Dual-energy CT Reconstruction Research Articles

The potential of iodinated contrast reduction in dual-energy CT thoracic angiography; an evaluation of image quality

IntroductionThe purpose of this study was to compare a dual energy CT (DECT) protocol with 50% reduction of iodinated contrast to a single energy CT (SECT) protocol using standard contrast dose in imaging of the thoracic aorta. MethodsDECT with a 50% reduction in iodinated contrast was compared with SECT. For DECT, monoenergetic images at 50, 55, 60, 65, 68, 70, and 74 keV were reconstructed with adaptive statistical iterative reconstruction (ASiR-V) of 50% and 80%. Objective image quality parameters included intravascular attenuation (HU), image noise (SD), contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR). Two independent radiologists subjectively assessed the image quality for the 55 and 68 keV DECT reconstructions and SECT on a five-point Likert scale. ResultsAcross 14 patients, the intravascular attenuation at 50–55 keV was comparable to SECT (p > 0.05). The CNRs were significantly lower for DECT with ASIR-V 50% compared to SECT for all keV-values (p < 0.05 for all). For ASIR-V 80%, CNR was comparable to SECT at energies below 60 keV (p > 0.05). The subjective image quality was comparable between DECT and SECT independent of keV level. ConclusionThis study indicates that a 50% reduction in iodinated contrast may result in adequate image quality using DECT with monoenergetic reconstructions at lower energy levels for the imaging of the thoracic aorta. The best image quality was obtained for ASiR-V 80% image reconstructions at 55 keV. Implications of practiceDual energy CT with a reduction in iodinated contrast may result in adequate image quality in imaging of the thoracic aorta. However, increased radiation dose may limit the use to patients in which a reduction in fluid and iodinated contrast volume may outweigh this risk.

Acute cholecystitis: diagnostic value of dual-energy CT-derived iodine map and low-keV virtual monoenergetic images.

To compare conventional and dual-energy CT (DECT) for the diagnosis of acute cholecystitis and gangrene. Fifty-seven consecutive adult patients with abdominal pain who underwent IV contrast-enhanced abdominal DECT on a dual-layer (dlDECT) or rapid-switching (rsDECT) scanner from September, 2018 to April, 2021 with cholecystectomy and pathology-confirmed cholecystitis were retrospectively reviewed, and compared with 57 consecutive adult patients without cholecystitis from the same interval scanned with DECT. Images were reviewed independently by two abdominal radiologists with 12 and 16years of experience in two sessions 4weeks apart, blinded to clinical data. Initially, only blended reconstructions (simulating conventional single-energy CT images) were reviewed (CT). Subsequently, CT and DECT reconstructions including low-keV virtual monoenergetic images and iodine maps were reviewed. Gallbladder fossa hyperemia, pericholecystic fluid, subjective presence of gangrene, heterogeneous wall enhancement, sloughed membranes, intramural air, abscess, overall impression of the presence of acute cholecystitis, and intramural iodine density were assessed. Gallbladder fossa hyperemia was detected with increased sensitivity on DECT (R1, 61.4%; R2, 75.4%) vs. CT (R1, 22.8%; R2, 15.8%). DECT showed increased sensitivity for gangrene (R1, 24.6%; R2, 38.6%) vs. CT (R1, 5.3%; R2, 14%), heterogeneous wall enhancement (DECT: R1, 33.3%; R2, 63.2% vs. CT: R1, 7%; R2, 31.6%), and cholecystitis (DECT: R1, 86%; R2, 89.5% vs. CT: R1, 77.2%; R2, 70.2%). In addition, DECT was more sensitive for the detection of acute cholecystitis (R1, 86%; R2, 89.5%) vs. CT (R1, 77.2%; R2, 70.2%). Iodine density threshold of 1.2mg/ml, 0.8mg/mL, and 0.5mg/mL showed specificity for gangrenous cholecystitis of 78.26%, 86.96%, and 95.65%, respectively, using the rsDECT platform. DECT showed improved sensitivity compared to conventional CT for detection of acute cholecystitis. Iodine density measurements may be helpful to diagnose gangrene.

Material decomposition for simulated dual-energy breast computed tomography via hybrid optimization method.

