Clinical Implementation of Dual-Energy CT for Gastrointestinal Imaging

Dual-energy CT (DECT) overcomes several limitations of conventional single-energy CT (SECT) for the evaluation of gastrointestinal diseases. This article provides an overview of practical aspects of the DECT technology and acquisition protocols, reviews existing clinical applications, discusses current challenges, and describes future directions, with a focus on gastrointestinal imaging. A head-to-head comparison of technical specifications among DECT scanner implementations is provided. Energy- and material-specific DECT image reconstructions enable retrospective (i.e., after examination acquisition) image quality adjustments that are not possible using SECT. Such adjustments may, for example, correct insufficient contrast bolus or metal artifacts, thereby potentially avoiding patient recalls. A combination of low-energy monochromatic images, iodine maps, and virtual unenhanced images can be included in protocols to improve lesion detection and disease characterization. Relevant literature is reviewed regarding use of DECT for evaluation of the liver, gallbladder, pancreas, and bowel. Challenges involving cost, workflow, body habitus, and variability in DECT measurements are considered. Artificial intelligence and machine-learning image reconstruction algorithms, PACS integration, photon-counting hardware, and novel contrast agents are expected to expand the multienergy capability of DECT and further augment its value.

Lower limit of iron quantification using dual-energy CT - a phantom study

Purpose

Dual‐energy computed tomography (DECT) has been proposed for quantification of hepatic iron concentration (IC). However, the lower limit of quantification (LLOQ) has not been established, limiting the clinical adoption of this technology. In this study, we aim to (a) establish the LLOQ using phantoms and (b) investigate the effects of patient size, dose level, energy combination, and reconstruction method.

Methods

Three phantom sizes and eight vials of ferric nitrate solution with IC ranging from 0 to 10 mg/ml were used. DECT scans were performed at 80/140 and 100/140Sn kVp, and using five different levels of CT dose index (CTDI). An image‐domain three‐material‐decomposition algorithm was used to calculate the IC. The LLOQ was determined based on the coefficient of variation from repeated measurements.

Results

The measured IC correlated strongly with the true IC in the small and medium phantoms (R² of linear regression > 0.99) and moderately in the large phantom (0.8 < R²<0.9). The LLOQ improved with increased CTDI. At 30 mGy, the LLOQ was found to be 0.50/1.73/6.25 mg/ml in the small/medium/large phantoms, respectively. 80/140Sn kVp resulted in superior LLOQ for all phantom sizes compared to 100/140Sn kVp, primarily due to the difference in their iron enhancement ratios (1.94 and 1.55, respectively). Iterative reconstruction was found to further improve the LLOQ (by ~ 11%), whereas reconstruction kernel smoothness had negligible effect. The LLOQ of iron was significantly higher than that of iodine due to its lack of a useful k‐edge and lower enhancement ratio.

Conclusion

Iron quantification at clinically important levels was achieved in a small‐ and a medium‐sized phantom using DECT, but proved challenging in a large phantom. Wide spectral separation and accurate calibration were found to be critical to the success of the technology.

Normalized Dual-Energy Iodine Ratio Best Differentiates Renal Cell Carcinoma Subtypes Among Quantitative Imaging Biomarkers From Perfusion CT and Dual-Energy CT

OBJECTIVE. The objective of our study was to assess and compare the diagnostic accuracy of perfusion CT (PCT) and dual-energy CT (DECT) in differentiating clear cell renal cell carcinoma (ccRCC) from non-ccRCC. MATERIALS AND METHODS. This retrospective study included 51 patients with 52 renal cell carcinomas (RCCs) (36 ccRCCs and 16 non-ccRCCs) who underwent both PCT and DECT before surgery or biopsy between January 2014 and December 2018. Three independent readers measured blood flow, blood volume (BV), and permeability using PCT and iodine concentration (IC) and iodine ratio using DECT. Interreader agreement was calculated using the intraclass correlation coefficient (ICC). Multivariable logistic regression analysis was performed to assess PCT and DECT models. Size-specific dose estimates of the two methods were compared. RESULTS. BV (ICC, 0.93) and iodine ratio (ICC, 0.85) were the most reproducible parameters. Both PCT and DECT were significant models (p < 0.05, all readers) for differentiating ccRCC from non-ccRCC. There was no significant difference in diagnostic accuracy between PCT and DECT (p > 0.05). BV and iodine ratio were independent predictors of nonccRCC (p < 0.05). However, the mean size-specific dose estimate was 16 times lower with DECT than with PCT (p < 0.001). The AUC of iodine ratio was 0.95, and sensitivity, specificity, and accuracy with an iodine ratio cutoff of 63.72% was 0.90, 0.86, and 0.87, respectively. CONCLUSION. PCT and DECT had comparable and high diagnostic accuracy in differentiating RCC subtypes; however, because of the significantly lower radiation dose of DECT, iodine ratio may be used as the best independent predictor.

