Cervical and Cranial Computed Tomographic Angiography With Automated Bone Removal: Dual Energy Computed Tomography Versus Standard Computed Tomography

Application and optimization of the U-Net++ model for cerebral artery segmentation based on computed tomographic angiography images

Accurate segmentation of cerebral arteries on computed tomography angiography (CTA) images is essential for the diagnosis and management of cerebrovascular diseases, including ischemic stroke. This study implemented a deep learning-based U-Net++ model for cerebral artery segmentation in CTA images, focusing on optimizing pruning levels by analyzing the trade-off between segmentation performance and computational cost. Dual-energy CTA and direct subtraction CTA datasets were utilized to segment the internal carotid and vertebral arteries in close proximity to the bone. We implemented four pruning levels (L1-L4) in the U-Net++ model and evaluated the segmentation performance using accuracy, intersection over union, F1-score, boundary F1-score, and Hausdorff distance. Statistical analyses were conducted to assess the significance of segmentation performance differences across pruning levels. In addition, we measured training and inference times to evaluate the trade-off between segmentation performance and computational efficiency. Applying deep supervision improved segmentation performance across all factors. While the L4 pruning level achieved the highest segmentation performance, L3 significantly reduced training and inference times (by an average of 51.56 % and 22.62 %, respectively), while incurring only a small decrease in segmentation performance (7.08 %) compared to L4. These results suggest that L3 achieves an optimal balance between performance and computational cost. This study demonstrates that pruning levels in U-Net++ models can be optimized to reduce computational cost while maintaining effective segmentation performance. By simplifying deep learning models, this approach can improve the efficiency of cerebrovascular segmentation, contributing to faster and more accurate diagnoses in clinical settings.

The Impact of Weighting Factors on Dual-Energy Computed Tomography Image Quality in Non-Contrast Head Examinations: Phantom and Patient Study

Background: This study aims to evaluate the impact of various weighting factors (WFs) on the quality of weighted average (WA) dual-energy computed tomography (DECT) non-contrast brain images and to determine the optimal WF value. Because they simulate standard CT images, 0.4-WA reconstructions are routinely used. Methods: In the initial phase of the research, quantitative and qualitative analyses of WA DECT images of an anthropomorphic head phantom, utilizing WFs ranging from 0 to 1 in 0.1 increments, were conducted. Based on the phantom study findings, WFs of 0.4, 0.6, and 0.8 were chosen for patient analyses, which were identically carried out on 85 patients who underwent non-contrast head DECT. Three radiologists performed subjective phantom and patient analyses. Results: Quantitative phantom image analysis revealed the best gray-to-white matter contrast-to-noise ratio (CNR) at the highest WFs and minimal noise artifacts at the lowest WF values. However, the WA reconstructions were deemed non-diagnostic by all three readers. Two readers found 0.6-WA patient reconstructions significantly superior to 0.4-WA images (p < 0.001), while reader 1 found them to be equally good (p = 0.871). All readers agreed that 0.8-WA images exhibited the lowest image quality. Conclusions: In conclusion, 0.6-WA reconstructions demonstrated superior image quality over 0.4-WA and are recommended for routine non-contrast brain DECT.

Utility of Dual-Energy Computed Tomography in Clinical Conundra

Advancing medical technology revolutionizes our ability to diagnose various disease processes. Conventional Single-Energy Computed Tomography (SECT) has multiple inherent limitations for providing definite diagnoses in certain clinical contexts. Dual-Energy Computed Tomography (DECT) has been in use since 2006 and has constantly evolved providing various applications to assist radiologists in reaching certain diagnoses SECT is rather unable to identify. DECT may also complement the role of SECT by supporting radiologists to confidently make diagnoses in certain clinically challenging scenarios. In this review article, we briefly describe the principles of X-ray attenuation. We detail principles for DECT and describe multiple systems associated with this technology. We describe various DECT techniques and algorithms including virtual monoenergetic imaging (VMI), virtual non-contrast (VNC) imaging, Iodine quantification techniques including Iodine overlay map (IOM), and two- and three-material decomposition algorithms that can be utilized to demonstrate a multitude of pathologies. Lastly, we provide our readers commentary on examples pertaining to the practical implementation of DECT's diverse techniques in the Gastrointestinal, Genitourinary, Biliary, Musculoskeletal, and Neuroradiology systems.

