectral computed tomography) takes advantage of the polychromatic X-ray energies and their varying degrees of photon interactions. MECT creates an image through the scope of particular kVp, allowing for tissue characterization and material decomposition. On postprocessing software, one can highlight or exclude materials on the basis of their spectral properties, therefore enhancing the diagnostic capabilities of an image.

Types of Spectral Computed Tomography Systems¹

There are four commercially available systems that allow for MECT image generation. They differ in the way they emit X-ray photons (i.e., in their source) and/or in their detection.

1. Rapid kVP switching. As the CT gantry rotates, the X-ray source rapidly switches between high-energy and low-energy X-rays in <1 msec. Classically, the high energy is 140 kVp and the low energy is 80 kVp.
2. kVp switching between gantry rotation. A full rotation with image acquisition is obtained at one energy before then rotating again for full acquisition at a second energy.
3. Dual-source scanning. Two X-ray sources set at different energies are aligned at 90 degrees from one another.
4. Dual-layer detector. As the X-ray source emits a wide spectrum of energies, two detectors are layered on top of each other, with one detecting lower-energy photons and the deeper detector for higher-energy photons.

Spectral Computed Tomography's Potential in Cardiac Imaging

Figure 1: Summary of the Potential CV Applications of Spectral CT

1. Virtual noncontrast (VNC) imaging. VNC allows for the identification and removal of iodinated contrast, virtually creating a noncontrast image. This approach can obviate the need for a separate noncontrast image for coronary artery calcification (CAC) or aortic valve calcium (AVC) scoring. Notably, as the Agatston score was derived on a noncontrast 120 kVp acquisition, the VNC, CAC, or AVC obtained from MECT needs to be corrected using a proportionality constant. However, data suggest an excellent correlation between VNC, CAC, AVC, and Agatston scoring for coronary and aortic calcium quantification.^2,3
2. Calcium removal. Blooming is a commonly encountered artifact in coronary computed tomography angiography (CTA), in which dense calcium precludes accurate luminal assessment. Blooming may lead to a nondiagnostic study or an overestimation of stenosis. MECT can identify and correct for the attenuation produced by calcium, allowing for improved contrast-enhanced luminal assessment.⁴
3. Estimation of extracellular volume (ECV). ECV is a useful marker of interstitial expansion, such as in edema or fibrosis, and is traditionally quantified via cardiac magnetic resonance imaging (MRI) using T1 mapping. CT-derived ECV has been shown to correlate well with ECV measured by MRI.⁵ The conventional HU-based subtraction method requires an initial noncontrast scan and a subsequent delayed scan 3-10 min after initial injection. However, MECT permits the use of just the contrast scan to directly quantify myocardial iodine content for an ECV estimation or an assessment of late iodine enhancement.⁶
4. Monoenergetic imaging (MI) to minimize iodinated contrast dose. MI constructs images on the basis of a particular kVp. As iodine contrast is capable of attenuating low-energy photons, MI can be used to enhance the contrast-to-noise ratio. Clinically, this approach allows for the use of lower contrast volumes. A prospective study on pre–transcatheter aortic valve implantation CTA had findings of improved image quality when using 40 kVp MI even with only 25 mL of iodinated contrast.⁷ Furthermore, MI can preserve study quality in the case of unforeseen issues with injection (e.g., poor contrast timing, partial extravasation; this is only feasible with detector-based MECT or with preselection in other systems).
5. MI to minimize metallic artifact. Metallic artifacts are caused primarily by beam hardening, which is the preferential attenuation of lower-energy photons. This approach leads to a streaking effect across the image, which can obscure surrounding structures or compromise luminal evaluation in the setting of metallic stents. This issue is common in imaging with implantable devices, such as pacemakers, defibrillators, and left ventricular assist devices. MI can prioritize image generation with high-energy photons to minimize metallic streaks and, at the same time, provide better luminal attenuation using a lower MI reconstruction, improving the visualization of stented coronary segments.⁸
6. Myocardial perfusion imaging. Cardiac computed tomography perfusion (CTP) assesses for the presence of intramyocardial iodine. Hypoperfusion leads to less myocardial iodine; therefore, ischemic/infarcted segments appear darker. CTP is susceptible to false-positive results, particularly in the basal-inferolateral wall, where the adjacent contrast-enhanced aorta and spine lead to beam hardening and myocardial hypoattenuation. MECT iodine mapping and MI with higher kVp can reduce beam hardening, improving the accuracy of CTP.⁹
7. Detection of left atrial appendage (LAA) thrombus. A filling defect in the LAA can be confirmed to represent thrombus if there is a persistent defect on delayed imaging. However, tissue characterization with MECT can be used to enhance the specificity for thrombus, using a single contrast-enhanced scan.¹⁰

In summary, MECT takes advantage of the differential attenuation observed across the spectrum of X-ray energies. This technology allows for material decomposition, the creation of iodine maps, and image generation through the lens of particular kVp values. There are several commercially available MECT systems in use. Despite showing promising technical features, further research is needed to clarify the added value of spectral imaging in different clinical scenarios.

References

1. Greffier J, Villani N, Defez D, et al. Spectral CT imaging: technical principles of dual-energy CT and multi-energy photon-counting CT. Diagn Interv Imaging 2023;104:167-77.
2. Lorenzatti D, Piña P, Daich J, et al. Diagnostic accuracy of virtual non-contrast CT for aortic valve stenosis severity evaluation. J Cardiovasc Comput Tomogr 2024;18:50-5.
3. Perez-Cervera J, Arce J, Fattouh M, et al. Influence of BMI on virtual coronary artery calcium scoring. Int J Cardiovasc Imaging 2023;39:863-72.
4. Li Z, Leng S, Halaweish AF, et al. Overcoming calcium blooming and improving the quantification accuracy of percent area luminal stenosis by material decomposition of multi-energy computed tomography datasets. J Med Imaging (Bellingham) 2020;7:[ePub ahead of print].
5. Han D, Lin A, Kuronuma K, et al. Cardiac computed tomography for quantification of myocardial extracellular volume fraction: a systematic review and meta-analysis. JACC Cardiovasc Imaging 2023;16:1306-17.
6. Oda S, Emoto T, Nakaura T, et al. Myocardial late iodine enhancement and extracellular volume quantification with dual-layer spectral detector dual-energy cardiac CT. Radiol Cardiothorac Imaging 2019;1:[ePub ahead of print].
7. Cavallo AU, Patterson AJ, Thomas R, et al. Low dose contrast CT for transcatheter aortic valve replacement assessment: results from the prospective SPECTACULAR study (spectral CT assessment prior to TAVR). J Cardiovasc Comput Tomogr 2020;14:68-74.
8. Selles M, van Osch JAC, Maas M, et al. Advances in metal artifact reduction in CT images: a review of traditional and novel metal artifact reduction techniques. Eur J Radiol 2024;170:[ePub ahead of print].
9. Kay FU. Dual-energy CT and coronary imaging. Cardiovasc Diagn Ther 2020;10:1090-107.
10. Li W, Liu M, Yu F, et al. Detection of left atrial appendage thrombus by dual-energy computed tomography-derived imaging biomarkers in patients with atrial fibrillation. Front Cardiovasc Med 2022;9:[ePub ahead of print].