Gastrointestinal Applications of Iodine Quantification Using Dual-Energy CT: A Systematic Review

Dual-energy computed tomography (DECT) can estimate tissue vascularity and perfusion via iodine quantification. The aim of this systematic review was to outline current and emerging clinical applications of iodine quantification within the gastrointestinal tract using DECT. The search was conducted with three databases: EMBASE, Pubmed and The Cochrane Library. This identified 449 studies after duplicate removal. From a total of 570 selected studies, 30 studies were enrolled for the systematic review. The studies were categorized into four main topics: gastric tumors (12 studies), colorectal tumors (8 studies), Crohn’s disease (4 studies) and miscellaneous applications (6 studies). Findings included a significant difference in iodine concentration (IC) measurements in perigastric fat between T1–3 vs. T4 stage gastric cancer, poorly and well differentiated gastric and colorectal cancer, responders vs. non-responders following chemo- or chemoradiotherapy treatment among cancer patients, and a positive correlation between IC and Crohn’s disease activity. In conclusion, iodine quantification with DECT may be used preoperatively in cancer imaging as well as for monitoring treatment response. Future studies are warranted to evaluate the capabilities and limitations of DECT in splanchnic flow.

Dual contrast in computed tomography allows earlier characterization of articular cartilage over single contrast

Cationic computed tomography contrast agents are more sensitive for detecting cartilage degeneration than anionic or non-ionic agents. However, osteoarthritis-related loss of proteoglycans and increase in water content contrarily affect the diffusion of cationic contrast agents, limiting their sensitivity. The quantitative dual-energy computed tomography technique allows the simultaneous determination of the partitions of iodine-based cationic (CA4+) and gadolinium-based non-ionic (gadoteridol) agents in cartilage at diffusion equilibrium. Normalizing the cationic agent partition at diffusion equilibrium with that of the non-ionic agent improves diagnostic sensitivity. We hypothesize that this sensitivity improvement is also prominent during early diffusion time points and that the technique is applicable during contrast agent diffusion. To investigate the validity of this hypothesis, osteochondral plugs (d = 8 mm, N = 33), extracted from human cadaver (n = 4) knee joints, were immersed in a contrast agent bath (a mixture of CA4+ and gadoteridol) and imaged using the technique at multiple time points until diffusion equilibrium. Biomechanical testing and histological analysis were conducted for reference. Quantitative dual-energy computed tomography technique enabled earlier determination of cartilage proteoglycan content over single contrast. The correlation coefficient between human articular cartilage proteoglycan content and CA4+ partition increased with the contrast agent diffusion time. Gadoteridol normalized CA4+ partition correlated significantly (P < .05) with Mankin score at all time points and with proteoglycan content after 4 hours. The technique is applicable during diffusion, and normalization with gadoteridol partition improves the sensitivity of the CA4+ contrast agent.

Evaluation of a commercial deformable image registration algorithm for dual-energy CT processing

Purpose

Several dual‐energy computed tomography (DECT) techniques require a deformable image registration to correct for motion between the acquisition of low and high energy data. However, current DECT software does not provide tools to assess registration accuracy or allow the user to export deformed images, presenting a unique challenge for image registration quality assurance (QA). This work presents a methodology to evaluate the accuracy of DECT deformable registration and to quantify the impact of registration errors on end‐product images.

Methods

The deformable algorithm implemented in Siemen Healthineers's Syngo was evaluated using a deformable abdomen phantom and a rigid phantom to mimic sliding motion in the thorax. Both phantoms were imaged using sequential 80 and 140 kVp scans with motion applied between the two scans. Since Syngo does not allow the export of the deformed images, this study focused on quantifying the accuracy of various end‐product, dual‐energy images resulting from processing of deformed images.

Results

The Syngo algorithm performed well for the abdomen phantom with a mean registration error of 0.4 mm for landmark analysis, Dice similarity coefficients (DSCs) > 0.90 for five organs contoured, and mean iodine concentrations within 0.2 mg/mL of values measured on static images. For rigid sliding motion, the algorithm performed poorer and resulted in noticeable registration errors toward the superior and inferior scan extents and DSCs as low as 0.41 for iodine rods imaged in the phantom. Additionally, local iodine concentration errors in areas of misregistration exceeded 3 mg/mL.

Conclusions

This work represents the first methodology for DECT image registration QA using commercial software. Our data support the clinical use of the Syngo algorithm for abdominal sites with limited motion (i.e., pancreas and liver). However, dual‐energy images generated with this algorithm should be used with caution for quantitative measurements in areas with sliding motion.

Assessment of Solitary Pulmonary Nodules Based on Virtual Monochrome Images and Iodine-Dependent Images Using a Single-Source Dual-Energy CT with Fast kVp Switching

With lung cancer being the most common malignancy diagnosed worldwide, lung nodule assessment has proved to be one of big challenges of modern medicine. The aim of this study was to examine the usefulness of Dual Energy Computed Tomography (DECT) in solitary pulmonary nodule (SPN) assessment. Between January 2017 and June 2018; 65 patients (42 males and 23 females) underwent DECT scans in the late arterial phase (AP) and venous phase (VP). We concluded that imaging at an energy level of 65 keV was the most accurate in detecting malignancy in solitary pulmonary nodules (SPNs) measuring ≤30 mm in diameter on virtual monochromatic maps. Both virtual monochromatic images and iodine concentration maps prove to be highly useful in differentiating benign and malignant pulmonary nodules. As for iodine concentration maps, the analysis of venous phase images resulted in the highest clinical usefulness. To summarize, DECT may be a useful tool in the differentiation of benign and malignant SPNs. A single-phase DECT examination with scans acquired 90 s after contrast media injection is recommended.