A Locally Weighted Linear Regression Look-Up Table-Based Iterative Reconstruction Method for Dual Spectral CT

OBJECTIVE

Compared with traditional computed tomography (CT), dual spectral CT (DSCT) exhibits superior material distinguishability and thus has broad prospects in industrial and medical fields. In iterative DSCT algorithms, accurately modeling forward-projection functions is crucial, but it is very difficult to analytically provide accurate functions.

METHODS

In this article, we propose a locally weighted linear regression look-up table-based (LWLR-LUT) iterative reconstruction method for DSCT. First, the proposed method uses LWLR to establish LUTs for the forward-projection functions through calibration phantoms, achieving good local information calibration. Second, the reconstructed images can be iteratively obtained through the established LUTs. The proposed method not only does not require knowledge of the X-ray spectra and the attenuation coefficients, but also implicitly accounts for some scattered radiation while fitting locally the forward-projection functions in the calibration space.

RESULTS

Both numerical simulations and real data experiments demonstrate that the proposed method can achieve highly accurate polychromatic forward-projection functions and greatly improve the quality of the images reconstructed from scattering-free and scattering projections.

CONCLUSION

The proposed method is simple and practical, and achieves good material decomposition effects for objects with different complex structures through simple calibration phantoms.

Vascular Applications of Dual-Energy Computed Tomography

Dual- or multi-energy CT imaging provides several advantages over conventional CT in the context of vascular imaging. Specific advantages include the use of low-energy virtual monoenergetic images (VMIs) to boost iodine attenuation to salvage suboptimal enhanced studies, perform low-contrast material dose studies, and increase conspicuity of small vessels and lesions. Alternatively, high-energy VMIs reduce artifacts caused by some metals, endoprosthesis, calcium blooming, and beam hardening. Virtual non-contrast (VNC) images reduce radiation dose by eliminating the need for a true non-contrast acquisition in multiphasic CT studies. Iodine maps can be used to evaluate perfusion of tissues and lesions.

Imaging Approach to Venous Sinus Thrombosis

Cerebral venous thrombosis (CVT) is a rare cerebrovascular disease caused by an occlusion of the cerebral venous sinuses or cortical veins. It has a favorable prognosis if diagnosed and treated early. CVT can be difficult to diagnose on clinical grounds, and imaging plays a key role. We discuss clinical features and provide an overview of current neuroimaging methods and findings in CTV.

An iterative reconstruction method based on monochromatic images for dual energy CT

PURPOSE

Dual-energy computed tomography (DECT) scans objects using two different X-ray spectra to acquire more information, which is also called dual spectral CT (DSCT) in some articles. Compared to traditional CT, DECT exhibits superior material distinguishability. Therefore, DECT can be widely used in the medical and industrial domains. However, owing to the nonlinearity and ill condition of DECT, studies are underway on DECT reconstruction to obtain high quality images and achieve fast convergence speed. Therefore, in this study, we propose an iterative reconstruction method based on monochromatic images (IRM-MI) to rapidly obtain high-quality images in DECT reconstruction.

METHODS

An IRM-MI is proposed for DECT. The proposed method converts DECT reconstruction problem from the basis material images decomposition to monochromatic images decomposition to significantly improve the convergence speed of DECT reconstruction by changing the coefficient matrix of the original equations to increase the angle of the high- and low-energy projection curves or reduce the condition number of the coefficient matrix. The monochromatic images were then decomposed into basis material images. Furthermore, we conducted numerical experiments to evaluate the performance of the proposed method.

