dual-energy ct of the abdomen

Dual-energy CT of the abdomen

Desiree E. Morgan

Department of Radiology, University of Alabama at Birmingham, JTN452 619 South 19th Street, Birmingham, AL 35249, USA

Abstract

Although conceived of in the 1970s, practical use of dual-energy CT in the clinical setting did not come to fruitionuntil 2006, and since that time an ever expandingexploration of the technology has been underway. Thisarticle will discuss technical aspects of the two commer-cially available CT scanners, review the recent literature,and provide an organ-based description of abdominaldual-energy CT applications for the practicing radiolo-gist.

Key words: Dual-energy CT—Abdomen—Dual-source—Rapid-switching—Single-source—Virtualunenhanced

Over the past 6 years the use of dual-energy CT has in-creased steadily and the number of publications dra-matically. Familiarity with the technology and anunderstanding of the capabilities and challenges associ-ated with the types of scanners presently available forclinical use may help radiologists to enhance their prac-tice. From an organ-based approach, specific opportu-nities to improve diagnostic performance above standardpolychromatic beam multi detector CT include: for thepancreas, identification of early-stage tumors or im-proved characterization of cystic lesions; for the liver,robust quantification of hepatic fat and iron, as well asmore accurate nodule detection and characterization fororgan allocation; for the kidney, characterization ofchemical components of renal stones, and identificationof iodine in renal neoplasms, even those with only min-imal enhancement, on a single post-contrast CT exami-nation; for adrenal glands, identification of benign lipid-rich adenomas on a single post-contrast acquisition. Inaddition, more global opportunities to reduce imageartifacts, especially those due to metal or beam harden-ing, to reduce radiation dose by eliminating conventionalunenhanced image acquisition, and to reduce IV iodin-

ated contrast dose for routine abdominal scanning maybe possible. The additional information available withdual-energy technique includes opportunities to improveassessment of early therapeutic response to novel onco-logic agents, where anatomic tumor shrinkage is a lateeffect, through identification of material density changesin tissues. As dual-energy technologies take CT beyondanatomic imaging, the additional information availableshould be achieved at a radiation neutral cost. Thisarticle will provide the reader with an updated generalreview of abdominal dual-energy CT technology andapplications, with case illustrations focusing on spectralor rapid-switching dual-energy methods.

Technology-scanners

There are two types of commercially available dual-en-ergy scanners presently available in the United States.The dual-source dual-energy CT scanner (dsDECT)(Definition FLASH Siemens Medical Solutions, Erlan-gen, Germany) has two approximately 90� offset tubesthat generate separate low (80 or 100 kVp) and high(140 kVp) energy beams which produce two separateimage data sets that are then combined to create materialdensity and blended images in ‘‘image space’’. Thesetubes have two different fields of view (FOV), the largerbeing 50 cm and the smaller tube initially being limitedto 25-cm coverage. This smaller second tube FOV con-straint limited applications in larger patients and re-quired careful patient positioning on the part of CTtechnologists at sites that used the first generationdsDECT scanners; however, the second generationinstrument now has 33 cm FOV dual-energy coverage,an improvement which has led to wider applicability ofdsDECT in practice [1]. A tin-filter added to the 140 kVpbeam is used to further separate the low and high energyspectra [2]. The rapid kilovoltage switching dual-energyCT scanner (rsDECT) (General Electric Healthcare,Waukesha, WI) uses a single rapidly switching tube toacquire near simultaneous 140 and 80 kVp datasets usinga single fast response detector. This system acquires dual-energy image over the entire 50 cm FOV. The image datais used to generate material density images and simulatedCorrespondence to: Desiree E. Morgan; email: [email protected]

ª Springer Science+Business Media New York 2013

Published online: 26 September 2013AbdominalImaging

Abdom Imaging (2014) 39:108–134

DOI: 10.1007/s00261-013-0033-5

monoenergetic images in ‘‘projection space’’. Typically,70 or 78 keV images are generated and used for diag-nostic interpretation, and unlike dsDECT, separate 80and 140 kVp images are not created. The simulatedmonoenergetic images are available over a range ofenergies from 40 to 140 keV; clinical utility of viewingthe images at different energies will be explained in theorgan specific sections to follow. As opposed to kVp,which defines the upper limit X-ray energy for a poly-chromatic X-ray spectra, the keV specifies the protonenergy for a monochromatic X-ray source.

Other dual-energy CT approaches not discussed inthis article include the use of a single-tube source with adual-layer detector or photon counting detector, neitherpresently available for clinical use, or the use of twoconsecutive standard single-energy CT (SECT) scansacquired at two different tube potentials and then post-processed to derive dual-energy information. Both ofthese methods have been referred to as single-sourceDECT, as has the rapid-switching or rsDECT describedabove. Therefore, for the purposes of this article and tobe as specific as possible when discussing the technology,

Fig. 1. 64-year-old woman with pancreatic endocrine neo-plasm, pancreatic parenchymal phase rsDECT acquisition.A 50 keV, B 70 keV, C 90 keV, D 120 keV. The overallattenuation within the hyperenhancing tumor replacing the

entire pancreas increases at the lower keVs. Note that thewindow and level have been kept constant on all images forcomparison of change in attenuation due solely to the viewingenergy level alteration.

D. E. Morgan: Dual-energy CT of the abdomen 109

the term single-source dual-energy CT or ssDECT willnot be utilized.