Focal organizing pneumonia in patients: differentiation from solitary bronchioloalveolar carcinoma using dual-energy spectral computed tomography

OBJECTIVE

To explore the utility of dual-energy spectral computed tomography (CT) in the differential diagnosis of focal organizing pneumonia (FOP) and solitary bronchioloalveolar carcinoma (S-BAC).

MATERIALS AND METHODS

The institutional review board approved this study and waived the requirement for informed consent. It is a retrospective study. A total of 105 patients (62 with FOP and 43 with S-BAC) enrolled and all patients have contrast enhanced spectral CT including the arterial phase (AP) and venous phase (VP). During AP and VP, CT_{40 keV}, CT_{70 keV}, and CT_{100 keV} values, iodine concentration (IC), water concentration (WC), and effective atomic number (Zeff) were measured on monochromatic and iodine-based material decomposition images, and the slope of the spectral curve (λ_Hu) was calculated. The two-sample t-test was used to compare quantitative parameters, and receiver operating characteristic (ROC) curves were generated to calculate diagnostic efficacies.

RESULTS

For AP, CT_{40 keV} and CT_{70 keV} values, IC, WC, Zeff, λ_{70 keV}, and λ_{100 keV} measurements, there were significantly higher in patients with S-BAC than in those with FOP (P < 0.05). However, these quantitative parameters of VP were significantly lower in patients with S-BAC than in those with FOP (P < 0.05). ROC curve analysis revealed that the combination of all quantitative parameters in AP and VP provided the best diagnostic performance in distinguishing S-BAC from FOP (area under the ROC curve, 93.1%; sensitivity, 95.3%; specificity, 77.4%).

CONCLUSIONS

Dual-energy spectral CT has the potential to identify S-BAC and FOP.

Deep learning based spectral extrapolation for dual-source, dual-energy x-ray computed tomography

PURPOSE

Data completion is commonly employed in dual-source, dual-energy computed tomography (CT) when physical or hardware constraints limit the field of view (FoV) covered by one of two imaging chains. Practically, dual-energy data completion is accomplished by estimating missing projection data based on the imaging chain with the full FoV and then by appropriately truncating the analytical reconstruction of the data with the smaller FoV. While this approach works well in many clinical applications, there are applications which would benefit from spectral contrast estimates over the larger FoV (spectral extrapolation)-e.g. model-based iterative reconstruction, contrast-enhanced abdominal imaging of large patients, interior tomography, and combined temporal and spectral imaging.

METHODS

To document the fidelity of spectral extrapolation and to prototype a deep learning algorithm to perform it, we assembled a data set of 50 dual-source, dual-energy abdominal x-ray CT scans (acquired at Duke University Medical Center with 5 Siemens Flash scanners; chain A: 50 cm FoV, 100 kV; chain B: 33 cm FoV, 140 kV + Sn; helical pitch: 0.8). Data sets were reconstructed using ReconCT (v14.1, Siemens Healthineers): 768 × 768 pixels per slice, 50 cm FoV, 0.75 mm slice thickness, "Dual-Energy - WFBP" reconstruction mode with dual-source data completion. A hybrid architecture consisting of a learned piecewise linear transfer function (PLTF) and a convolutional neural network (CNN) was trained using 40 scans (five scans reserved for validation, five for testing). The PLTF learned to map chain A spectral contrast to chain B spectral contrast voxel-wise, performing an image domain analog of dual-source data completion with approximate spectral reweighting. The CNN with its U-net structure then learned to improve the accuracy of chain B contrast estimates by copying chain A structural information, by encoding prior chain A, chain B contrast relationships, and by generalizing feature-contrast associations. Training was supervised, using data from within the 33-cm chain B FoV to optimize and assess network performance.

RESULTS

Extrapolation performance on the testing data confirmed our network's robustness and ability to generalize to unseen data from different patients, yielding maximum extrapolation errors of 26 HU following the PLTF and 7.5 HU following the CNN (averaged per target organ). Degradation of network performance when applied to a geometrically simple phantom confirmed our method's reliance on feature-contrast relationships in correctly inferring spectral contrast. Integrating our image domain spectral extrapolation network into a standard dual-source, dual-energy processing pipeline for Siemens Flash scanner data yielded spectral CT data with adequate fidelity for the generation of both 50 keV monochromatic images and material decomposition images over a 30-cm FoV for chain B when only 20 cm of chain B data were available for spectral extrapolation.

CONCLUSIONS

Even with a moderate amount of training data, deep learning methods are capable of robustly inferring spectral contrast from feature-contrast relationships in spectral CT data, leading to spectral extrapolation performance well beyond what may be expected at face value. Future work reconciling spectral extrapolation results with original projection data is expected to further improve results in outlying and pathological cases.

Reducing contrast dose using virtual monoenergetic imaging for aortic CTA

Three‐dimensional computed tomographic angiography (3D‐CTA) is widely used to evaluate the inner diameters of vessels and the anatomical vascular structure prior to endoscopic aortic surgery or transcatheter valve implantation. Virtual monoenergetic imaging (VMI) is a new application in dual‐energy CT (DECT). We evaluated the potential for contrast dose reduction in preoperative aortic CTA using VMI. To evaluate performance in terms of image quality and vessel shape, we quantified the contrast‐to‐noise ratio (CNR) and the vessel diameter using a cylinder phantom we developed, and used volume rendering to assess visual quality. All VMI had improved CNR values compared with conventional 120 kVp images at an iodine content of 15 mgI/mL. In each image, a virtual mono‐energy of 40 keV yielded the highest CNR value, and an iodine content of 9 mgI/mL was comparable to that of conventional images with an iodine content of 15 mgI/mL. The circularity indices (CI) of the vascular model at 15, 12, and 9 mgI/mL were similar to those of the reference condition using conventional voltages; however, CI was degraded at iodine contents of 6 and 3 mgI/mL with VMI.