Dual-energy breast CT reconstruction has a potential application that includes separation of microcalcification from healthy breast tissue for assisting early breast cancer detection. To investigate and validate the noise suppression algorithm applied in the decomposition of the simulated breast phantom into microcalcification and healthy breast. The proposed hybrid optimization method (HOM) uses a simultaneous algebraic reconstruction technique (SART) output as a prior image, which is then incorporated into the self-adaptive dictionary learning. This self-adaptive dictionary learning seeks each group of patches to faithfully represent the learned dictionary, and the sparsity and non-local similarity of group patches are used to enforce the image regularization term of the prior image. We simulate a numerical phantom by adding different levels of Gaussian noise to test performance of the proposed method. The mean value of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and root mean square error (RMSE) for the proposed method are (49.043±1.571), (0.997±0.002), (0.003±0.001) and (51.329±1.998), (0.998±0.002), (0.003±0.001) for 35 kVp and 49 kVp, respectively. The PSNR of the proposed method shows greater improvement over TWIST (5.2%), SART (34.6%), FBP (40.4%) and TWIST (3.7%), SART (39.9%), FBP (50.3%) for 35 kVp and 49 kVp energy images, respectively. For the proposed method, the signal-to-noise ratio (SNR) of decomposed normal breast tissue (NBT) is (22.036±1.535), which exceeded that of TWIST, SART, and FBP by 7.5%, 49.6%, and 96.4%, respectively. The results reveal that the proposed algorithm achieves the best performance in both reconstructed and decomposed images under different levels of noise and the performance is due to the high sparsity and good denoising ability of minimization exploited to solve the convex optimization problem. This study demonstrates the potential of applying dual-energy reconstruction in breast CT to detect and separate clustered MCs from healthy breast tissues without noise amplification. Compared to other competing methods, the proposed algorithm achieves the best noise suppression performance for both reconstructed and decomposed images.

Virtual monochromatic dual-energy CT reconstructions improve detection of cerebral infarct in patients with suspicion of stroke

PurposeEarly infarcts are hard to diagnose on non-contrast head CT. Dual-energy CT (DECT) may potentially increase infarct differentiation. The optimal DECT settings for differentiation were identified and evaluated.MethodsOne hundred and twenty-five consecutive patients who presented with suspected acute ischemic stroke (AIS) and underwent non-contrast DECT and subsequent DWI were retrospectively identified. The DWI was used as reference standard. First, virtual monochromatic images (VMI) of 25 patients were reconstructed from 40 to 140 keV and scored by two readers for acute infarct. Sensitivity, specificity, positive, and negative predictive values for infarct detection were compared and a subset of VMI energies were selected. Next, for a separate larger cohort of 100 suspected AIS patients, conventional non-contrast CT (NCT) and selected VMI were scored by two readers for the presence and location of infarct. The same statistics for infarct detection were calculated. Infarct location match was compared per vascular territory. Subgroup analyses were dichotomized by time from last-seen-well to CT imaging.ResultsA total of 80–90 keV VMI were marginally more sensitive (36.3–37.3%) than NCT (32.4%; p > 0.680), with marginally higher specificity (92.2–94.4 vs 91.1%; p > 0.509) for infarct detection. Location match was superior for VMI compared with NCT (28.7–27.4 vs 19.5%; p < 0.010). Within 4.5 h from last-seen-well, 80 keV VMI more accurately detected infarct (58.0 vs 54.0%) and localized infarcts (27.1 vs 11.9%; p = 0.004) than NCT, whereas after 4.5 h, 90 keV VMI was more accurate (69.3 vs 66.3%).ConclusionNon-contrast 80–90 keV VMI best differentiates normal from infarcted brain parenchyma.

Virtual non-enhanced dual-energy CT reconstruction may replace true non-enhanced CT scans in the setting of suspected active hemorrhage