RESULTS

The decomposition results of the simulated data and real data experiments confirmed the effectiveness of the proposed method. Compared to the extended algebraic reconstruction technique (E-ART) method, the proposed method exhibited a significant increase in the convergence speed by increasing the angle of polychromatic projection curves or decreasing the condition number of the coefficient matrix, when choosing the appropriate monochromatic images. Therefore, the proposed method is also advantageous in acquiring high quality and rapidly converged images.

CONCLUSIONS

We developed an iterative reconstruction method based on monochromatic images for the material decomposition for DECT. The numerical experiments using the proposed method validated its capability of decomposing the basis material images. Furthermore, the proposed method achieved faster convergence speed compared to the E-ART method.

An oblique projection modification technique (OPMT) for fast multispectral CT reconstruction

In x-ray multispectral (or photon-counting) computed tomography (MCT), the object of interest is scanned under multiple x-ray spectra, and it can acquire more information about the scanned object than conventional CT, in which only one x-ray spectrum is used. The obtained polychromatic projections are utilized to perform material-selective and energy-selective image reconstruction. Compared with the conventional single spectral CT, MCT has a superior material distinguishability. Therefore, it has wide potential applications in both medical and industrial areas. However, the nonlinearity and ill condition of the MCT problem make it difficult to get high-quality and fast convergence of images for existing MCT reconstruction algorithms. In this paper, we proposed an iterative reconstruction algorithm based on an oblique projection modification technique (OPMT) for fast basis material decomposition of MCT. In the case of geometric inconsistency, along the current x-ray path, the oblique projection modification direction not only relates to the polychromatic projection equation of the known spectrum, but it also comprehensively refers to the polychromatic projection equation information of the unknown spectra. Moreover, the ray-by-ray correction makes it applicable to geometrically consistent projection data. One feature of the proposed algorithm is its fast convergence speed. The OPMT considers the information from multiple polychromatic projection equations, which greatly speeds up the convergence of MCT reconstructed images. Another feature of the proposed algorithm is its high flexibility. The ray-by-ray correction will be suitable for any common MCT scanning mode. The proposed algorithm is validated with numerical experiments from both simulated and real data. Compared with the ASD-NC-POCS and E-ART algorithms, the proposed algorithm achieved high-quality reconstructed images while accelerating the convergence speed of them.

Estimating dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network

Dual-energy computed tomography (DECT) is of great significance for clinical practice due to its huge potential to provide material-specific information. However, DECT scanners are usually more expensive than standard single-energy CT (SECT) scanners and thus are less accessible to undeveloped regions. In this paper, we show that the energy-domain correlation and anatomical consistency between standard DECT images can be harnessed by a deep learning model to provide high-performance DECT imaging from fully-sampled low-energy data together with single-view high-energy data. We demonstrate the feasibility of the approach with two independent cohorts (the first cohort including contrast-enhanced DECT scans of 5753 image slices from 22 patients and the second cohort including spectral CT scans without contrast injection of 2463 image slices from other 22 patients) and show its superior performance on DECT applications. The deep-learning-based approach could be useful to further significantly reduce the radiation dose of current premium DECT scanners and has the potential to simplify the hardware of DECT imaging systems and to enable DECT imaging using standard SECT scanners.

Effects of Patient Size and Radiation Dose on Iodine Quantification in Dual-Source Dual-Energy CT

RATIONALE AND OBJECTIVES

The purpose of this study was to investigate the potential effects of patient size and radiation dose on the accuracy of iodine quantification using dual-source dual-energy computed tomography (CT).

MATERIALS AND METHODS

Three phantoms representing different patient sizes were constructed, containing iodine inserts with concentrations from 0 to 20 mg/ml. Dual-energy CT scans were performed at six dose levels from 2 to 30 mGy. Iodine concentrations were measured using a three-material-decomposition algorithm and their accuracy was assessed.

RESULTS

In a small phantom, iodine quantification was accurate and consistent at all dose levels. In a medium phantom, minor underestimations were observed, and the results were consistent except at low dose. In the large phantom, more significant underestimation of iodine concentration was observed at higher doses (≥15 mGy), which was attributed to the beam-hardening effect. At lower doses, increasing upward bias was observed in the CT number, leading to significant overestimations of both iodine concentration and fat fraction, which was attributed to the photon-starvation effect. The severity of the latter effect was determined by mA instead of mAs, suggesting that the electronic noise, rather than the quantum noise, was responsible for the bias. Using higher kVp for the low-energy tube was found to alleviate these effects.