In the case of iodine content of 15 mgI/mL, VMI was superior, with conventional image by visual evaluation. In the cases of iodine contents of 12 and 9 mgI/mL, image quality was judged to be almost the same level when comparing 12 and 9 mgI/mL to conventional images. In the case of 6 and 3 mgI/mL, reference image using conventional technique was superior to that of VMI. We demonstrated in that decreasing contrast iodine content is possible using VMI with an energy of 40 keV for preoperative aortic 3D‐CTA.

Spectral CT in Lung Cancer: Usefulness of Iodine Concentration for Evaluation of Tumor Angiogenesis and Prognosis

OBJECTIVE. The purpose of this study was to investigate the correlation between iodine concentration (IC) derived from spectral CT and angiogenesis and the relationships between IC and clinical-pathologic features associated with lung cancer prognosis. SUBJECTS AND METHODS. Sixty patients with lung cancer were enrolled and underwent spectral CT. The IC, IC difference (ICD), and normalized IC (NIC) of tumors were measured in the arterial phase, venous phase (VP), and delayed phase. The microvessel densities (MVDs) of CD34-stained specimens were evaluated. Correlation analysis was performed for IC and MVD. The relationships between the IC index showing the best correlations with MVD and clinical-pathologic findings of pathologic types, histologic differentiation, tumor size, lymph node status, pathologic TNM stage, and intratumoral necrosis were investigated. RESULTS. The mean (± IQR) MVD of all tumors was 42.00 ± 27.50 vessels per field at ×400 magnification, with two MVD distribution types. The MVD of lung cancer correlated positively with the IC, ICD, and NIC on three-phase contrast-enhanced scanning (r range, 0.581-0.800; all p < 0.001), and the IC in the VP showed the strongest correlation with MVD (r = 0.800; p < 0.001). The correlations between IC and MVD, ICD and MVD, and NIC and MVD varied depending on whether the same scanning phase or same IC index was used. The IC in the VP showed statistically significant differences in the pathologic types of adenocarcinoma and squamous cell carcinoma, histologic differentiation, tumor size, and status of intratumoral necrosis of lung cancer (p < 0.05), but was not associated with nodal metastasis and pathologic TNM stages (p > 0.05). CONCLUSION. IC indexes derived from spectral CT, especially the IC in the VP, were useful indicators for evaluating tumor angiogenesis and prognosis.

Gastrografin can be detected in ex vivo biological specimens by dual-energy CT scanning

BACKGROUND

Dual-energy CT is able to distinguish between materials based on differences in X-ray absorption at different X-ray beam energies. The strong k-edge photoelectric effect of materials with a high atomic number makes this modality ideal for identifying iodine-containing compounds. We aim to evaluate dual-energy CT for the detection of Gastrografin (GG) (diatrizoate, Bayer PLC, Reading, UK) enteric contrast medium and validate the conditions for the measurement in ex vivo samples.

METHODS

Dual-energy CT acquisitions were performed to detect Gastrografin in serial dilutions of water, saline and body fluids. We also evaluated the stability of Gastrografin solutions over time at room temperature. Stool specimens were examined to validate the proposed study protocol for clinical applications.

RESULTS

Concentrations as low as 0.2% of Gastrografin were reproducibly detected in vitro and ex vivo samples by DECT, with linear readings ranging from 0.2% to 25% Gastrografin. Gastrografin was shown to be stable in ex vivo biological samples, and there was no difference in detection over time. Gastrografin was detected in stool specimens when administered orally. The detection curves followed the expected saturation effect at high concentrations of iodine.

CONCLUSIONS

Dual-energy CT offers a convenient, quick, reliable and reproducible method for detecting and quantifying the presence of Gastrografin in ex vivo clinical specimens. Biological solutions containing Gastrografin are stable over time. A minimum dilution level of 25% is suggested to avoid beam saturation and inaccurate results.

Semiautomatic Segmentation and Radiomics for Dual-Energy CT: A Pilot Study to Differentiate Benign and Malignant Hepatic Lesions

OBJECTIVE. This study assessed a machine learning-based dual-energy CT (DECT) tumor analysis prototype for semiautomatic segmentation and radiomic analysis of benign and malignant liver lesions seen on contrast-enhanced DECT. MATERIALS AND METHODS. This institutional review board-approved study included 103 adult patients (mean age, 65 ± 15 [SD] years; 53 men, 50 women) with benign (60/103) or malignant (43/103) hepatic lesions on contrast-enhanced dual-source DECT. Most malignant lesions were histologically proven; benign lesions were either stable on follow-up CT or had characteristic benign features on MRI. Low- and high-kilovoltage datasets were deidentified, exported offline, and processed with the DECT tumor analysis for semiautomatic segmentation of the volume and rim of each liver lesion. For each segmentation, contrast enhancement and iodine concentrations as well as radiomic features were derived for different DECT image series. Statistical analyses were performed to determine if DECT tumor analysis and radiomics can differentiate benign from malignant liver lesions. RESULTS. Normalized iodine concentration and mean iodine concentration in the benign and malignant lesions were significantly different (p < 0.0001-0.0084; AUC, 0.695-0.856). Iodine quantification and radiomic features from lesion rims (AUC, ≤ 0.877) had higher accuracy for differentiating liver lesions compared with the values from lesion volumes (AUC, ≤ 0.856). There was no difference in the accuracies of DECT iodine quantification (AUC, 0.91) and radiomics (AUC, 0.90) for characterizing liver lesions. CONCLUSION. DECT radiomics were more accurate than iodine quantification for differentiating solid benign and malignant hepatic lesions.

