Available dual-energy technologies
Different technological implementations of DECT are commercially available and in clinical use. [Fig. 1] provides a schematic overview of available DECT concepts and technologies. While different terminologies for the several DECT platforms have been suggested and used in the literature, the Society for Body Computed Tomography and Magnetic Resonance (SBCTMR) recently provided systematic nomenclature to facilitate communication, which will be used throughout this article [6].
Fig. 1 Schematic overview of different CT technologies currently available, including conventional, dual-energy, and multi-energy CT
To understand the underlying technological concepts of DECT, it is important to acknowledge that X-rays as used in medical imaging refer to a spectrum of photons (or X-ray quanta) of different energies (unit: kiloelectron volt, keV) with the maximum being defined by the tube voltage (kVp). In this spectrum, the energies are not linearly distributed but follow a specific pattern that depends on the X-ray tube materials and other system-inherited characteristics, e. g., filters that are used. Alteration of the X-ray tube voltage will therefore result in a different X-ray spectrum, which is the underlying principle of emission-based DECT. While techniques such as scan-scan and rotate-rotate DECT are available from some vendors, they are severely limited by motion effects and temporal misregistration. The following technical implementations of DECT are commercially available and relevant to routine imaging [7]
[8]:
Dual-source DECT (dsDECT): Two tube detector pairs offset by 90* to each other allow for simultaneous acquisition of low- and high-energy attenuation spectra. The reconstructed images from both tubes can be fused to obtain a conventional CT image or used as input for the reconstruction of DECT results.
Rapid kVp switching DECT (rsDECT): Within a single rotation, the tube voltage is changed frequently in a succession of as short as 0.5 ms, enabling acquisition of low- and high-energy attenuation spectra. After angular correction, raw data can be fused to obtain a conventional CT image or be used to reconstruct DECT results.
Twin-beam DECT (tbDECT): A filter made from gold and tin is placed along the Z-axis (out-of-plane) to split the X-ray spectrum into a high-energy component and low-energy component that are read out separately by corresponding detector rows.
Dual-layer DECT (dlDECT): The only available detector-based DECT system includes a horizontally aligned detector that consists of two different scintillator materials with one being more prone to detection of low- and high-energy photons, respectively (from a single X-ray spectrum). Raw data can be processed aggregated or separately to obtain conventional images or DECT results.
Photon-counting CT (PCCT): These systems use a novel detector that allows for direct conversion of photons to energy (without the need for a scintillating layer). The detector, therefore, enables higher resolution of images as well as multi-energy separation. However, due to the novelty of this system, the body of literature is still comparably small.
DECT reconstructions used in the clinical routine
While each of the available DECT systems has its own advantages and disadvantages, all systems enable material decomposition for iodine and linear blending of low and high keV X-ray photon data.
Material decomposition exploits the fact that the attenuation of X-rays is dependent on their energy and the composition of the absorbing material. At material decomposition, the dependence of the photoelectric effect as well as Compton scattering, the two main X-ray interactions in the diagnostic energy range, on the atomic number and the physical density of a given material is modeled. This can be achieved by determining the material-specific attenuation coefficient as a linear combination of the attenuation of either two (i. e., two material decomposition) or three (i. e., three material decomposition) base materials in a given voxel [7]. While material decomposition is advantageous in many instances, it is subject to inherent limitations. First, materials with similar absorption characteristics show a “spectral overlap”, which may result in erroneous depiction of a confounding material in a material specific map (e. g., calcified structures in iodine maps). This spectral overlap is influenced by different factors such as image noise and the acquisition paradigm. Another limitation of material decomposition is that the presence of a confounding material in a volume of interest may lead to erroneous quantification of the material of interest, since the modeling assumptions are violated [9].
As iodine images selectively depict the iodine-associated component of X-ray attenuation, they allow for absolute quantification of iodine in milligrams per milliliter [10]. The very same information can be subtracted from the conventional image, hence making it possible to obtain virtual unenhanced (VUE) images that closely represent quantitative and qualitative characteristics of a truly unenhanced acquisition [11]. A different way of visualizing iodine content is by reconstructing fused images (similar to well-known PET/CT images): Here, the functional information (i. e., iodine content) is color-coded and superimposed on top of morphological/anatomical reconstructions (see the section on oncology applications). Material decomposition is also available for uric acid as used in the imaging of gout and urinary stones (see the corresponding sections below).