CONCLUSION

Reliable iodine quantification can be achieved using dual-source CT, but the result can be affected by patient size and dose rate. In large patients, biases may occur due to the beam-hardening and the photon-starvation effects, in which case higher dose rate and higher kVp are recommended to minimize these effects.

A sequential regularization based image reconstruction method for limited-angle spectral CT

In spectral computed tomography (CT), the object is respectively scanned under different x-ray spectra. Multiple projection data can be collectively used for reconstructing basis images and virtual monochromatic images, which have been used in material decomposition, beam-hardening correction, bone removal, and so on. In practice, projection data may be obtained in a limited scanning angular range. Images reconstructed from limited-angle data by conventional spectral CT reconstruction methods will be deteriorated by limited-angle related artifacts and basis image decomposition errors. Motivated by observations of limited-angle spectral CT, we propose a sequential regularization-based limited-angle spectral CT reconstruction model and its numerical solver. Both simulated and real data experiments validate that our method is capable of suppressing artifacts, preserving edges and reducing decomposition errors.

Dual energy CT in clinical routine: how it works and how it adds value

Dual energy computed tomography (DECT), also known as spectral CT, refers to advanced CT technology that separately acquires high and low energy X-ray data to enable material characterization applications for substances that exhibit different energy-dependent x-ray absorption behavior. DECT supports a variety of post-processing applications that add value in routine clinical CT imaging, including material selective and virtual non-contrast images using two- and three-material decomposition algorithms, virtual monoenergetic imaging, and other material characterization techniques. Following a review of acquisition and post-processing techniques, we present a case-based approach to highlight the added value of DECT in common clinical scenarios. These scenarios include improved lesion detection, improved lesion characterization, improved ease of interpretation, improved prognostication, inherently more robust imaging protocols to account for unexpected pathology or suboptimal contrast opacification, length of stay reduction, reduced utilization by avoiding unnecessary follow-up examinations, and radiation dose reduction. A brief discussion of post-processing workflow approaches, challenges, and solutions is also included.

CAD-RADS: Pushing the Limits

Coronary CT angiography is now established as the first-line diagnostic imaging test to exclude coronary artery disease (CAD) in the population at low to intermediate risk. Wide variability exists in both the reporting of coronary CT angiography and the interpretation of these reports by referring physicians. The CAD Reporting and Data System (CAD-RADS) is sponsored by multiple societies and is a collaborative effort to provide standard classification of CAD, which is then integrated into patient clinical care. The main goals of the CAD-RADS are to decrease variability among readers; enhance communication between interpreting and referring clinicians, allowing collaborative determination of the best course of patient care; and generate consistent data for auditing, data mining, quality improvement, research, and education. There are several scenarios in which the CAD-RADS guidelines are ambiguous or do not provide definite recommendations for further management of CAD. The authors discuss the CAD-RADS categories and modifiers, highlight a variety of complex or ambiguous scenarios, and provide recommendations for managing these scenarios. Online supplemental material is available for this article. ^©RSNA, 2020 See discussion on this article by Aviram and Wolak.

Applications of dual energy CT in clinical practice: A pictorial essay

In dual-energy CT (DECT), two different x-ray spectra are used to acquire two image datasets of the same region, to allow the analysis of energy-dependent changes in the attenuation of different materials. Each type of material demonstrates a relatively specific change in attenuation between images obtained with a high-energy spectrum and those obtained with a low-energy spectrum. Based on the relatively specific change in attenuation with two different energies, material composition information can be obtained to allow tissue characterization. The DECT ability of material differentiation allows bone removal in various CT angiography studies and bone marrow edema depiction, while with material optimization, metal artefacts can be significantly reduced to almost nil. DECT allows material separation to differentiate uric acid crystals from calcium to determine the composition of urinary calculi and to diagnose gout. Using the DECT ability of material decomposition, iodine maps can be generated, which are useful in the evaluation of any enhancing lesion in the body without the need to obtain a plain scan and allow perfusion maps to be created in cases of pulmonary thromboembolism.