Combined Dual-Energy and Single-Energy Metal Artifact Reduction Techniques Versus Single-Energy Techniques Alone for Lesion Detection Near an Arthroplasty

OBJECTIVE. The purpose of this study was to compare a combined dual-energy CT (DECT) and single-energy CT (SECT) metal artifact reduction technique with a SECT metal artifact reduction technique for detecting lesions near an arthroplasty in a phantom model. MATERIALS AND METHODS. Two CT phantoms with a cobalt chromium sphere attached to a titanium rod, simulating an arthroplasty, within a background of soft-tissue attenuation containing spherical lesions (range, 10-20 mm) around the head and stem of different attenuations from the background (range of attenuation, 10-70 HU) were scanned with a single CT scanner individually (unilateral) and together (bilateral) with the following three dose-equivalent techniques: the currently used clinical protocol (140 kVp, 300 Reference mAs); 100 kVp; and DECT (100 kVp and 150 kVp with a tin filter). Three radiologists reviewed the datasets to identify lesions. Nonparametric AUC was estimated for each reader with each technique. Multireader ANOVA was performed to compare AUCs. Multiple-variable logistic regression analysis was used to identify factors affecting sensitivity and specificity. RESULTS. Accuracy was lower (p < 0.001) for the DECT 130-keV technique than for the 100-, 70-, and 140-kVp techniques. Sensitivity was higher with unilateral arthroplasties (p = 0.037), with greater contrast differences from background (p < 0.001), and with the SECT 100-kVp technique versus other techniques (p < 0.001). The difference in specificities of modalities was not statistically significant (p = 0.148). CONCLUSION. Combining DECT and SECT techniques does not provide additional benefits for lesion detection as opposed to using SECT alone.

Dual-Energy Computed Tomography for Stone Type Assessment: A Pilot Study of Dual-Energy Computed Tomography with Five Indices

Purpose: To assess the efficacy of dual-energy CT (DECT) in predicting the composition of urinary stones with a single index (dual energy ratio [DER]) and five indices. Methods: Patients undergoing DECT before active urolithiasis treatment were prospectively enrolled in the study. Predictions of stone composition were made based on discriminant analysis with a single index (DER) and five indices (stone density at 80 and 135 kV, Zeff [the effective atomic number of the absorbent material] of the stone, DER, dual-energy index [DEI] and dual-energy difference [DED]). After extraction, stone composition was evaluated by means of physicochemical analyses (X-ray phase analysis, electron microscopy, wet chemistry techniques, and infrared spectroscopy). Results: A total of 91 patients were included. For calcium oxalate monohydrate (COM) stones, the sensitivity, specificity, and overall accuracy of DECT with one index (DER) were 83.3%, 89.8%, and 86.8%, respectively; for calcium oxalate dihydrate (COD) and calcium phosphate stones-88.2%, 92.9%, and 91.2%, respectively; for uric acid stones-0%, 98.8% and 97.8%, respectively; for struvite stones-60%, 95.3%, and 93.4%, respectively. Discriminant analysis with five indices yielded the following sensitivity, specificity, and overall accuracy: 95.2%, 89.8%, and 92.3% for COM stones, 85.3%, 96.4%, and 92.3% for COD stones, and 100% in all three categories for both uric acid and struvite stones. Conclusions: DECT is a promising tool for stone composition assessment. It allowed for evaluation of chemical composition of all stone types with specificity and accuracy ranging from 85% to 100%. Five DECT indices have shown much better diagnostic accuracy compared to a single DECT index.

Metal artifact reduction by monoenergetic extrapolation of dual-energy CT in patients with metallic implants

PURPOSE

The objective of this study is to assess artifact reduction and image quality using dual-energy computed tomography (DECT) and metal artifact reduction techniques in patients with metallic implants.

METHODS

Forty patients with metallic implants, who had targeted CT performed by DECT during March to September 2018, were prospectively recruited. Post-processing with monoenergetic extrapolation at 70 and 150 keV was performed. Forty matched controls with metallic implants with single-energy CT (SECT) performed were selected. Attenuation value, noise, and signal-to-noise ratio (SNR) at the site of maximal artifact were measured at muscle and fat areas. Image quality of three sets of images (70 keV, 150 keV, and SECT) was assessed by two independent reviewers using a 5-point Likert-type scale. Statistical analysis of measured values, Likert-type scales, and radiation doses (volume CT dose index (CTDI_vol)) of DECT and SECT were performed with Mann-Whitney U test.