ObjectiveTo assess virtual non-enhanced dual energy computed tomography (DECT) reconstruction as a potential alternative to true non-enhanced thoracic and abdominal CT scans in patients with suspected active hemorrhage. Methods and MaterialsNinety-seven consecutive patients with suspected active bleeding, who underwent routine triphasic CT with intravenous contrast, were included. All patients underwent single energy non-enhanced (TNE) and arterial phase CT as well as venous DECT. Using commercially available software, venous dual energy images were used to generate virtual non-enhanced images (VNE). TNE and VNE were evaluated regarding subjective image quality and diagnostic confidence on a 5-point-scale. The consistency of interpretation with respect to presence and type of hemorrhage between conventional triphasic CT including TNE and biphasic CT with simulated VNE was assessed by two blinded independent readers. ResultsAmong the included subjects (mean age: 66.3 ± 14.5 years, 63.9% male), 37.1% were diagnosed with acute hemorrhage. VNE yielded significantly lower image quality but superior reduction of artefacts as compared to TNE (p ≤ 0.001). Diagnostic confidence was rated high for both TNE and VNE with a significant superiority of TNE (p = 0.003). Triphasic and biphasic CT datasets yielded perfect intrareader agreement regarding presence and type of hemorrhage. The interrater agreement was almost perfect (K = 0.955). Radiation dose was significantly reduced using biphasic dual energy CT with VNE (p ≤ 0.001). ConclusionVirtual non-enhanced images yield comparable diagnostic confidence and perfect agreement with true non-enhanced images for assessment of acute hemorrhage. This suggests that true non-enhanced images could be replaced by virtual non-enhanced images resulting in a significant reduction of radiation dose.

Role of dual energy CT to improve diagnosis of non-traumatic abdominal vascular emergencies.

Computed tomography angiography (CTA) is the modality of choice to evaluate abdominal vascular emergencies (AVE). CTA protocols are often complex and require acquisition of multiple phases to enable a variety of diagnosis such as acute bleeding, pseudoaneurysms, bowel ischemia, and dissection. With single energy CT (SECT), differentiating between calcium, coagulated blood, and contrast agents can be challenging based on their attenuation, especially when in small quantity or present as a mixture. With dual-energy CT (DECT), virtual monoenergetic (VM) and material decomposition (MD) image reconstructions enable more robust tissue characterization, improve contrast-enhancement, and reduce beam hardening artifacts. This article will demonstrate how radiologists can utilize DECT for various clinical scenarios in assessment of non-traumatic AVE.

Applications of Dual-Energy Computed Tomography for the Evaluation of Head and Neck Squamous Cell Carcinoma.

There are multiple emerging applications of dual-energy computed tomography (DECT) for the evaluation of pathology in the head and neck, in particular head and neck squamous cell carcinoma. Studies suggest that DECT image sets reconstructed as supplements to routine diagnostic images may improve lesion visualization, determination of tumor extent, and identification of invasion of critical anatomic structures. This article reviews the evidence for the use and potential advantages of supplementary DECT reconstructions for the evaluation of head and neck squamous cell carcinoma. A summary of potentially useful reconstructions and a suggested approach for multiparametric DECT evaluation of head and neck cancer based on current evidence are presented.

Iterative reconstruction in single-source dual-energy CT angiography: feasibility of low and ultra-low volume contrast medium protocols.

To evaluate the feasibility of using contrast medium (CM) of low and ultra-low volumes and injection rates in aortic CT angiography (CTA) through the joint application of single-source dual-energy CT (ssDECT) and adaptive statistical iterative reconstruction (ASIR). 120 patients with known or suspected aortic dissection underwent aortic CTA and were equally divided into 3 groups. Conventional 120-kVp scan with a CM volume of 70 ml and an injection rate of 5 ml s-1 was performed on Group A. Groups B and C underwent ssDECT scan with CM volumes of 0.6 and 0.4 ml kg-1, respectively. 40% and 50% ASIR algorithms were applied for Groups B and C, respectively. A five-point grading scheme was utilized to subjectively evaluate the image quality, and the CT value and contrast-to-noise ratio were recorded as objective measures. The radiation dose was also evaluated. Groups B and C had equivalent subjective scores and CT values as Group A, whereas they had higher or equivalent contrast-to-noise ratios. Group B had 40.1% and 30% reductions on CM volume and injection rate, respectively, than Group A. Group C further resulted in 19.2% and 22% lesser CM volume and injection rate than Group B. The average effective radiation doses for the study groups were 22.5-24.5% lower than the control group. With the aid of ASIR and ssDECT for aortic CTA, it is feasible to adopt low and ultra-low CM volumes and injection rates while obtaining good quality images. Advances in knowledge: Low and ultra-low CM volumes and injection rates are feasible in CTA through the joint application of ssDECT and ASIR.