Technology-types of imagesgenerated

Dual-energy CT scanners are capable of making twofundamentally different kinds of images. One type ofimage is the material density image, sometimes referredto as material-specific image. Because linear attenuationcoefficients obtained at different X-ray energies areunique for a given element, such as calcium, iodine,gold, gadolinium, or a substance such as fat, blood,mucin, etc, the change in attenuation between the twoenergy spectra used for DECT can be used to discrimi-nate the materials. This computational process whichdetermines the amount of a substance within each imagevoxel is used to produce clinically relevant presentationsof the data such as iodine images or overlays, uric acidmaps, or a virtual unenhanced image, sometimes referredto as virtual noncontrast image. With dsDECT, thisprocess is a three-point material decomposition where itis assumed that every voxel in the abdomen is composedof soft tissue, iodine, and fat, and a post-processingalgorithm generates a map that encodes the iodine dis-tribution in each voxel, then subtracts it from the image.With rsDECT, this process uses material decomposition

basis pairs of water(–iodine) and iodine(–water) tocreate the virtual unenhanced and iodine materialimages. On the rsDECT workstation, the same materialdecomposition basis pair process can evaluate othersubstances, such as calcium(–iodine) and iodine(–cal-cium), or fat(–iodine) and iodine(–fat); any material forwhich a NIST (National Institute of Standards andTechnology) attenuation curve is available (gadolinium,gold, iron, blood, mucin, etc) can be installed into thesystem and then the material can be rapidly evaluatedquantitatively on the images.

The other type of image created is the routine diag-nostic image which, to a practicing radiologist, simulatesa conventional single-energy polychromatic beam CTimage. On the dual-source system, this image is gener-ated by combining image data from the low and highkVp sources in ‘‘image space’’, such that separate 80 and140 kVp image sets plus the blended or weighted imageare available for diagnostic viewing. It is possible on thededicated dual-energy workstation of this system tochange the relative percent contribution of the low andhigh energy image data from 30/70%, respectively, to50/50% using a slider bar [3], or to have non-linearblending. From a practice standpoint, the 80, 140 kVp,and blended image sets are sent to PACS and used fordiagnosis, with additional material density image setsdefined per clinical indication. On the rsDECT system,

Fig. 2. 52-year-old man with pancreatic adenocarcinomaand metallic biliary duct stent, pancreatic parenchymal phasersDECT acquisition. Note that the appearance of the artifact

from the stent at lower energies is lessened on the 140 keVimage, and is nearly absent on the iodine material densityimage (far-right).

110 D. E. Morgan: Dual-energy CT of the abdomen

Fig. 3. 48-year-old man with cirrhosis and lateral segmenthepatocellular carcinoma, late hepatic arterial phase rsDECTacquisition. Lower-left image demonstrates appearance of theheterogeneously hyperenhancing mass at 70 keV. Lower-right image demonstrates the appearance of the mass at‘‘CNR-optimized’’ 49 keV. Hounsfield units within the mass atthe lower energy measure 151 HU, compared to nontumoralliver which measures 74 HU. This 77 HU difference is greaterthan the 17 HU difference seen at 70 keV (72 HU within themass and 55 HU in the liver). The upper-left image shows the

graphical representation of the automatic calculation of the‘‘CNR-optimized’’ keV, based on the regions of interest withinthe tumor (yellow circle) and non-tumoral liver (red circle). Theupper-right image shows the spectral Hounsfield unit curveacross all simulated monoenergetic energies (X-axis). Theyellow curve represents the tumor and corresponds to theyellow ROI, and the red curve represents the nontumoral liverand corresponds to the red ROI. Note that the greater degreeof separation at the lower energies compared to ‘‘PACSequivalent’’ keVs, which typically range from 70 to 78 HU.


simulated monoenergetic, also referred to as monochro-matic images, are created in ‘‘projection’’ or ‘‘raw dataspace’’ from the detector data, without generation ofactual 80 and 140 kVp images. From a practice stand-point, although 141 possible viewing energies exist foreach image of the CT examination, images generatedfrom either the 70 or 78 keV energy are sent to PACS andused for diagnosis. One advantage of simulated mono-chromatic images over low kVp images is that reductionin beam hardening artifacts is inherent, and morequantitatively accurate attenuation measurements maybe obtained [4], a feature confirmed by reduction of renal

cyst pseudo-enhancement in a recent phantom study [5].Also with the rapid-switching system it is possible usingeither the dedicated workstation or thin client server toview simulated monoenergetic images that range from 40to 140 keV dynamically or on-the-fly, much as one wouldto window and level a standard CT image, selecting theenergy that best depicts disease processes. In our prac-tice, at 70 keV the image appears visually similar to aconventional CT obtained with a polychromatic beam of120 kVp, and is preferred over 78 keV images. The cor-relations of keV to kVp have been demonstrated in aphantom study by Matsumoto et al. [6], with 70 keV HUmore closely correlating with 100 kVp, and 78 keV with120 kVp images, however.