RESULTS

As compared to SECT, high keV reconstruction of DECT show (1) significantly higher values within muscle and fat surrounding the implant (DECT vs. SECT-muscle: -96 Hounsfield units (HU) vs. -405 HU, fat: -115 HU vs. -301 HU; p < 0.001), (2) significantly lower mean image noise (75 HU vs. 129 HU; p = 0.02), and (3) higher SNR (-0.8 vs. -4.3; p < 0.001). In addition, image quality of high keV reconstruction was rated superior to the other two groups on Likert-type scales ( p < 0.001). The mean radiation doses (CTDI_vol) were comparable between DECT and SECT (14.2 mGy vs. 19.3 mGy; p = 0.08).

CONCLUSION

For patients with metallic implants, monoenergetic extrapolation of DECT at high keV can reduce metal artifacts, increase SNR, and improve qualitative image quality at comparable radiation dose.

Diagnostic Accuracy of Dual-Energy CT in Detection of Acute Pulmonary Embolism: A Systematic Review and Meta-Analysis

PURPOSE

In this systematic review and meta-analysis, we aimed to investigate the accuracy of dual-energy computed tomography (DECT) in the detection of acute pulmonary embolism (PE).

METHODS

We searched Medline (via PubMed), EBSCO, Web of Science, Scopus, and the Cochrane Library for relevant published studies. We selected studies assessing the accuracy of DECT in the detection of PE. Quality assessment of bias and applicability was conducted using the Quality of Diagnostic Accuracy Studies-2 tool. Meta-analysis was performed to calculate mean estimates of sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR). The summary receiver operating characteristic (sROC) curve was drawn to get the Cochran Q-index and the area under the curve (AUC).

RESULTS

Seven studies were included in our systematic review. Of the 182 patients included, 108 patients had PEs. The pooled analysis showed an overall sensitivity and specificity of 88.9% (95% confidence interval [CI]: 81.4%-94.1%) and 94.6% (95% CI: 86.7%-98.5%), respectively. The pooled PLR was 8.186 (95% CI: 3.726-17.986), while the pooled NLR was 0.159 (95% CI: 0.093-0.270). Cochran-Q was 0.8712, and AUC was 0.935 in the sROC curve.

CONCLUSION

Dual-energy computed tomography shows high sensitivity, specificity, and diagnostic accuracy in the detection of acute PE. The high PLR highlights the high clinical importance of DECT as a prevalence-independent, rule-in test. Studies with a larger sample size with standardized reference tests are still needed to increase the statistical power of the study and support these findings.

Utility of Iodine Density Perfusion Maps From Dual-Energy Spectral Detector CT in Evaluating Cardiothoracic Conditions: A Primer for the Radiologist

OBJECTIVE. The purpose of this article is to outline the utility of iodine density maps for evaluating cardiothoracic disease and abnormalities. Multiple studies have shown that the variety of images generated from dual-energy spectral detector CT (SDCT) improve identification of cardiothoracic conditions. CONCLUSION. Understanding the technique of SDCT and being familiar with the features of different cardiothoracic conditions on iodine density map images help the radiologist make a better diagnosis.

Assessing Liver Hemodynamics in Children With Cholestatic Cirrhosis by Use of Dual-Energy Spectral CT

OBJECTIVE. The purpose of this study was to evaluate the value of dual-energy CT (DECT) in assessing liver hemodynamics in children with cholestatic cirrhosis. MATERIALS AND METHODS. The cases of 60 children with cholestatic cirrhosis (study group) and 15 children with inherited metabolic diseases but normal liver function (control group) were retrospectively evaluated. Enhanced CT scans were obtained in spectral imaging mode. Iodine concentration (IC) of hepatic parenchyma in the arterial phase (IC_A) and portal venous phase (IC_P) was measured on iodine-water material decomposition images. The hepatic arterial iodine fraction (AIF) was calculated as: AIF = IC_A / IC_P. The IC_A, IC_P, and AIF of children in the control and study groups were analyzed by one-way ANOVA and post hoc test with Bonferroni correction. The radiation dose was recorded. RESULTS. There were differences in IC_A and AIF between the control and study groups. The values in patients in the Child-Pugh class C group were the highest and those in the control group the lowest (p < 0.05). Statistically significant differences in IC_P were not found (p > 0.05). Specifically, the multiple comparison results indicated that there were differences in both IC_A and AIF in most of the groups (p < 0.05). The volume CT dose index value for all patients was the same at 10.14 mGy for each enhanced phase, and the total dose-length product varied between 402.68 and 679.18 mGy-cm. CONCLUSION. IC_A and AIF obtained at dual-energy CT can be used as semiquantitative indicators to evaluate the liver hemodynamics of children with cholestatic cirrhosis.

Contribution of dual-energy computed tomography in the differentiation of illicit drugs

INTRODUCTION

The objective of this study was to compare the dual-energy behaviour of the main illicit substances as well as their cutting agents in order to be able to differentiate them.

MATERIAL AND METHODS

Cocaine, heroin, MDMA, and cannabis as well as 3 adulterants, 2 diluents, and water were scanned at 90 kV and then at 140 kV on a single X-ray tube computed tomography (CT) scanner. The data acquired enabled a mapping of the attenuation values to 90 and 140 kVp as well as a resulting dual-energy index (DEI) mapping.

RESULTS

Drugs, cocaine, MDMA (pill), and cannabis had a positive DEI (0.014-0.008), while heroin and MDMA (powder) had a negative DEI (-0.016 and -0.013). The DEI of water was -0.01 and that of taurine was -0.018. Adulterants had negative DEI, while diluents had a positive DEI. All DEI were significantly different (p < 0.01).