Accurate Iterative FBP Reconstruction Method for Material Decomposition of Dual Energy CT

Compared with traditional CT, dual energy CT (DECT) has the capability to improve material differentiation and reduce beam hardening artifacts, and thus has wide prospects of applications. In this paper, by linearizing the polychromatic projections with their first-order Taylor expansions, we derive an iterative reconstruction method for DECT. The method updates the basis material images by adding the residual images reconstructed from the residual projections to the current estimated basis material images, i.e., the iteration process of the proposed method is carried out in image domain, so it is applicable to both geometrically consistent and inconsistent projections. In addition, as the filtered back-projection method is used in the reconstruction of the residual images, the proposed method has a high degree of parallelism. Both numerical simulation and real-data experiments are performed, and the results confirm the effectiveness of the proposed reconstruction method.

Photon-Counting Computed Tomography for Vascular Imaging of the Head and Neck: First In Vivo Human Results

PURPOSE

The purpose of this study was to evaluate image quality of a spectral photon-counting detector (PCD) computed tomography (CT) system for evaluation of major arteries of the head and neck compared with conventional single-energy CT scans using energy-integrating detectors (EIDs).

METHODS

In this institutional review board-approved study, 16 asymptomatic subjects (7 men) provided informed consent and received both PCD and EID contrast-enhanced CT scans of the head and neck (mean age, 58 years; range, 46-75 years). Tube settings were (EID: 120 kVp/160 mA vs PCD: 140 kVp/108 mA) for all volunteers. Quantitative analysis included measurements of mean attenuation, image noise, and contrast-to-noise ratio (CNR). Spectral PCD data were used to reconstruct virtual monoenergetic images and iodine maps. A head phantom was used to validate iodine concentration measurements in PCD images only. Two radiologists blinded to detector type independently scored the image quality of different segments of the arteries, as well as diagnostic acceptability, image noise, and severity of artifacts of the PCD and EID images. Reproducibility was assessed with intraclass correlation coefficient. Linear mixed models that account for within-subject correlation of analyzed arterial segments were used. Linear regression and Bland-Altman analysis with 95% limits of agreement were used to calculate the accuracy of material decomposition.

RESULTS

Photon-counting detector image quality scores were significantly higher compared with EID image quality scores with lower image noise (P < 0.01) and less image artifacts (P < 0.001). Photon-counting detector image noise was 9.1% lower than EID image noise (8.0 ± 1.3 HU vs 8.8 ± 1.5 HU, respectively, P < 0.001). Arterial segments showed artifacts on EID images due to beam hardening that were not present on PCD images. On PCD images of the head phantom, there was excellent correlation (R = 0.998) between actual and calculated iodine concentrations without significant bias (bias: -0.4 mg/mL [95% limits of agreements: -1.1 to 0.4 mg/mL]). Iodine maps had 20.7% higher CNR compared with nonspectral PCD (65.2 ± 9.0 vs 54.0 ± 4.5, P = 0.01), and virtual monoenergetic image at 70 keV showed similar CNR to nonspectral images (52.6 ± 4.2 vs 54.0 ± 4.5, P = 0.39).

CONCLUSIONS

Photon-counting CT has the potential to improve the image quality of carotid and intracranial CT angiography compared with single-energy EID CT.

Unenhanced Dual-Energy Computed Tomography: Visualization of Brain Edema

PURPOSE

The aim of this study was to determine whether dual-energy computed tomography (DECT) imaging is superior to conventional noncontrast computed tomography (CT) imaging for the detection of acute ischemic stroke.