Because the k edge of iodine is 33.2 keV, just belowthe lower end of the scale of spectral imaging availablewith the rsDECT system, the contribution of iodine toattenuation of the images increases as the viewing keVlevel decreases (Fig. 1). It is important to recognize thatpost-contrast simulated monoenergetic HU values on arsDECT differ substantially at different viewing energies(e.g., 50 vs. 70 vs. 140 keV), with attenuation on spectralHU curves of post-contrast enhanced images increasingat the lower end of the energy spectra. It has becomeapparent in our practice that viewing iodinated IV con-trast enhanced rsDECT abdominal images at 50–52 keVconsistently better depicts lesion contrast in the pancreas[7] and liver, whereas viewing abdominal images at 110–140 keV lessens metal [8] artifacts (Fig. 2); viewing at140 keV maximally removes (but not completely) theeffects of iodine on the monoenergetic images therebyproducing ‘‘pseudo-unenhanced’’ images of the adrenalgland which may help to confirm the presence of a lipid-rich adenoma (Weber et al. (2012) presented to the an-nual meeting of the Society of Abdominal Radiology,unpublished data). Simulated monoenergetic image noisealso increases as the keV decreases, similar to the noiseincrease on 80 kVp images compared to 120 kVp. Theoptimal balance between tissue contrast and noise can becalculated with a push button feature on the independentworkstation of the rsDECT scanner, and a ‘‘CNR-opti-mized’’ level can then be viewed to enhance lesion con-spicuity (Fig. 3). Workflow issues for the dsDECTsystem and rsDECT system have been summarized byMegibow and Sahani [1]. Several articles delving into thephysics of dual-energy CT are recommended for moreinformation. [4, 9–11], but to understand potentialabdominal applications of DECT, more discussion of the‘‘virtual unenhanced’’ image is warranted.

Virtual unenhanced images

There are substantial technical differences between the‘‘virtual unenhanced’’, or ‘‘virtual nonenhanced’’, imagesthat are generated with dsDECT versus rsDECT scan-ners. Both represent post-IV-contrast injection images

Fig. 4. 52-year-old man with left adrenal adenoma, pan-creatic parenchymal phase rsDECT acquisition. A GSI VUEimage demonstrates mean Hounsfield units of 7 within theadenoma. This post-contrast image is derived from multi-material decomposition processing, where iodine is identifiedthen replaced with blood to simulate a monoenergetic imageon which Hounsfield units are measurable with the rsDECTsystem. B Conventional unenhanced image demonstrates aHounsfield unit value of zero, confirming adenoma. Note thatwhile the GSI VUE value of 7 on the GSIVUE image is lessthan the clinically accepted threshold of 10 HU to confirmadenoma, the measurement is different than conventionalunenhanced HU, and further validation of this method iswarranted.


where the iodine has been ‘‘subtracted’’ through thematerial decomposition process. On the dual-sourcesystem, because virtual unenhanced images are created in‘‘image space’’ the measurement of density is in Houns-field units. Early studies revealed no loss in subjectiveimage quality viewing dsDECT virtual unenhancedcompared to conventional unenhanced images [12]. Be-cause the single-source rapid-switching system createsmaterial density virtual unenhanced images in ‘‘projec-tion space’’ using material decomposition basis pairs, thedensity is measured in terms of mg/cc of the materialbeing evaluated, and in the case of the ‘‘water(–iodine)image, the units are mg/cc water rather than HU as ondsDECT. This presents a problem with rsDECT forquantifying liver fat or characterizing incidentally-dis-covered adrenal lesions because the validated HounsfieldUnit thresholds derived from single-energy CT observa-tions cannot currently be applied to rsDECT materialdecomposition basis pair images of fat(–iodine) or wa-ter(–iodine). A new multimaterial post-processing soft-ware for the rsDECT, termed ‘‘GSIVUE’’ (Fig. 4) by themanufacturer (General Electric Healthcare, Waukesha,WI) and available after March 2013 may overcome thishurdle but needs further evaluation before being appliedto clinical practice.

Hounsfield units on dual-energy CT

In phantom studies and in evaluation of many body re-gions, the fidelity of virtual unenhanced attenuationvalues is a subject of continued investigation and maydepend upon the scanner technology, the dynamic phaseof images being evaluated, and the location in the bore ofthe tissue being evaluated. Sahni et al. [13] found a sta-tistically significant difference in values of liver, renalparenchyma, and aorta, but no difference in spleen andfat values using a dsDECT system in 100 consecutivepatients undergoing CT urograms with dual-energytechnique. The same authors found that the contrastmaterial phase did not affect the HU values on the vir-tual unenhanced images. Yet in a phantom and patientstudy of dsDECT acquired in arterial and venous phasescompared to conventional unenhanced CT, significantdifferences in HU of the abdominal organs were foundand were the greatest in the aorta, spleen, and fat; thedifferences were below 15 HU in 95.5% of measurements[11]. The greater differences between the virtual and trueunenhanced HU in the spleen and fat compared to otherabdominal organs have been noted on portal phasedsDECT with the use of a tin-filter on dsDECT [14].Location in the bore might be an issue as well. On a

Fig. 5. 77-year-old man with incidental renal cell carcinomaidentified on CT angiogram performed to evaluate endovas-cular aortic repair, arterial phase rsDECT acquisition. The rightimage demonstrates 5.9 mg/cc iodine within the enhancingmass in the anterior right renal midportion. Although this mass

is clearly evident on the simulated monoenergetic (left 70 keV,center 52 keV) images, the method of iodine quantification hasbeen proposed as a means to confirm enhancement when noconventional unenhanced image is acquired, and theenhancement is less robust visually.


phantom study using a rsDECT scanner, Matsuda et al.[9] found that attenuation measurements in HU on mo-noenergetic 65 keV images provided consistent valuesregardless of phantom shape, whereas conventionalMDCT produced a statistically significant difference inHU measured in the center and periphery of an ellipticalphantom. Other authors found higher-fitting coefficientsfor CT attenuation values and Iodine concentrationusing single-source rapid-switching imaging compared toconventional polychromatic beam CT [10]. Simulatedmonoenergetic HU on rsDECT are different than HUderived from dsDECT blended simulated 120 kVp ima-ges, and none of these dual-energy derived HU are thesame as conventional HU values obtained with single-energy CT using 120, 100, or 80 kVp; all are referred tosimply as HU in today’s literature, but in the era ofDECT, changes in nomenclature to facilitate an under-standing of the level and mode of energy from which theHU was derived might be in order. The dependence ofCT attenuation values on energy is a topic that has beendiscussed for nearly 40 years [15].