CONCLUSIONS

Cocaine and heroin can be clearly differentiated using DEI.

[Dual-energy computed tomography in the diagnostics of urolithiasis]

THE AIM

To assess the diagnostic performance of dual-energy computed tomography (DECT) in the evaluation of the composition of urinary stones "in vivo".

MATERIALS AND METHODS

A total of 91 patients aged from 20 to 70 years old (mean 42.7) with urinary stone disease were examined at Sechenov University, including 68 men (75%) and 23 women (25%). Prior to surgery, all patients underwent DECT (Canon, Japan) in order to predict the chemical composition of urinary stones in vivo. Extracorporeal shockwave lithotripsy (ESWL), percutaneous nephrolithotomy (PCNL) and ureteroscopy (URS) was performed in 53 (58.2%), 18 (19.7%) and 20 (22.1%) patients, respectively. Postoperatively, all stones or stone fragments (n=91; 100%) were examined using a comprehensive physical and chemical analysis (X-ray phase analysis, electron microscopy, infrared spectroscopy).

RESULTS

In 6 patients (6.6%) staghorn stones were diagnosed, while in 15 (16.5%), 17 (18.7%), 22 (24.2%) and 31 (34.1%) stones were located in ureteropelvic junction, pelvis and ureter, respectively, including 24 patients with lower ureteric stones (26.4%). Prediction of the stone composition in vivo was carried out on the basis of the one indicator, the dual energy ratio (DER). The threshold values of DER for different types of stones were taken from the literature. All stones were divided into 4 groups according to the DECT results: vevellite stones (n=40, 43.9%), Ca-containing stones without vevellite (n=34, 37.3%), uric acid stones (n=10, 10.9%) and struvite stones (n=7, 7.9%). Thus, when comparing the results of DECT and physical and chemical analysis, in the first group four stones were incorrectly assigned by DECT to the group of Ca-containing stones without vevellite and three stones were incorrectly assigned to the group of struvite stones; in the second group four stones were incorrectly assigned to the group of vevellite stones; in the third group one stone was incorrectly assigned to the group of struvite stones; in the fourth group one stone was incorrectly assigned to the group of vevellite stones and one stone in the group of uric acid stones. In order to increase the diagnostic efficiency of DECT, we performed a comprehensive analysis of five specific DECT indicators (stone density at 135 kV, Z eff of the stone, DER, DEI, DED) using discriminant analysis. Thus, the sensitivity, specificity and overall accuracy of DECT with the use of just one indicator (DER) were 83.3%, 89.8%, 86.8% for vevellite, 88.2%, 92.9%, 91.2% for Ca-containing stones without vevellite, 90%, 98.8%, 97.8% for uric acid stones and 60%, 95.3%, 93.4% for struvite stones, respectively. When using discriminant analysis with five specific DECT indicators, higher values of sensitivity, specificity and overall accuracy were seen: 95.2%, 89.8%, 92.3% for a vevellite, 85,3%, 96,4%, 92,3% for Ca-containing stones without a vevellite and 100%, 100% and 100% for both uric acid and struvite stones, respectively.

CONCLUSIONS

Dual-energy computed tomography is a highly informative method which allows to perform preoperatively the reliable assessment of the chemical composition. DECT in patients with urinary stone disease allows to optimize the treatment strategy and carry out preventive measures on individual basis, taking into account the stone type.

Impact of Dual-Energy CT Postprocessing Protocol for the Detection of Gouty Arthritis and Quantification of Tophi in Patients Presenting With Podagra: Comparison With Ultrasound

OBJECTIVE. The objective of our study was to compare ultrasound (US) tophus and monosodium urate (MSU) deposit detection and US tophus size in the metatarsophalangeal (MTP) 1 joint with dual-energy CT (DECT) using two DECT postprocessing protocols in patients presenting with podagra. SUBJECTS AND METHODS. Seventy-five consecutive patients with podagra (66 men and nine women; mean age, 65.6 years; age range, 33-88 years) and 75 control subjects with MTP 1 joint osteoarthritis (49 men and 26 women; mean age, 63.0 years; age range, 35-87 years) prospectively underwent US and DECT between 2016 and 2018 to assess the MTP 1 joint. Two Syngovia postprocessing DECT protocols with different minimum attenuation thresholds of 150 HU (DECT 150 protocol) versus 120 HU (DECT 120 protocol) and the same maximum attenuation threshold (500 HU) and constant kilovoltage setting of tubes A and B at 80 and 140 kVp were evaluated. Interobserver variability of the two DECT protocols was calculated and compared with that of US. RESULTS. The postprocessing DECT 150 protocol was positive for tophus detection in 55 of 75 patients (73.3%) with podagra, whereas the postprocessing DECT 120 protocol detected MSU deposits in all 75 patients (100%). Tophus size assessed using the DECT 120 protocol showed an improved correlation with tophus size detected on US (p < 0.01). Interobserver variability of DECT was improved when using the DECT 120 protocol (p < 0.01). CONCLUSION. The postprocessing DECT 120 protocol enables improved visualization of MSU deposits and provides more accurate information about tophus size that better correlates with tophus size on US compared with the standard postprocessing DECT 150 protocol.

Feasibility study using iodine quantification on dual-energy CT enterography to distinguish normal small bowel from active inflammatory Crohn's disease

BACKGROUND

Assessment of Crohn's disease (CD) activity is important to identify patients with active inflammation for therapy management. Quantitative analysis can provide objective measurement of disease presence.