MATERIALS AND METHODS

This was a retrospective, single-center study of 40 patients who presented to the emergency department (ED) of a major, acute care, teaching center with signs and symptoms of acute stroke. Only those patients who presented to the ED within 4 hours of symptom onset were included in this study. All 40 patients received a noncontrast DECT of the head at the time of presentation. Each patient also received standard noncontrast CT of the head 24 hours after their initial presentation to the ED. "Brain edema" images were then reconstructed using 3-material decomposition with parameters adjusted to suppress gray/white matter contrast while preserving edema and increasing its conspicuity. The initial unenhanced, mixed images, brain edema, and 24-hour follow-up true noncontrast (TNC) images were reviewed and assigned Alberta Stroke Program Early CT scores. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated.

RESULTS

Of the 40 patients, 28 (70%) were diagnosed with an acute infarction. Brain edema reconstructions were better able to predict end infarction volume, with Alberta Stroke Program Early CT scores similar to the 24-hour follow-up TNC CT (7.75 vs 7.7; P > 0.05), whereas the mixed images routinely underestimated the extent of infarction (8.975 vs 7.7; P < 0.001). Initial TNC images had a sensitivity, specificity, PPV, and NPV of 80% (95% confidence interval [CI], 51.9%-95.7%), 72.7% (95% CI, 39%-94%), 80% (95% CI, 51.9%-95.7%), and 72.73% (95% CI, 51.91%-95.67%), respectively. The DECT brain edema images provided a sensitivity, specificity, PPV, and NPV of 93.33% (95% CI, 68.05%-99.83%), 100% (95% CI, 71.51%-100%), 100% (95% CI, 76.84%-100%), and 91.67% (95% CI, 61.52%-99.79%), respectively. There was very good interrater reliability across all 3 imaging techniques.

CONCLUSION

Brain edema reconstructions are able to more accurately detect edema and end-infarct volume as compared with initial TNC images. This provides a better assessment of the degree and extent of infarction and may serve to better guide therapy in the future.

How to Incorporate Dual-Energy Computed Tomography Into Your Neuroradiology Practice: Questions and Answers

Dual-energy computed tomography (DECT) has many current and evolving applications in neuroradiology including material decomposition, improving conspicuity of iodinated contrast enhancement, and artifact reduction. However, there are multiple challenges in incorporating DECT into practice including hardware selection, postprocessing software requirements, technologist and physician training, and numerous workflow issues. This article reviews in a question-and-answer format common issues that arise when incorporating DECT into a busy neuroradiology practice.

Dual-Energy Computed Tomography in Cardiothoracic Vascular Imaging

Dual energy computed tomography is becoming increasingly widespread in clinical practice. It can expand on the traditional density-based data achievable with single energy computed tomography by adding novel applications to help reach a more accurate diagnosis. The implementation of this technology in cardiothoracic vascular imaging allows for improved image contrast, metal artifact reduction, generation of virtual unenhanced images, virtual calcium subtraction techniques, cardiac and pulmonary perfusion evaluation, and plaque characterization. The improved diagnostic performance afforded by dual energy computed tomography is not associated with an increased radiation dose. This review provides an overview of dual energy computed tomography cardiothoracic vascular applications.

Blooming Artifact Reduction in Coronary Artery Calcification by A New De-blooming Algorithm: Initial Study

The aim of this study was to investigate the use of de-blooming algorithm in coronary CT angiography (CCTA) for optimal evaluation of calcified plaques. Calcified plaques were simulated on a coronary vessel phantom and a cardiac motion phantom. Two convolution kernels, standard (STND) and high-definition standard (HD STND), were used for imaging reconstruction. A dedicated de-blooming algorithm was used for imaging processing. We found a smaller bias towards measurement of stenosis using the de-blooming algorithm (STND: bias 24.6% vs 15.0%, range 10.2% to 39.0% vs 4.0% to 25.9%; HD STND: bias 17.9% vs 11.0%, range 8.9% to 30.6% vs 0.5% to 21.5%). With use of de-blooming algorithm, specificity for diagnosing significant stenosis increased from 45.8% to 75.0% (STND), from 62.5% to 83.3% (HD STND); while positive predictive value (PPV) increased from 69.8% to 83.3% (STND), from 76.9% to 88.2% (HD STND). In the patient group, reduction in calcification volume was 48.1 ± 10.3%, reduction in coronary diameter stenosis over calcified plaque was 52.4 ± 24.2%. Our results suggest that the novel de-blooming algorithm could effectively decrease the blooming artifacts caused by coronary calcified plaques, and consequently improve diagnostic accuracy of CCTA in assessing coronary stenosis.