Dual-Energy Computed Tomography of the Neck: A Pictorial Review of Normal Anatomy, Variants, and Pathologic Entities Using Different Energy Reconstructions and Material Decomposition Maps.

There is increasing use of dual-energy computed tomography (DECT) for the evaluation of head and neck pathologic entities. Optimal DECT utilization requires familiarity with the appearance of normal tissues variants, and pathologic entities on different DECT reconstructions that may be used in clinical practice. The purpose of this article is to provide a practical, pictorial review of the appearance of normal anatomic structures and different neoplastic and nonneoplastic head and neck pathologic entities on commonly used DECT reconstructions.

Total variation superiorization in dual-energy CT reconstruction for proton therapy treatment planning

Proton therapy is a precise form of radiotherapy in which the range of an energetic beam of protons within a patient must be accurately known. The current approach based on single-energy computed tomography (SECT) can lead to uncertainties in the proton range of approximately 3%. This range of uncertainty may lead to under-dosing of the tumour or over-dosing of healthy tissues. Dual-energy CT (DECT) theoretically has the potential to reduce these range uncertainties by quantifying electron density and the effective atomic number. In practice, however, DECT images reconstructed with filtered backprojection (FBP) tend to suffer from high levels of noise. The objective of the current work was to examine the effect of total variation superiorization (TVS) on proton therapy planning accuracy when compared with FBP. A virtual CT scanner was created with the Monte Carlo toolkit Geant4. Tomographic images were reconstructed with FBP and TVS combined with diagonally relaxed orthogonal projections (TVS-DROP). A total variation minimization (TVM) filter was also applied to the image reconstructed with FBP (FBP-TVM). Quantitative accuracy and variance of proton relative stopping power (RSP) derived from each image set was assessed. Mean RSPs were comparable with each image; however, the standard deviation of pixel values with TVS-DROP was reduced by a factor of 0.44 compared with the FBP image and a factor of 0.66 when compared with the FBP-TVM image. Proton doses calculated with the TVS-DROP image set were also better able to predict a reference dose distribution when compared with the FBP and FBP-TVM image sets. The study demonstrated the potential advantages of TVS-DROP as an image reconstruction method for DECT applied to proton therapy treatment planning.

Dual energy CT with one full scan and a second sparse-view scan using structure preserving iterative reconstruction (SPIR)

Conventional dual-energy CT (DECT) reconstruction requires two full-size projection datasets with two different energy spectra. In this study, we propose an iterative algorithm to enable a new data acquisition scheme which requires one full scan and a second sparse-view scan for potential reduction in imaging dose and engineering cost of DECT. A bilateral filter is calculated as a similarity matrix from the first full-scan CT image to quantify the similarity between any two pixels, which is assumed unchanged on a second CT image since DECT scans are performed on the same object. The second CT image from reduced projections is reconstructed by an iterative algorithm which updates the image by minimizing the total variation of the difference between the image and its filtered image by the similarity matrix under data fidelity constraint. As the redundant structural information of the two CT images is contained in the similarity matrix for CT reconstruction, we refer to the algorithm as structure preserving iterative reconstruction (SPIR). The proposed method is evaluated on both digital and physical phantoms, and is compared with the filtered-backprojection (FBP) method, the conventional total-variation-regularization-based algorithm (TVR) and prior-image-constrained-compressed-sensing (PICCS). SPIR with a second 10-view scan reduces the image noise STD by a factor of one order of magnitude with same spatial resolution as full-view FBP image. SPIR substantially improves over TVR on the reconstruction accuracy of a 10-view scan by decreasing the reconstruction error from 6.18% to 1.33%, and outperforms TVR at 50 and 20-view scans on spatial resolution with a higher frequency at the modulation transfer function value of 10% by an average factor of 4. Compared with the 20-view scan PICCS result, the SPIR image has 7 times lower noise STD with similar spatial resolution. The electron density map obtained from the SPIR-based DECT images with a second 10-view scan has an average error of less than 1%.