PURPOSE

To evaluate the feasibility of quantitative analysis of contrast-enhanced dual-energy computed tomography (DECT) data in detection of small bowel inflammation in patients with CD with an emphasis on iodine quantification.

MATERIAL AND METHODS

DECT enterography was prospectively performed in 20 patients with active CD and in 20 healthy individuals, as the control group. Iodine overlay images were created. Wall thickness, attenuation, absolute iodine density, relative iodine density, and fat fraction were measured in the terminal ileum of all patients by two radiologists. Intraclass correlation coefficients were calculated to assess inter-rater agreement. Parameters were compared between patient groups using mixed model analysis. Receiver operating characteristic (ROC) analysis was performed.

RESULTS

Both absolute and relative iodine density were significantly higher in active disease than in normal small bowel (all P < 0.001). In contrast, measurement of fat fraction was not significantly different in affected terminal ileal loops compared to normal terminal ileum ( P = 0.075). ROC analysis demonstrated a similar excellent diagnostic accuracy of wall thickness, attenuation, and absolute and relative iodine density with area under the ROC curve (AUC) values in the range of 0.96 for attenuation to 1 for relative iodine density.

CONCLUSION

DECT with iodine quantification can be used in distinguishing normal small bowel from active inflammatory CD. Further research should investigate the value of iodine quantification in grading CD activity and in monitoring therapeutic response.

Third generation dual-energy CT with 80/150 Sn kV for head and neck tumor imaging

BACKGROUND

Dual-energy CT (DECT) provides additional image datasets which enable improved tumor delineation or reduction of beam hardening artifacts in patients with head and neck squamous cell carcinoma (SCC).

PURPOSE

To assess radiation dose and image quality of third-generation DECT of the head and neck in comparison to single-energy CT (SECT).

MATERIAL AND METHODS

Thirty patients with SCC who underwent both SECT (reference tube voltage 120 kVp) and DECT (80/150 Sn kVp) of the head and neck region for staging were retrospectively selected. Attenuation measurements of the sternomastoid muscle, internal jugular vein, submandibular gland and tongue were compared. Image noise was assessed at five anatomic levels. Subjective image quality was evaluated by two radiologists in consensus.

RESULTS

CTDI_vol was 55% lower with DECT (4.2 vs. 9.3 mGy; P = 0.002). Median image noise was equal or lower in DECT at all levels (nasopharynx: 3.9 vs. 5.8, P < 0.0001; floor of mouth: 3.6 vs. 4.5, P = 0.0002; arytenoids: 3.6 vs. 3.1, P = 0.096; lower thyroid: 4.4 vs. 5.7, P = 0.002; arch of aorta: 5.6 vs. 6.5, P = 0.001). Attenuation was significantly lower in DECT ( P < 0.05). Subjective image analysis revealed that DECT is equal or superior to SECT with regard to overall image quality (nasopharynx: 5 vs. 5, P = 1; floor of mouth: 5 vs. 5, P = 0.0041; arytenoids: 5 vs. 5, P = 0.6; lower thyroid: 5 vs. 3, P < 0.0001; arch of aorta: 5 vs. 4, P < 0.0001).

CONCLUSION

Head and neck imaging with third-generation DECT can reduce radiation dose by half compared to SECT, while maintaining excellent image quality.

Systematic Review and Meta-Analysis Investigating the Diagnostic Yield of Dual-Energy CT for Renal Mass Assessment

OBJECTIVE. The objective of our study was to perform a systematic review and meta-analysis to evaluate the diagnostic accuracy of dual-energy CT (DECT) for renal mass evaluation. MATERIALS AND METHODS. In March 2018, we searched MEDLINE, Cochrane Database of Systematic Reviews, Embase, and Web of Science databases. Analytic methods were based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Pooled estimates for sensitivity, specificity, and diagnostic odds ratios were calculated for DECT-based virtual monochromatic imaging (VMI) and iodine quantification techniques as well as for conventional attenuation measurements from renal mass CT protocols. I² was used to evaluate heterogeneity. The methodologic quality of the included studies and potential bias were assessed using items from the Quality Assessment Tool for Diagnostic Accuracy Studies 2 (QUADAS-2). RESULTS. Of the 1043 articles initially identified, 13 were selected for inclusion (969 patients, 1193 renal masses). Cumulative data of sensitivity, specificity, and summary diagnostic odds ratio for VMI were 87% (95% CI, 80-92%; I², 92.0%), 93% (95% CI, 90-96%; I², 18.0%), and 183.4 (95% CI, 30.7-1093.4; I², 61.6%), respectively. Cumulative data of sensitivity, specificity, and summary diagnostic odds ratio for iodine quantification were 99% (95% CI, 97-100%; I², 17.6%), 91% (95% CI, 89-94%; I², 84.2%), and 511.5 (95% CI, 217-1201; I², 0%). No significant differences in AUCs were found when comparing iodine quantification to conventional attenuation measurements (p = 0.79). CONCLUSION. DECT yields high accuracy for renal mass evaluation. Determination of iodine content with the iodine quantification technique shows diagnostic accuracy similar to conventional attenuation measurements from renal mass CT protocols. The iodine quantification technique may be used to characterize incidental renal masses when a dedicated renal mass protocol is not available.