Post-mortem computed tomography: Technical principles and recommended parameter settings for high-resolution imaging

Post-mortem computed tomography (PMCT) has become a standard procedure in many forensic institutes worldwide. However, the standard scan protocols offered by vendors are optimised for clinical radiology and its main considerations regarding computed tomography (CT), namely, radiation exposure and motion artefacts. Thus, these protocols aim at low-dose imaging and fast imaging techniques. However, these considerations are negligible in post-mortem imaging, which allows for significantly increased image quality. Therefore, the parameters have to be adjusted to achieve the best image quality. Several parameters affect the image quality differently and have to be weighed against each other to achieve the best image quality for different diagnostic interests. There are two main groups of parameters that are adjustable by the user: acquisition parameters and reconstruction parameters. Acquisition parameters have to be selected prior to scanning and affect the raw data composition. In contrast, reconstruction parameters affect the calculation of the slice stacks from the raw data. This article describes the CT principles from acquiring image data to post-processing and provides an overview of the significant parameters for increasing the image quality in PMCT. Based on the CT principles, the effects of these parameters on the contrast, noise, resolution and frequently occurring artefacts are described. This article provides a guide for the performance of PMCT in morgues, clinical facilities or private practices.

Dual-Energy Computed Tomography in Stroke Imaging: Technical and Clinical Considerations of Virtual Noncontrast Images for Detection of the Hyperdense Artery Sign

OBJECTIVE

The technical feasibility of virtual noncontrast (VNC) images from dual-energy computed tomography (DECT) for the detection of the hyperdense artery sign (HAS) in ischemic stroke patients was investigated.

METHODS

True noncontrast (TNC) scans of 60 patients either with or without HAS (n = 30 each) were investigated. Clot presence and characteristics were assessed on VNC images from DECT angiography and compared with TNC images. Clot characterization included the level of confidence for diagnosing HAS, a qualitative clot burden score, and quantitative attenuation (Hounsfield unit [HU]) measurements.

RESULTS

Sensitivity, specificity, and accuracy of VNC for diagnosing HAS were 97%, 90%, and 93%, respectively. No significant differences were found regarding the diagnostic confidence (P = 0.18) and clot burden score (P = 0.071). No significant HU differences were found among vessels with HAS in VNC (56 ± 7HU) and TNC (57 ± 8HU) (P = 0.691) images.

CONCLUSIONS

Virtual noncontrast images derived from DECT enable an accurate detection and characterization of HAS.

An Image-Domain Contrast Material Extraction Method for Dual-Energy Computed Tomography

OBJECTIVES

Conventional material decomposition techniques for dual-energy computed tomography (CT) assume mass or volume conservation, where the CT number of each voxel is fully assigned to predefined materials. We present an image-domain contrast material extraction process (CMEP) method that preferentially extracts contrast-producing materials while leaving the remaining image intact.

MATERIALS AND METHODS

Image processing freeware (Fiji) is used to perform consecutive arithmetic operations on a dual-energy ratio map to generate masks, which are then applied to the original images to generate material-specific images. First, a low-energy image is divided by a high-energy image to generate a ratio map. The ratio map is then split into material-specific masks. Ratio intervals known to correspond to particular materials (eg, iodine, calcium) are assigned a multiplier of 1, whereas ratio values in between these intervals are assigned linear gradients from 0 to 1. The masks are then multiplied by an original CT image to produce material-specific images. The method was tested quantitatively at dual-source CT and rapid kVp-switching CT (RSCT) with phantoms using pure and mixed formulations of tungsten, calcium, and iodine. Errors were evaluated by comparing the known material concentrations with those derived from the CMEP material-specific images. Further qualitative evaluation was performed in vivo at RSCT with a rabbit model using identical CMEP parameters to the phantom. Orally administered tungsten, vascularly administered iodine, and skeletal calcium were used as the 3 contrast materials.