At our institution, rsDECT of the abdomen is typi-cally employed for patients with suspected hepatic or

pancreatic disease, and is part of a multiphasic exami-nation consisting of: conventional unenhanced imagesobtained using SECT, late hepatic arterial or pancreaticparenchymal phase images obtained with rsDECT, andportal venous and equilibrium phase (if applicable) usingstandard polychromatic beam CT. With this multiphasicmethod, patients scanned at our institution have lowerradiation exposures as measured by DLP compared tosimilar anatomic coverage abdominal scans being ob-tained on other units in our department (Sarver et al.(2012) presented to the Society of Abdominal Radiology,unpublished data). If a multiphasic abdominal scanningtechnique is required, dose reduction achievable byomitting the conventional unenhanced scan was approx-imately 30%–50% [12, 16–18]. Finally, although twoenergies are used to generate DECT images regardless ofthe type of system (dual-source vs. rapid-switching), theradiation dose is not twice the dose of conventional CT,and iterative reconstruction techniques may be appliednow on both types of dual-energy scanners during dual-energy as well as conventional CT acquisitions. Thereader is referred to several articles addressing the com-plex subject of dual-energy CT radiation dose [19–21].

Fig. 6. 52-year-old man with left adrenal adenoma (same pa-tient as Fig. 4), pancreatic parenchymal phase rsDECT acqui-sition, material density evaluation. The left image represents the‘‘pseudo-unenhanced’’ or 140 keV image, with HU value of 6.The right image represents thewater(–iodine) material densityor‘‘virtual unenhanced’’ image on which the adenoma measures

994 mg/cc water. This quantification of material in mg/cc on thevirtual unenhanced image has limited the ability to exclude theconventional unenhanced acquisition from multiphasic abdom-inal protocolson the rsDECTsystem.This isnot the casewith thedsDECT system, which has quantification of attenuation in HUon virtual noncontrast images generated in image space.


Renal applications

Urinary tract calculi

One of the early and promising applications of dual-en-ergy CT was the improved characterization of renal stonecontent using material-specific imaging. This is impor-tant since stones of different chemical compositions havedifferent results following shockwave lithotripsy. Earlystudies using dual-source dual-energy technique inphantoms and in clinical patients showed an ability todifferentiate uric acid from calcium-containing stones[22–27]. Zilberman et al. [28] used a novel post-process-ing technique also on the dsDECT system to identifystones of varying content from uric acid to cysteine tostruvite in addition to other stone types. More recentstudies using the dual-source system and adding a tin-filter to the high-energy beam reported differentiationnot only of uric acid from calciferous stones, but alsobetween types of calcified stones in a phantom study [29].It is important to note that most work on renal stonecomposition using material-specific DECT has beenperformed on unenhanced studies. The administration ofIV contrast makes characterization of stones morechallenging when acquisition is timed to occur afterexcretion into the collecting systems, although thismethodology would be used to reduce radiation dose tothe patient. In a phantom study where progressively in-creased amounts of iodine were added to test tubescontaining stones, Wang et al. [30] showed diminishedsensitivity for identification of uric acid stones as theiodine concentration increased. If this technique of ana-lysis is applied to routine DECT scanning acquired in apost-contrast manner, particularly the excretory phaseoften utilized to assess hematuria, this could hinderaccurate stone characterization in clinical patients with-out re-scanning. Karlo et al. [31] found that 17% ofstones were missed on a prospective study of split-bolus

dsDECTin 100 patients, the majority <4 mm. Further-more, the majority of urinary tract calculi contain mul-tiple components and accurate classification of mixedstone types is a challenge [32, 33]. This challenge may beovercome by more sophisticated combinations of dual-energy interrogation. With a rsDECT system, Kulkarniet al. [34] were able to separate uric acid and nonuric acidstones using two material decomposition, and then usedthe stone effective atomic number ‘‘z eff’’ (a push buttonapplication) to characterize struvite, cysteine, and cal-cium oxalate stones; for mixed stones the dominantcomponent was identified with z eff.

Focal renal lesions

The ability of DECT to produce material-specific imagesprovides the opportunity to detect iodine withinenhancing renal masses on a single post-contrast CTacquisition. The virtual unenhanced (VU) image is cre-ated by subtracting iodine and serves as a baseline. If, asseen on conventional CT, a renal lesion is high densitydue to hemorrhage, it will remain visible on the VUimage, whereas if it was due to minimal enhancement itwould not. Material-specific iodine images are used tocreate iodine maps or overlays, but more importantly areused to quantify the amount of iodine within a focalrenal lesion. On dsDECT, the colored iodine overlays aresuperimposed on the grayscale blended image. Graseret al. [16] showed fast and accurate characterization ofrenal lesions based on this visual methodology. Alsousing the dsDECT system, Chandarana et al. [35] re-ported a linear relationship between measured andknown iodine concentration in a phantom study, andsubsequently found that lesion iodine concentration andlesion-to-aorta iodine ratio in enhancing masses wereboth significantly higher in neoplasms than in hyper-dense and simple cysts. On rsDECT, the iodine(–water)basis pair is used to measure the concentration of iodinein mg/cc (Fig. 5), although iodine overlays can also bemade for rapid visual assessment as described fordsDECT above. Kaza et al. [36] found that renal neo-plasms were present when a threshold of 2 mg/cc orgreater iodine density was identified within a focal lesion.In their study of 83 patients, the identification of iodineusing material density measurement was more accuratethan detection of enhancement on overlay images. As-centi et al. [37] also recently reported a statistically sig-nificant improvement in accuracy using whole tumoriodine quantification compared to HU enhancementmeasurements for characterization of renal lesions. Inaddition to these applications, quantification of iodinewithin renal carcinoma metastases has the potential toserve as an imaging biomarker for patients receivingantiangiogenic agents.