For virtual monoenergetic images (VMIs), linear bending of low- and high-energy information is conducted or extrapolated. VMIs are considered to approximate attenuation characteristics of images acquired with a true monoenergetic X-ray and are therefore indicated by the corresponding, targeted keV level. VMI are available from as low as 40 keV up to 140–200 keV (depending on the DECT technology). Generally, VMIs can be classified according to their energy spectrum as low-energy VMIs (40–60 keV, VMI_low) that show a greater soft-tissue and iodine contrast, and high-energy VMIs (> 90 keV, VMI_high) that reduce beam hardening. VMIs in the mid-range (e. g., between 65 and 70 keV) have been suggested as a working equivalent of polychromatic images at 120 kVp [12]
[13].
Other more investigational reconstructions include virtual non-calcium images, electron density images, and Zeff images. While the latter two are thought to be useful for radiation therapy planning, virtual non-calcium images subtract all calcium-associated attenuation from the image (analogously to VUE for iodine) and therefore might prove beneficial for depicting bone marrow edema or cellular infiltration in oncologic diseases.
Clinical applications
The following section will include applications of DECT-derived images for different body regions and indications. At the end of each subsection, a short summary of feasible clinical applications is provided.
Neuroradiology
Detection of intracranial hemorrhage and identification of a distortion of grey-white matter differentiation are naturally among the key objectives of an unenhanced CT scan of the head. However, the latter is often found to be challenging as differences between grey and white matter are in the order of 10 HU. This in turn justifies and requires a relatively high radiation dose to minimize image noise. In this instance, low-energy VMIs have been reported to be instrumental, as they allow for an improved contrast between grey and white matter ([Fig. 2]). Most previous publications investigating this topic concluded that virtual keV levels in the range of 50–65 keV would be optimal for enhanced grey-white matter differentiation [14]
[15]
[16]. Using such image reconstructions, a radiation dose reduction of up to 20 % appears justifiable without image quality impairment [16]. In this context, the following thoughts require consideration: A) Some technological DECT implementations, particularly earlier generations, demonstrate a notable increase in image noise with photon energies decreasing towards 40 keV. A balance has to be determined that ensures the increase in contrast is not compromised by an accompanying increase in noise. B) When moving to a lower keV, blooming of calcific structures is a well observed phenomenon. This possibly impairs assessment of the subcalvarial space and hence requires careful consideration. While studies suggested both improvements in quantitative image metrics and image quality in unremarkable cranial CT examinations, some studies also denoted improved detection and delineation of edematous and/or hemorrhagic areas [17]
[18]
[19]. Furthermore, low keV VMIs can improve vascular assessment, e. g., in the case of suspected stroke. This is discussed in detail in the section “cardiovascular imaging”.
Fig. 2 Image examples showing improved gray-white matter differentiation (left), increased contrast and conspicuity of intracerebral hemorrhage (center), and better delineation of cerebral infarction (right) in dual-energy CT-derived virtual monoenergetic images (VMI) at different energy levels compared to conventional images (CI).
Another common challenge in cranial CT examinations is the differentiation between blood and iodine after endovascular treatment of ischemic stroke or aneurysm. For this purpose, VUE images have been reported to be helpful as they eliminate iodine-associated attenuation. Therefore, if hyperattenuating material remains in these images within the brain parenchyma space, it is likely related to blood [20]
[21] as opposed to postinterventional contrast material accumulation. A meta-analysis including 204 patients from nine studies on that topic concluded that DECT had a sensitivity and specificity for differentiation between hemorrhage and contrast media or small calcifications of 96 % and 98 %, respectively [22].
Besides the above-mentioned clinical applications of DECT for neuroradiology, a more generic use that will be covered extensively in the “Musculoskeletal Imaging” section is the reduction of artifacts. In the context of neuroradiology, DECT-derived metal artifact reduction has been suggested to improve visualization in patients who underwent clipping or coiling of intracranial aneurysms. High-energy VMIs facilitate the reduction of artifacts. However, in the case of vascular assessment, a balance between the accompanying decline in intravascular contrast and artifact reduction is key. Therefore, in this specific case, the suggested optimal keV levels are not as high as those in musculoskeletal applications and mostly range between 100 and 120 keV [23]
[24]
[25]. Other publications focusing on the assessment of the surrounding brain parenchyma as opposed to vessels suggested higher keV levels accordingly [26].