SU‐G‐TeP2‐11: Initial Evaluation of a Novel Split‐Filter Dual‐Energy CT for Use in Radiation Oncology

Purpose:To perform an initial evaluation of a novel split‐filter dual‐energy CT (DECT) system with the goal of understanding the clinical utility and limitations of the system for radiation therapy.Methods:Several phantoms were imaged using the split‐filter DECT technique on the Siemens Edge CT scanner using a range of clinically‐relevant doses. The optimum‐contrast reconstruction, the mixed reconstruction, and the monoenergetic reconstructions (ranging from 40 keV to 190 keV) were evaluated. Each image was analyzed for CT number accuracy, uniformity, noise, low‐contrast visibility (LCV), spatial resolution and geometric distortion. For comparison purposes, all parameters were evaluated on 120 kVp single‐energy CT (SECT) scans used for treatment planning, as well as, a sequential‐scan DECT technique for corresponding doses.Results:For all DECT reconstructions no observable geometric distortion was found. Both the optimal‐contrast and mixed images demonstrated slight improvements in LCV and noise when compared to the SECT, and slight reductions in CT number accuracy and spatial resolution. The CT numbers trended as expected for the monoenergetic reconstructions, with CT number accuracy within 50 HU for materials of density &lt;2 g/cm3. Spatial resolution increased with energy, and for monoenergetic reconstructions &gt;70 keV the spatial resolution exceeded that of the SECT. The noise in the monoenergetic reconstructions increased with decreasing energy. Thus, the image uniformity, signal‐to‐noise ratio and LCV were diminished at lower energies (70 keV). Applying iterative reconstruction techniques to the low‐energy images reduced noise and improved LCV. The signal‐to‐noise ratio was stable for energies &gt;100 keV.Conclusion:The initial commissioning of the novel split‐filter DECT technology demonstrated favorable results for clinical implementation. The mixed reconstruction showed potential as a replacement for the treatment planning SECT. The image parameters for the monoenergetic reconstructions varied appropriately with energy. This work provides an initial understanding of the limitations and potential applications for monoenergetic imaging.

WE‐EF‐207‐07: Dual Energy CT with One Full Scan and a Second Sparse‐View Scan Using Structure Preserving Iterative Reconstruction (SPIR)

Purpose:Conventional dual energy CT (DECT) reconstructs CT and basis material images from two full‐size projection datasets with different energy spectra. To relax the data requirement, we propose an iterative DECT reconstruction algorithm using one full scan and a second sparse‐view scan by utilizing redundant structural information of the same object acquired at two different energies.Methods:We first reconstruct a full‐scan CT image using filtered‐backprojection (FBP) algorithm. The material similarities of each pixel with other pixels are calculated by an exponential function about pixel value differences. We assume that the material similarities of pixels remains in the second CT scan, although pixel values may vary. An iterative method is designed to reconstruct the second CT image from reduced projections. Under the data fidelity constraint, the algorithm minimizes the L2 norm of the difference between pixel value and its estimation, which is the average of other pixel values weighted by their similarities. The proposed algorithm, referred to as structure preserving iterative reconstruction (SPIR), is evaluated on physical phantoms.Results:On the Catphan600 phantom, SPIR‐based DECT method with a second 10‐view scan reduces the noise standard deviation of a full‐scan FBP CT reconstruction by a factor of 4 with well‐maintained spatial resolution, while iterative reconstruction using total‐variation regularization (TVR) degrades the spatial resolution at the same noise level. The proposed method achieves less than 1% measurement difference on electron density map compared with the conventional two‐full‐scan DECT. On an anthropomorphic pediatric phantom, our method successfully reconstructs the complicated vertebra structures and decomposes bone and soft tissue.Conclusion:We develop an effective method to reduce the number of views and therefore data acquisition in DECT. We show that SPIR‐based DECT using one full scan and a second 10‐view scan can provide high‐quality DECT images and accurate electron density maps as conventional two‐full‐scan DECT.

Value of monoenergetic dual-energy CT (DECT) for artefact reduction from metallic orthopedic implants in post-mortem studies.

The aim of this ex vivo study was to assess the performance of monoenergetic dual-energy CT (DECT) reconstructions to reduce metal artefacts in bodies with orthopedic devices in comparison with standard single-energy CT (SECT) examinations in forensic imaging. Forensic and clinical impacts of this study are also discussed. Thirty metallic implants in 20 consecutive cadavers with metallic implants underwent both SECT and DECT with a clinically suitable scanning protocol. Extrapolated monoenergetic DECT images at 64, 69, 88, 105, 120, and 130keV and individually adjusted monoenergy for optimized image quality (OPTkeV) were generated. Image quality of the seven monoenergetic images and of the corresponding SECT image was assessed qualitatively and quantitatively by visual rating and measurements of attenuation changes induced by streak artefact. Qualitative and quantitative analyses showed statistically significant differences between monoenergetic DECT extrapolated images and SECT, with improvements in diagnostic assessment in monoenergetic DECT at higher monoenergies. The mean value of OPTkeV was 137.6 ± 4.9 with a range of 130 to 148keV. This study demonstrates that monoenergetic DECT images extrapolated at high energy levels significantly reduce metallic artefacts from orthopedic implants and improve image quality compared to SECT examination in forensic imaging.