Fig. 7. 38-year-old woman with marked hepatic steatosis,late hepatic arterial phase rsDECT acquisition. A Conven-tional unenhanced image demonstrating HU within the lateral,anterior, and posterior segments. B ‘‘Virtual unenhanced’’water(–iodine) material density image with values of mg/cc;while visually this liver is extremely steatotic, the quantitativevalue of 989 mg/cc water is not familiar to most radiologists.C GSIVUE image relates attenuation in terms of HU, similar toconventional unenhanced CT. D Volumetric color contrastpresentation of degree of steatosis. The color scale of HUvalues on the left side of the image indicates extreme stea-tosis and it is possible with this program to assess the percentof parenchyma that demonstrates the specific range of HUlevels for a more global assessment of steatosis. E Forcomparison, the 70 keV images from which images B–D werederived is shown. Post-processing to generate images B–Dtook approximately 8 s.

b


Adrenal applications

Incidental adrenal lesions are commonly found on con-trast-enhanced CT examinations performed for otherindications [38]. If unenhanced images are present, there

are defined attenuation criteria to differentiate types ofadrenal lesions and confirm a lesion as a benign ade-noma. However, even if conventional unenhancedimages are not acquired, it may still be possible to

Fig. 8. 54-year-old man with multifocal hepatocellular car-cinoma, undergoing transarterial chemoembolization. A Pre-treatment rsDECT images acquired in the late hepatic arterialphase displayed as left column 70 keV, center column52 keV, and right column iodine(–water) material density im-age, axial superior row, and coronal inferior row. Thenumerous hyper-enhancing masses are better seen at thelower energy. B Same set of images as A displayed withcolor information (a push-button feature of the independent

workstation) for ease of rapid visualization. C Angiogramdemonstrating the multifocal HCC prior to embolization.D Post-treatment rsDECT late hepatic arterial phase imagedemonstrates absence of enhancement in the region oftreated tumors on the monoenergetic images, and lack ofiodine indicating diminished perfusion/successful TACE onthe iodine(–water) material density image on the right. Ideally,an automated method of volumetric response quantificationfor lesion iodine will be developed.


characterize a lesion if the contrast enhanced CT wasperformed using a dual-energy technique. Gnannt et al.[39] showed good accuracy of virtual unenhanced imagesgenerated on dsDECT in a study evaluating 42 patientswith 51 lesions. Using conventional unenhanced CT as areference, the sensitivity, specificity, and accuracy fordsDECT virtual unenhanced images for classifying a le-sion ‡1 cm as probably benign were 95, 100, 97%, and91, 100, 95%, respectively, for two independent readers.There were no significant differences in the mean HUvalues on virtual unenhanced compared to conventional

unenhanced images. Similarly, Ho et al. [40] reported nostatistically significant difference in the mean HounsfieldUnit measurements of adenomas (10.3 ± 13.1 on virtualunenhanced vs. 8.9 ± 10.4 on conventional unenhancedimages), or metastases (35.7 ± 6.0 on virtual unenhancedvs. 32.6 ± 6.1 on conventional unenhanced images). Thevirtual unenhanced images were an average of1.8 ± 1.7 HU higher than conventional unenhancedimages, and virtual unenhanced images classified adrenaladenomas as greater than 10 HU in only 13% (3/23), 4%

(1/23), and 9% (2/23) for readers 1, 2, and 3, respectively,

Fig. 8. continued


Fig. 8. continued


in that study. Importantly, no malignant nodules weremisclassified in either study. In a different type of studyevaluating patients with known adrenal lesions, Kimet al. [41] found diminished sensitivity for detection oflipid-rich adenomas on both the ‘‘early’’ (1 min post-contrast) and ‘‘late’’ (15 min post-contrast) virtual un-enhanced images, due to insufficient iodine subtractionusing the three point material decomposition algorithm.Using rsDECT, our group evaluated arterial phase wa-ter(–iodine), fat(–iodine), and pseudo-unenhanced140 keV images compared to conventional unenhancedscans in the same subjects and found strong correlationbetween these rsDECT variables and accepted single-energy MDCT attenuation values for high lipid-contentand low lipid-content adrenal lesions. Unlike dual-sourcedual-energy CT, virtual unenhanced material decompo-sition images acquired using rsDECT provide densities inunits of mg/cc (Fig. 6) rather than HU as is presentlyavailable on material-specific dsDECT images. Despitethis fact, clinically relevant thresholds on rsDECT thatidentified lipid-rich adenomas with high specificity weredetermined (Weber et al. (2012) presented to the Societyof Abdominal Radiology, unpublished data). But nowwith the advent of GSI VUE, it may be possible to do adirect HU comparison with conventional unenhancedCT (See Fig. 4), and validation studies are underway byseveral groups using this technology.