Key clinical applications: Neuroradiology
-
Improved grey-white matter differentiation in low-keV VMIs (50–65 keV) with potential for radiation dose reduction
-
Improved visualization of hypodense (e. g., ischemia) and hyperdense (e. g., hemorrhage) brain lesions
-
Differentiation between intracranial hemorrhage and contrast media
-
Reduction of artifacts in patients who underwent intracranial coiling and/or clipping (optimal keV levels need to be adjusted for assessment of the surrounding vessels (lower) or the parenchyma (higher))
Musculoskeletal imaging
CT is one of the key modalities in acute trauma and fracture imaging. The DECT use case in musculoskeletal imaging with the greatest clinical relevance and impact, for which there is a large body of evidence, is the use of high keV irradiation VMIs to reduce artifacts associated with orthopedic hardware. Moving towards higher energies in VMIs decreases the probability for complete absorption of a photon and the risk for an unsampled or undersampled region surrounding any implant resulting in hypodense streaks. The value of this approach has been investigated in different use cases [27]
[28]. Research data suggests a benefit from VMIs with regards to artifacts caused by nearly all types of implants ([Fig. 3a–c]). Most groups suggest implant-specific adjustments of keV levels in order to balance the degree of artifact reduction versus the loss of soft-tissue contrast encountered in high keV imaging [27]
[28].
Fig. 3 a Image example depicting artifact reduction in a patient with orthopedic hardware in the lower lumbar spine by means of virtual monoenergetic images (VMI) at 200 keV. Reduction of hypodense streak artifacts with improvement of the paravertebral compartments can be clearly seen. b Artifact reduction in a patient with plate osteosynthesis following traumatic fracture of the proximal humerus. Virtual monoenergetic images (VMI) at 200 keV effectively reduce artifacts, allowing for an improved assessment of the remaining fracture lines as well as the osseous tissue surrounding the fixating screws. c Different approaches to artifact reduction in a patient with right-sided, total hip replacement. The conventional image depicts pronounced hyperattenuating artifacts surrounding the implant and hypoattenuating artifacts superimposing the organs of the lower pelvis (left side). Virtual monoenergetic images (VMI) at 200 keV show marked reduction of artifacts with improved periprosthetic as well as pelvic assessment (center image). The combination of VMI with an artifact reduction algorithm (OMAR) yields the best possible reduction of artifacts and adequate visualization of the acetabular bone as well as the lower pelvis (right side).
The effectiveness of VMI-enabled artifact reduction appears limited in very dense materials (e. g., in hip protheses or endovascular coils). Here, a particular benefit has been shown for combining high-energy VMIs and dedicated iterative reconstruction algorithms for metal artifact reduction (i. e., MAR; [Fig. 3c]) [29]. This combination currently represents the strongest means for artifact reduction in DECT imaging (together with optimized imaging protocols).
Another well-established application of DECT in musculoskeletal imaging employs material-specific maps for uric acid in suspected (or clinically proven) gout arthritis [30]
[31]
[32]. These maps are typically evaluated in a fused manner that allows for visualization of uric acid deposits. However, care has to be taken as tendon sheaths and/or cartilage may mimic the attenuation characteristics of uric acid and, therefore, are indicated as uric acid on such reconstructions ([Fig. 4]).
Fig. 4 A Uric acid overlay images showing gout adjacent to the tarsometatarsal joints (arrow) and the proximal interphalangeal joint of the second toe. B Calcifications of the plantar aponeurosis, mimicking uric acid deposits.
Further suggested applications include an improvement in the imaging of vertebral disc herniation [33] as well as the detection of bone bruise on CT imaging [34]
[35]
[36] (the latter by means of virtual non-calcium images). However, according to the opinion of the authors of this article, these applications are not yet sufficiently validated to allow broad clinical application outside of scientific studies and/or experienced centers.
Key clinical applications: musculoskeletal imaging
-
Artifact reduction in patients with orthopedic implants using high-keV virtual monoenergetic images exclusively or in combination with dedicated metal artifact-reduction algorithms
-
DECT-derived uric acid overlay images for the depiction of urate deposition in patients with gout
Cardiovascular imaging
Following its capabilities of increasing iodine contrast by means of low keV VMI and subtracting iodine-related attenuation components, DECT has been investigated for various clinical use cases in the field of vascular imaging. For pulmonary embolism, DECT-derived VMI have been shown to yield superior contrast and increase detection, diagnostic certainty, and delineation of thromboembolism [37]
[38]
[39]. Those reconstructions are particularly helpful for salvaging the diagnostic assessability of examinations with suboptimal contrast within the pulmonary arteries [40] ([Fig. 5]). Besides low-keV VMIs yielding superior vessel contrast, iodine maps can be used for the assessment of pulmonary embolism by depicting areas of hypoperfusion within the lung parenchyma. This can be of use both in the acute setting as well as in patients with suspected chronic thromboembolic pulmonary hypertension [41]
[42].