CT Liver Imaging: What is New?

This review article aims to bring the reader up to date on advances in liver CT imaging, with an emphasis on the literature from the past year. Recent studies and developments in hepatic imaging using dual-energy CT, perfusion CT, low-tube-voltage imaging, and iterative reconstruction techniques are discussed.

WE‐D‐BRF‐05: Quantitative Dual‐Energy CT Imaging for Proton Stopping Power Computation

Purpose:To extend the two‐parameter separable basis‐vector model (BVM) to estimation of proton stopping power from dual‐energy CT (DECT) imaging.Methods:BVM assumes that the photon cross sections of any unknown material can be represented as a linear combination of the corresponding quantities for two bracketing basis materials. We show that both the electron density (ρe) and mean excitation energy (Iex) can be modeled by BVM, enabling stopping power to be estimated from the Bethe‐Bloch equation. We have implemented an idealized post‐processing dual energy imaging (pDECT) simulation consisting of monogenetic 45 keV and 80 keV scanning beams with polystyrene‐water and water‐CaCl2 solution basis pairs for soft tissues and bony tissues, respectively. The coefficients of 24 standard ICRU tissue compositions were estimated by pDECT. The corresponding ρe, Iex, and stopping power tables were evaluated via BVM and compared to tabulated ICRU 44 reference values.Results:BVM‐based pDECT was found to estimate ρe and Iex with average and maximum errors of 0.5% and 2%, respectively, for the 24 tissues. Proton stopping power values at 175 MeV, show average/maximum errors of 0.8%/1.4%. For adipose, muscle and bone, these errors result range prediction accuracies less than 1%.Conclusion:A new two‐parameter separable DECT model (BVM) for estimating proton stopping power was developed. Compared to competing parametric fit DECT models, BVM has the comparable prediction accuracy without necessitating iterative solution of nonlinear equations or a sample‐dependent empirical relationship between effective atomic number and Iex. Based on the proton BVM, an efficient iterative statistical DECT reconstruction model is under development.

Objective and Subjective Image Quality of Liver Parenchyma and Hepatic Metastases with Virtual Monoenergetic Dual-source Dual-energy CT Reconstructions: An Analysis in Patients with Gastrointestinal Stromal Tumor

To compare in dual-energy CT (DECT) conventionally reconstructed polyenergetic images (PEI) at 120 kVp to virtual monoenergetic images (MEI) at different kiloelectron volt (keV) levels for evaluation of liver and gastrointestinal stromal tumor (GIST) hepatic metastases with regard to objective (IQob) and subjective image quality (IQsub) assessed by two readers of varying experience. Image quality was correlated to patient size and compared between PEI and MEI. From 50 examinations of 17 GIST patients (12 with hepatic metastases) undergoing abdominal dual-source DECT for staging, therapy monitoring or follow-up, PEI and nine MEI in 10-keV intervals from 40 to 120 keV were reconstructed. Liver contrast-to-noise ratios (CNR) and metastasis-to-liver ratios were calculated. MEI reconstructions with the highest IQob were compared to PEI for IQsub by one experienced reader (ER) and one inexperienced reader (IR). Patients' diameters were correlated to IQob and IQsub ratings. MEI at 70 keV had the highest IQob with equal liver CNR and metastasis-to-liver ratio compared to PEI. The ER rated 70-keV MEI and PEI equally high (median 4), whereas the IR rated IQsub best in 70-keV MEI (median 5). Unlike in PEI, IQsub ratings in 70-keV MEI were not correlated to patient size. MEI at 70 keV provided an IQob equivalent to PEI. Regarding the IR, IQsub was improved in 70-keV MEI compared to PEI and less dependent on patient size. Therefore, IRs might improve their diagnostic confidence in the assessment of hepatic GIST metastases by evaluating MEI reconstructions at 70 keV.