Liver applications

Evolving liver applications include material-specific im-age viewing and quantification as well as low keV mo-noenergetic image viewing to increase lesion conspicuity.Material-specific images may be used to evaluate biliarystone disease, hepatic parenchymal deposition of fat oriron, or identification of iodine within tumors both as ameans of detection of disease as well as assessment ofresponse. Virtual unenhanced images generated on adsDECT system from late hepatic arterial and portalvenous phase failed to identify 16% of gallstones seen onconventional unenhanced images in a study of 100 pa-tients with gallbladder or bile duct stones. These werepredominantly small gallstones (<1.7 mm) and pig-mented bile duct stones with HU £ 78 HU [42]. In clin-ical practice, it is difficult on SECT to quantify hepaticfat in the presence of iron and vice versa. The amount offat is underestimated in the presence of iron, and theamount of iron is underestimated due to the presence ofhepatic fat. In phantom studies using dsDECT and aniron-specific three material decomposition algorithm,Fischer et al. [43] were able to create a virtual iron imageto accurately quantify iron irrespective of liver tissueattenuation and fat, and to generate a virtual non-ironimage to accurately quantify fat in the presence of iron

[44]. In a combined phantom and clinical study, Joe et al.[45] showed that the difference of averaged attenuationbetween the 140 and 80 kVp images could be used todifferentiate patients with greater than 10% hepatic iron,but the same value did not correlate with hepatic stea-tosis. Note that the dual-energy acquisition for this studywas without IV contrast enhancement. In a phantom andmouse model of hepatic steatosis, Artz et al. [46] dem-onstrated that attenuation and fat density of the liverparenchyma using unenhanced rsDECT correlatedhighly with triglyceride content in the phantom, but inthe model, only attenuation correlated highly with tri-glyceride content in hepatocytes; the fat material densityimages did not perform as well. Using novel post-pro-cessing of rsDECT monoenergetic image subtraction(termed DESI) in a patient population, Zheng et al. [47]were able to identify varying degrees of fat accumulation.Note that these studies did not attempt to addressquantification of hepatic steatosis in a post-contrastsetting. Given the prevalence of fatty liver disease, it willbe important to use material-specific imaging capabilitiesto quantify hepatic fat after administration of IV con-trast for patients who did not undergo an unenhancedSECT series (Fig. 7). This is important, as the quanti-tative information of hepatic fat content can be gainedfrom the images already acquired as part of the clinicallyindicated scan rather than having to suggest that thepatient undergo a second unenhanced CT or an MRI forfurther evaluation. Another application explored withmaterial-specific imaging of the liver is the identificationof iodine within tumor thrombus in patients with hepa-tocellular carcinoma; using iodine indices (comparingthrombus to aorta) Qian et al. [48] reliably distinguishedbland from tumor thrombus in patients using rsDECT.

Lesion contrast and conspicuity in hepatocellularcarcinomas may be improved by viewing lower keVimages on rsDECT or the low kVp images on dsDECT.However, although Altenbernd et al. found better sen-sitivity for detection of hyperenhancing liver lesions witharterial-phase 80 kVp images compared to blendedimages on dsDECT, the subjective image quality of the80 kVp images was judged very poor. In addition, 15 of40 subjects in that study had incomplete hepatic coveragewith the early generation dsDECT machine [49].Applying novel blending parameters might help to im-prove image quality [50]. Using the rsDECT system, it ispossible to instantaneously calculate the optimal viewingkeV (from a range of 40–140) for a lesion within the liveror other abdominal organs, based on contrast to noiseratios (CNR) of the image (See Fig. 3). Using this tech-nique and comparing the CNR-optimized keV image tothe 70 keV image, a greater number of focal hepatic le-sions were identified on arterial-phase rsDECT withoutcompromising image quality (Thomas et al. (2011)


presented to the American Roentgen Ray Society,unpublished data); further study with a larger multi-reader protocol is ongoing. When images are viewed withdedicated rsDECT software, it is possible to view thelower keV images and 70 keV images side by side withiodine images (Fig. 8), a practice which also enhanceslesion detection due to the lower CNR of the iodineimages. Color coding (see Fig. 8), iodine thresholdimaging, spectral HU curves, and a slide-bar that allowson the fly scrolling through all available energies provideadditional means of presentation the dual-energy infor-mation. This can be helpful in rapidly visualizing re-sponse to locoregional therapies such as transarterterialchemoembolization or ablation; alternatively, quantita-tive measures can be utilized (Fig. 9) [51, 52]. Highercontrast to noise ratios of iodine maps provide improvedconspicuity of ablation zone margins compared toblended images [52].

Pancreas applications

Macari et al. [53] first showed that conspicuity of pan-creatic adenocarcinoma was greater using 80 kVp com-pared to blended 120 kVp images on dsDECT obtainedin portal venous phase. Patel et al. [7] used rsDECTacquired during pancreatic parenchymal phase to eval-uate pancreatic adenocarcinoma lesion conspicuity in alarger population of 65 patients, comparing 70 keVimages to contrast to noise ratio (CNR)-optimized keVimages and 45 keV images. The statistically significantincrease of lesion contrast (defined as HU differencebetween tumoral and nontumoral pancreas) at the CNR-optimized keV was nearly double that of the 70 keVimage, the image typically used for routine PACS view-ing. Notably, the median value of the CNR optimizedimages for the population was 52 keV (Fig. 10). There islittle lesion-specific published literature on other dual-energy applications in the pancreas; however, earlyexperiences with pancreatic endocrine neoplasms andcystic pancreatic lesions have been presented in abstracts.The technology appears promising for improved evalu-ation compared to single-energy CT because of the po-tential gains in conspicuity of pancreatic hypervascularlesions or of improved visualization of complexity withincystic masses (Fig. 11). We have explored the use of io-dine images for evaluation of small or isoattenuatingpancreatic neoplasms (Fig. 12), since on rsDECT theseimages have lower contrast noise ratios than 70 or lowerkeV images. Chu et al. [54] also found that iodine imageshad additional diagnostic yield compared to blendedimages on a dsDECT system; in that study the iodineimages helped to discriminate the cystic versus solidnature of a lesion, provided greater conspicuity and aclearer assessment of the relationship to nearby vessels.Iodine images might be helpful for evaluation of patients

with pancreatic necrosis (Fig. 13) to determine if per-fused pancreas is present within a complex retroperito-neal collection evolving during the course of an acutepancreatitis episode.