Fig. 5 Patient with suspected pulmonary embolism. Conventional image shows severely impacted visualization due to suboptimal contrast of the pulmonary arteries. Virtual monoenergetic image (VMI) at 40 keV (right) salvages diagnostic quality by increasing the iodine contrast in the pulmonary arteries, allowing confident delineation of pulmonary emboli.
One particular use case for DECT in vascular imaging that has been evaluated in the literature is the assessment of aortic endografts. Here, iodine images and VMIs at low energies yielded improved detection of endoleaks depicted as contrast media leakage in the aneurysm sac [43]
[44]. Moreover, VUE images showed high sensitivity and specificity for endoleaks in aneurysm graft assessment when used instead of true unenhanced images, enabling differentiation between contrast media and hyper-attenuation caused by other causes e. g., calcifications or hemorrhagic deposits. Chandarana et al. suggested that VUE and 80 kVp acquisitions from a dual-source scanner derived from one 60-second phase might be sufficient for endovascular aneurysm repair assessment [45]. Another important challenge for vascular imaging is the differentiation of contrast material from hemorrhage, e. g., in the assessment of vascular hematoma, for which VUE images may be helpful [46].
The capabilities of DECT to yield VUE and virtual high-contrast (i. e., low-energy virtual monoenergetic) images has been suggested to be combined in a “virtual triphasic” acquisition derived from one portal venous phase image, with significant potential for radiation dose reduction due to the possible elimination of two acquisitions [47].
One potential application of DECT in cardiac imaging that has been investigated in various studies is calcium scoring based on VUE images derived from CCTA, which, if accurate, would allow for omission of an unenhanced acquisition and therefore a significantly lower radiation dose. Whereas most studies described a good correlation between coronary artery calcium scores, they also outlined a systematic underestimation of those metrics in VUE [48]
[49]
[50]
[51], which can be attributed to the spectral overlap between calcium and iodine, resulting in an erroneous subtraction of calcium-containing voxels in VUE images. As there is no validated model taking into account this underestimation for routine clinical use, further investigation in this regard seems necessary before routine clinical application can be implemented.
Key clinical applications: cardiovascular imaging
-
Improved assessment of pulmonary embolism in low-keV VMIs
-
Restoring diagnostic image quality in angiographic phase examinations with suboptimal contrast using low-keV VMIs
-
Assessment of contrast media leakage (e. g., in endograft assessment) and vascular wall hematoma in low keV/iodine images and VUE images, respectively
Oncologic and organ-specific imaging
Liver
Accurate assessment of the liver parenchyma is paramount to determine the presence or absence of liver metastases and safeguard optimal therapeutic concepts for cancer patients. Due to the limited soft-tissue contrast on CT, the detection of small lesions with subtle enhancement differences compared to the surrounding parenchyma can be hampered. DECT-derived VMIs at low energy levels facilitate improved conspicuity of liver lesions. For hyperattenuating liver lesions, this is achieved by increasing the attenuation of the lesion itself, thereby improving the contrast-to-noise ratio and its conspicuity and detectability [52]
[53]
[54]
[55], as schematically depicted in [Fig. 6]. For hypoattenuating lesions, a better depiction is attained by increasing the attenuation of the surrounding liver parenchyma [56]
[57]. In summary, low-keV virtual monoenergetic images sent to the PACS as standard reconstructions in oncologic patients are an easy-to-use screening tool for small, subtle, hypo- and hyperattenuating liver lesions.
Fig. 6 Schematic diagram showing increased contrast and conspicuity of hypo- and hyperattenuating liver lesions attained in low keV virtual monoenergetic images. Improved delineation of hypoattenuating lesions is achieved by increased contrast of the surrounding parenchyma, whereas delineation of hyperattenuating lesions is improved by increased attenuation of the lesion itself.
Small, intermediate lesions of the liver, which are often called “too small to characterize”, present another diagnostic challenge in regard to CT liver imaging. DECT-derived iodine images may help to increase diagnostic confidence when diagnosing such lesions, for example by ruling out any iodine uptake in iodine images. One study found that the classification of such small, intermediate hypoattenuating liver lesions could be improved significantly with the use of iodine images and an iodine-based threshold as compared to conventional images [58]. However, large-scale validation of this quantitative application seems necessary before broad clinical application can be implemented. The same applies to studies that suggested DECT-enabled differentiation of liver lesions, e. g., between small HCCs and metastases based on iodine quantification, which has been investigated only in small cohorts [59]
[60].