Dual Energy CT of the Chest

New generation Dual Source computed tomography (CT) scanners offer different x-ray spectra for Dual Energy imaging. Yet, an objective, manufacturer independent verification of the dose required for the different spectral combinations is lacking. The aim of this study was to assess dose and image noise of 2 different Dual Energy CT settings with reference to a standard chest scan and to compare image noise and contrast to noise ratios (CNR). Also, exact effective dose length products (E/DLP) conversion factors were to be established based on the objectively measured dose. An anthropomorphic Alderson phantom was assembled with thermoluminescent detectors (TLD) and its chest was scanned on a Dual Source CT (Siemens Somatom Definition) in dual energy mode at 140 and 80 kVp with 14 x 1.2 mm collimation. The same was performed on another Dual Source CT (Siemens Somatom Definition Flash) at 140 kVp with 0.8 mm tin filter (Sn) and 100 kVp at 128 x 0.6 mm collimation. Reference scans were obtained at 120 kVp with 64 x 0.6 mm collimation at equivalent CT dose index of 5.4 mGy*cm. Syringes filled with water and 17.5 mg iodine/mL were scanned with the same settings. Dose was calculated from the TLD measurements and the dose length products of the scanner. Image noise was measured in the phantom scans and CNR and spectral contrast were determined in the iodine and water samples. E/DLP conversion factors were calculated as ratio between the measured dose form the TLDs and the dose length product given in the patient protocol. The effective dose measured with TLDs was 2.61, 2.69, and 2.70 mSv, respectively, for the 140/80 kVp, the 140 Sn/100 kVp, and the standard 120 kVp scans. Image noise measured in the average images of the phantom scans was 11.0, 10.7, and 9.9 HU (P > 0.05). The CNR of iodine with optimized image blending was 33.4 at 140/80 kVp, 30.7 at 140Sn/100 kVp and 14.6 at 120 kVp. E/DLP conversion factors were 0.0161 mSv/mGy*cm for the 140/80 kVp protocol, 0.0181 mSv/mGy*cm for the Sn140/100 kVp mode and 0.0180 mSv/mGy*cm for the 120 kVp examination. Dual Energy CT is feasible without additional dose. There is no significant difference in image noise, while CNR can be doubled with optimized dual energy CT reconstructions. A restriction in collimation is required for dose-neutrality at 140/80 kVp, whereas this is not necessary at 140 Sn/100 kVp. Thus, CT can be performed routinely in Dual Energy mode without additional dose or compromises in image quality.

Does Dual-Energy CT of Lower-Extremity Tendons Incur Penalties in Patient Radiation Exposure or Reduced Multiplanar Reconstruction Image Quality?

The purposes of this study were to evaluate the quality and radiation exposure of data acquired with dual-energy CT compared with single-energy MDCT in the depiction of lower-extremity tendons and to assess whether a dual-energy CT voltage exists at which the quality of tendon depiction is optimal. Eleven healthy volunteers and seven clinically referred patients (10 men, eight women; mean age, 43.1 years; range, 20-71 years) underwent conventional single-energy CT and dual-energy CT examinations of both lower extremities with a dual-source CT scanner. Dual-energy reconstructions were made at combined tube voltages approximating 86, 98, 110, 122, and 134 kVp. Quantitative and qualitative analyses were performed on six tendons in each lower extremity, and the findings were compared with single-energy CT findings. The radiation dose involved was recorded in each case. A trend toward increasing tendon attenuation was observed with increasing reconstructed tube voltage. The group of single-energy CT reconstructions proved significantly superior to each of the dual-energy CT reconstructions with regard to signal-to-noise ratio (F = 35.25, p < 0.0001) and contrast-to-noise ratio (F = 37.19, p < 0.0001), although interobserver agreement in subjective ranking was poor. Dual-energy CT had a significantly higher radiation dose (p < 0.05) than single-energy CT. Dual-energy CT of lower-extremity tendons, irrespective of the reconstruction tube voltage chosen, yields multiplanar reformations inferior to those of single-energy CT with regard to signal-to-noise and contrast-to-noise ratios while involving significantly escalated patient exposure to ionizing radiation. Whether the tissue-differentiating promise of dual-energy CT is realized in future studies and warrants such concessions remains to be seen.