In our practice, as a result of preliminary hepatic andpancreatic investigations we now routinely send 52 keVsimulated monoenergetic images, in addition to 70 keVimages to PACS for routine clinical interpretation ofmultiphasic abdominal rsDECTs. We have found thatnot only does this increase lesion conspicuity, but also, inthe case of a suboptimal bolus, the gain in contrast dif-ference between the tumoral and nontumoral tissues canbe recovered in part by viewing at the lower energies.Creation of CT angiograms from the lower keV sourceimages provides more robust surface rendered images forreferring surgeons. In addition to the two sets of simu-lated monoenergetic images, the water(–iodine) and io-dine(–water) material decomposition basis pair imagesare routinely sent to PACS as separate series and viewedfor clinical interpretation. Finally, the use of a dedicatedmetal artifact reduction algorithm (MARS) usingrsDECT, or simply viewing the images at 140 keV pro-vides more optimal viewing of the pancreas aroundmetallic bile duct stents or surgical clips that may bepresent from prior hepatic or pancreatic resections(Fig. 14), similar to reduction of metal artifacts aroundjoint prostheses [8].

Gastrointestinal tract applications

Potential benefits of utilizing dual-energy CT in the gutinclude possibilities for improved visualization of hype-renhancing bowel pathologies, better identification ofischemic segments, evaluation of alternate contrast

Fig. 9. 53-year-old man with cirrhosis and hepatocellularcarcinoma, quantitative evaluation of transarterial chemo-embolization response. A Pretreatment late hepatic arterialphase rsDECT acquisition, middle-left image 70 keV, middle-right image 52 keV, lower-left image water(–iodine), lower-right image iodine(–water). The iodine content within the tu-mor measures 2.58 mg/cc. The upper-left image representsthe Hounsfield unit spectral curve of the tumor (yellow curve)vs. hepatic parenchyma (pink curve), with greater separationbetween tumor and nontumoral tissue at the lower energies;note that the curve of the hyperenhancing lesion is locatedabove the curve of the hepatic parenchyma up to the 80 keVlevel. B Post-treatment late hepatic arterial rsDECT acquisi-tion reveals visual diminished enhancement on the simulatedmonoenergetic images (middle row). The quantitative de-crease in iodine content reveals (lower-right image) that thelesion now contains 0.8 mg/cc iodine. Note that the spectralcurves (upper-left image) now reflect consistently lower val-ues of the treated tumor (yellow curve) compared to the liverparenchyma (red curve) across all energies.

c


Fig. 9. continued


agents, or improved methods of electronic colon cleans-ing during CT colonography. Similar to evaluation ofCrohn disease at 80 kVp [55] compared to 120 kVp,improved sensitivity to detect hyperenhancing segmentsof active small bowel inflammation using lower keVviewing energies might be possible, if CT rather than

MRI is being utilized to establish the diagnosis. Identi-fication of melanoma metastases (Fig. 15) or small gas-troenteric neuroendocrine neoplasms (Fig. 16) may alsobenefit from low keV viewing or low kVp acquisition andviewing. Identification of colonic adenocarcinomas(median size 4.3 cm) in unprepped patients was aided by

Fig. 10. 47-year-old woman with pancreatic adenocarci-noma, pancreatic parenchymal phase rsDECT acquisition.Lower left 70 keV image demonstrates region of interestwithin a non-contour altering hypoattenuating pancreaticadenocarcinoma (yellow oval) and nontumoral pancreas (redoval). Lower right, 49 keV image demonstrating the increasedconspicuity of the lesion at the lower viewing energy. Upper-

left image demonstrates spectral Hounsfield unit curvesacross all available at energies, from 40 to 140 keV. Thehypovascular pancreatic tumor curve is lower than the normalparenchyma, and the difference between the two values isgreater at the lower energies. Note that unlike Fig. 1, thewindow and level have been altered for optimal viewing at thelower energy.


Fig. 11. 42-year-old woman with mucinous cystic neoplasm,pancreatic parenchymal phase rsDECT acquisition. A Themultiple septations are better seen on the 52 keV image(right) compared to the ‘‘PACS-equivalent’’ 70 keV image(left). Window and level have not been altered. B Same levelas A with standard push-button color filter applied. Note thatthe enhanced visualization of the septations, denoted by thered coloration within the tumor at 52 keV (right image) com-pared to 70 keV (left image). Also, the low attenuation cystcontents have a different appearance at the lower versus

higher viewing energy, and are clearly different than the waterwithin the stomach. C Regions of interest within the cysticmass (yellow oval) and stomach (blue oval). Hounsfield unitmeasurement within the lesion and stomach are both in-creased on the 52 keV image (lower right) compared to the70 keV image (lower left), however, so is the difference be-tween the two substances. This is plotted out on the spectralHounsfield unit curve (upper-left image), where the cystcontents have higher attenuation at all energies compared tothe water in the stomach.


the use of iodine maps in a population with known orhighly suspected cancers [56]. The utility of dual-energyCT in patients with metastatic gastrointestinal stromaltumors has been evaluated by two groups, both of whomsuggested that iodine quantification rather than size de-crease and Choi criteria might be a more robust indicatorof response to therapy with targeted agents [57–59], andthis type of novel analysis can be translated to otherhypervascular tumors (Fig. 17), where an iodine content

decrease represents a surrogate biomarker for perfusionand thus response to anti-angiogenic agents. Finally, in arabbit model of trauma, experienced and inexperiencedreaders alike were able to distinguish with increasedconfidence and accuracy extraluminal abdominal col-lections that arose from IV iodinated contrast extrava-sation compared to those originating from oral Bismuthcontrast extravasation, using rsDECT material decom-position attenuation maps [60].