Kidneys
Renal masses with non-cystic attenuation of equal or greater than 20 HU on contrast-enhanced abdominal CT are a common incidental finding [61]. One study suggested that in > 50 % of adults aged 50 or older, imaging would yield at least one incidental renal mass [62]. The differential diagnoses for such masses include hemorrhagic or proteinaceous cysts as well as solid-enhancing masses. Differentiation between these lesions in monophasic, portal venous phase single-energy CT is hampered by the lack of information on the baseline unenhanced attenuation enabling assessment of lesion enhancement. Consequently, many patients diagnosed with such incidental lesions are recommended to undergo additional multiphasic renal protocol CT or MRI examination. By means of material decomposition, DECT allows differentiation between the attenuation component derived from iodinated contrast material and other non-iodine-related tissue or material components such as protein or blood. This has resulted in a large number of studies that aimed to assess the utility of DECT in characterizing renal lesions, which investigated both the use of virtual unenhanced and iodine images. A meta-analysis of five studies with a total patient number of 367 revealed a sensitivity and specificity of 96.6 and 95.1 %, respectively, for iodine images with respect to determining lesion enhancement [63]. In another study, Meyer et al. showed that virtual unenhanced images allow for accurate renal lesion characterization, albeit with a lower specificity compared to true unenhanced images [64]. Accordingly, Cao et al. recently found that virtual enhancement calculated from the portal venous phase and virtual unenhanced images correctly identified all enhancing lesions within their study cohort, yet noted that in some cases, virtual unenhanced images diverged from true unenhanced image attenuation with regard to the evaluation of cystic lesions [65]. In the clinical routine, virtual unenhanced and iodine images can be used synergistically to rule out enhancement in ambiguous renal lesions. In this instance, previously investigated, scanner-dependent lower limits of detection and quantification of iodine should be consulted when aiming to assess the presence of iodine enhancement [66]. We suggest that the current body of evidence supports using DECT for determining or ruling out enhancement of hyperattenuating renal lesions. More advanced quantitative applications such as differentiation of different subtypes of RCCs have been investigated [67]
[68]. However, the corresponding thresholds have not been validated and are prone to a certain variability of iodine quantification [69]
[70].
Another, and one of the earliest use cases of DECT in renal imaging is the characterization of renal calculi. Significant evidence is available that indicates that identification of uric acid concrements is possible by means of material-specific maps for uric acid [71]
[72]
[73]
[74]. Furthermore, several groups investigated whether stone composition analysis is possible beyond this. However, the body of literature is too small and furthermore too scanner- and protocol-specific to be able to consider this a generally valid method in this context [75]
[76].
Adrenal glands
Adrenal nodules are one of the most common incidental findings in abdominal CT with a reported prevalence of up to 7 % [77]. In the overall population, the majority of these adrenal nodules are known to represent benign adrenal adenomas. However, in cancer patients, there is an increased risk that these lesions represent metastatic spread to the adrenal glands. Lipid-rich adenomas are characterized by the presence of macroscopic fat. This can be determined by an unenhanced CT attenuation threshold of 10 HU, which has been suggested to yield a sensitivity/specificity of 71 %/98 % [78], or by a signal loss on chemical shift MRI. It has been described that overall, around 70 % of adenomas can be determined as lipid-rich following an unenhanced attenuation of < 10 HU [79]
[80]
[81]
[82]. However, in most instances, adrenal incidentalomas are detected in CT examinations not tailored for such an assessment due to a lack of unenhanced or delayed phase image acquisitions, based on radiation protection considerations. Consequently, definitive characterization and exclusion of metastatic spread would require additional imaging such as dedicated CT for adrenal assessment comprising an unenhanced and delayed phase, or MRI with in-and-out-of-phase imaging. DECT-derived VUE and iodine images have been extensively investigated scientifically for one-stop-shop characterization of incidental adrenal nodules in portal venous phase abdominal CT examinations [83]
[84]
[85]
[86]
[87]
[88]
[89]. As discussed before, VUE images allow for estimation of the true unenhanced image attenuation. Therefore, a VUE attenuation of < 10 HU calculated from portal venous phase images is highly indicative of lipid-rich adrenal adenoma. One problem that has been addressed in the literature is that virtual unenhanced image attenuation shows a tendency towards overestimation of true unenhanced image attenuation in adrenal adenomas [89]
[90]
[91]
[92], limiting the sensitivity in determining their lipid-rich nature. Different ways of mitigating this issue have been suggested, most notably increasing the 10 HU threshold. Another means of addressing this issue has been suggested, i. e., including iodine measurements in a multiparametric approach, which yielded promising results. However, these monocentric, retrospective results have not been validated yet [89]. As virtual unenhanced attenuation is known to show intra-patient variation between different DECT platforms, state-of-the-art, device-specific data should be consulted when using quantitative DECT measurements as stated above for the characterization of incidental adrenal nodules [93]. [Fig. 7] illustrates an example of adrenal differentiation using VUE images.