Fig. 11. continued


Fig. 12. 62-year-old woman with non-contour altering isoat-tenuating pancreatic adenocarcinoma. A rsDECT images ac-quired in the pancreatic parenchymal phase displayed as leftcolumn 70 keV, center column 52 keV, and right column io-dine(–water) material density image, axial superior row, andcoronal inferior row. The 52 keV images have been windowedand leveled appropriately, better revealing the small mass pro-

ducing common bile duct obstruction in the pancreatic head. Thelesion may be best seen on the iodine images (right column) dueto the lower contrast to noise ratio. B Same image with regions ofinterest placed in the pancreatic tumor (green circle) and non-tumoral pancreas (magenta circle). The Hounsfield unit differ-ence between tumor and nontumoral pancreas at 70 keV is lessthan 10, whereas on the 52 keV image the difference is 44.


Fig. 12. continued


Fig. 13. 57-year-old man with necrotizing pancreatitis,pancreatic parenchymal phase rsDECT acquisition. A 70 keVsimulated monoenergetic image demonstrates a focal,homogeneous low attenuation collection replacing the pan-creatic neck and body region. B Iodine(–water) materialdensity image at the same level reveals slight heterogeneitywithin the collection, with increased density seen posteriorly.C Same image with regions of interest in the anterior aspectof the collection (red oval), posterior collection (pink oval), andpancreatic tail (green oval). The relative amounts of iodine,0.68, 2.35, and 2.97 mg/cc suggest that the material in theposterior aspect of the collection may represent partiallyperfused pancreas. Validation of this type of quantitative io-dine assessment is being investigated.

b


Fig. 14. Metal artifact reduction algorithm applied toabdominal images. 73-year-old woman with metastatic pan-creatic serous cystadenocarcinoma, pancreatic parenchymalphase rsDECT acquisition. Left column viewed as originallyacquired, right column after post-processing with ‘‘metal arti-fact reduction software’’ (MARS) algorithm. Note that the

beam hardening artifact resulting from clips around the inferiormargin of the liver on the left images. There are two hype-renhancing metastases within the posterior segment, howeverthe medial and anterior segments are difficult to evaluate forpotential additional metastases. After use of MARS (rightcolumn), the hepatic parenchyma is much better seen.


Fig. 15. 69-year-old manwith metastatic melanoma,late hepatic arterial phasersDECT acquisition.A 50 keV, B 70 keV,C 90 keV, and D 120 keVimages demonstrateincreased visualization ofthe hyperenhancingmelanoma metastasisinvolving the ileum at thelower energies.


Fig. 16. 39-year-old man with duodenal gastrointestinalstromal tumor, late hepatic arterial phase rsDECT acquisition.A push-button color filter has been applied to the 70 keVsimulated monoenergetic image, revealing the heteroge-neously enhancing mass with hypervascular rim in the distalsecond portion of the duodenum. Use of simple color filters ongrayscale images may enhance visualization, similar to theway that superimposed iodine maps over grayscale can im-prove the ability to detect perfusion.

Fig. 17. 72-year-old man with multifocal hepatocellular car-cinoma, on sorafenib therapy, late hepatic arterial phasersDECT acquisition on sequential examinations obtainedthrough therapy. Upper-left block pretreatment evaluation;upper-right block 3 months after therapy initiation, lower-leftblock 5 months, lower-right block 9 months after therapy initi-ation, respectively. Two different color filters (for comparison)have been applied to the 70 keV (left) and 52 keV (center)

images. The iodine images are on the right of each block. Notethat the progressive increase in size of the lesions over time,which would suggest progression by RECIST. However, thereis central necrosis, clearly depicted on the color maps andmeasurable quantitatively on the iodine images throughouttherapy, suggesting favorable response. This type of assess-ment is being incorporated into investigator-initiated clinicaltrials for comparison with standard response assessment.


Summary

The abdominal applications of dual-energy CT continueto evolve. There is great potential for improved diag-nostic performance by capitalizing on increased lesionconspicuity with lower keV monoenergetic images orlower kVp image sets. Material-specific imaging allowsgeneration of virtual unenhanced images, iodine quan-tification, and renal stone characterization at present,and the possibilities exist to create new types of contrastor expand qualitative and quantitative tissue analyses forsubstances other than iodine. Artifacts due to beamhardening and pseudo-enhancement in abdominalstructures can be lessened with the rsDECT approach.Because post-contrast rsDECT simulated monoenergeticHU values increase at the lower end of the energy spectraas the k edge of iodine is approached, just as with lowkVp imaging the opportunities to use lesser amounts ofiodinated contrast are being explored. Finally, bothclinically available technologies, dsDECT and rsDECT,can be utilized to reduce radiation dose by obviating theneed for conventional unenhanced series from multi-phasic abdominal protocols.

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