Fig. 7 Virtual unenhanced images derived from dual-energy CT for differentiation between adrenal adenoma (upper row) and adrenal metastasis (lower row).
Metastasis detection
With its large overall volume and high physical density, the skeletal muscle is notoriously hard to assess on conventional CT, qualifying it as one of the “blind spots” of oncologic staging and follow-up CT. Due to several underlying factors, the human skeletal muscle is relatively resistant to hematogenous metastatic spread of oncologic diseases. However, for some malignant diseases such as malignant melanoma, a higher probability of skeletal muscle metastasis has been described [94]. In oncologic imaging, the detection of such distant metastases is important since the new appearance of metastatic lesions may indicate the necessity for the adjustment of treatment concepts. Several studies have described an improved sensitivity for skeletal muscle metastases in DECT-derived reconstructions highlighting iodine contrast, such as low keV virtual monoenergetic images and iodine overlay images, in which the iodine content is color-coded and merged with underlying grey-scale conventional images [95]
[96].
The underlying rationale is that images highlighting the iodine-related attenuation allow for the differentiation of iodine-related attenuation components of enhancing metastatic lesions vs. physical density-related attenuation components of circumjacent muscle, which may be almost indistinguishable on conventional images ([Fig. 8]). Therefore, these images may qualify as screening tools for patients with oncologic diseases or disease stages, respectively, that yield a higher pre-test probability for metastatic spread to the muscle. Finally, in a prospective evaluation of patients with occult cancer, it was described that spectral reconstructions may improve the confidence of radiologists in characterizing lesions, thereby making it possible to minimize correlative imaging [97].
Fig. 8 Simplified schematic illustration of attenuation components of skeletal muscle metastases and surrounding muscle parenchyma including an exemplary case of skeletal muscle metastasis on conventional and iodine overlay images in a patient with melanoma.
Other applications
The substantially increased attenuation of iodinated contrast material in low keV virtual monoenergetic reconstructions can not only be used to increase conspicuity and detectability of organ-specific lesions as described above, but also to lower the overall amount of contrast media that has to be applied for attaining sufficient visualization ([Fig. 9]). In a study by Nagayama et al., it was shown that VMIs from 40 to 55 keV allowed for a reduction of contrast media dose by 50 % in multiphase liver CT [98]. In another study, VMIs at 40 keV were reported to yield organ and vessel assessment comparable to a full-dose protocol in portal venous phase abdominal CT at a 50 % lower iodine concentration load [99]. In regard to aortic angiography with 50 % contrast material reduction, DECT-derived VMIs ranging from 40 to 60 keV were reported to yield similar image quality as normal iodine contrast material doses [100]. Lastly, Agrawal et al. reported a significantly higher attenuation and CNR in low-energy VMI CTA with a reduction of contrast media to 24 g/l compared to standard-dose CTA (33 g/l) [101]. Based on the above-mentioned evidence, a minimum volume of 50 ml contrast media (depending on the specific contrast media administration protocol (i. e., bolus length)) in combination with low keV VMI appears to be a valid strategy in patients at an increased risk for contrast media-associated nephropathy or other dose-dependent adverse events.
Fig. 9 Cross-sectional image of a portal venous phase CT scan of the upper abdomen with a contrast media reduction of 50 %. The left image represents the conventional image, whereas the right image with only poor contrast enhancement depicts the corresponding virtual monoenergetic image at 40 keV, restoring adequate tissue contrast.
Key clinical applications: Oncologic and organ-specific imaging
-
Liver:
-
Kidneys:
-
Adrenals: Identification of incidental adenoma with virtual unenhanced images (consult literature for scanner-specific, adjusted thresholds)
-
Detection of skeletal muscle metastases in iodine overlay images in patients with increased pretest probability
-
Contrast media reduction with low-keV virtual monoenergetic images to antagonize iodine contrast deterioration