RESULTS

All 5 material combinations-tungsten, iodine, and calcium, and mixtures of tungsten-calcium and iodine-calcium-showed distinct dual-energy ratios, largely independent of material concentration at both dual-source CT and RSCT. The CMEP was successful in both phantoms and in vivo. For pure contrast materials in the phantom, the maximum error between the known and CMEP-derived material concentrations was 0.9 mg/mL, 24.9 mg/mL, and 0.4 mg/mL for iodine, calcium, and tungsten respectively. Mixtures of iodine and calcium showed the highest discrepancies, which reflected the sensitivity of iodine to the image-type chosen for the extraction of the final material-specific image. The rabbit model was able to clearly show the 3 extracted material phases, vascular iodine, oral tungsten, and skeletal calcium. Some skeletal calcium was misassigned to the extracted iodine image; however, this did not impede the depiction of the vasculature.

CONCLUSIONS

The CMEP is a straightforward, image-domain approach to extract material signal at dual-energy CT. It has particular value for separation of experimental high-Z contrast elements from conventional iodine contrast or calcium, even when the exact attenuation coefficient profiles of desired contrast materials may be unknown. The CMEP is readily implemented in the image-domain within freeware, and can be adapted for use with images from multiple vendors.

Dual-Energy CT in Emergency Neuroimaging: Added Value and Novel Applications

Dual-energy computed tomography (CT) is a powerful diagnostic tool that is becoming more widely clinically available. Dual-energy CT has the potential to aid in the detection or add diagnostic confidence in the evaluation of a variety of emergent neurologic conditions with use of postprocessing techniques that allow one to take advantage of the different x-ray energy-dependent absorption behaviors of different materials. Differentiating iodine from hemorrhage may help in delineating CT angiographic spot signs, which are small foci of intracranial hemorrhage seen on CT angiograms in cases of acute hemorrhage. Bone subtraction can be used to effectively exclude osseous structures surrounding enhancing vessels at imaging for improved vessel visualization and to create images that are similar in appearance to three-dimensional magnetic resonance imaging vessel reconstructions. Bone subtraction may also be helpful for improving the conspicuity of small extra-axial fluid collections and extra-axial masses. Material characterization can be helpful for clarifying whether small foci of intermediate attenuation represent hemorrhage, calcification, or a foreign material, and it may also be useful for quantifying the amount of hemorrhage or iodine in preexisting or incidentally detected lesions. Virtual monochromatic imaging also can be used to problem solve in challenging cases. ^©RSNA, 2016.

Material Separation Using Dual-Energy CT: Current and Emerging Applications

Dual-energy (DE) computed tomography (CT) offers the opportunity to generate material-specific images on the basis of the atomic number Z and the unique mass attenuation coefficient of a particular material at different x-ray energies. Material-specific images provide qualitative and quantitative information about tissue composition and contrast media distribution. The most significant contribution of DE CT-based material characterization comes from the capability to assess iodine distribution through the creation of an image that exclusively shows iodine. These iodine-specific images increase tissue contrast and amplify subtle differences in attenuation between normal and abnormal tissues, improving lesion detection and characterization in the abdomen. In addition, DE CT enables computational removal of iodine influence from a CT image, generating virtual noncontrast images. Several additional materials, including calcium, fat, and uric acid, can be separated, permitting imaging assessment of metabolic imbalances, elemental deficiencies, and abnormal deposition of materials within tissues. The ability to obtain material-specific images from a single, contrast-enhanced CT acquisition can complement the anatomic knowledge with functional information, and may be used to reduce the radiation dose by decreasing the number of phases in a multiphasic CT examination. DE CT also enables generation of energy-specific and virtual monochromatic images. Clinical applications of DE CT leverage both material-specific images and virtual monochromatic images to expand the current role of CT and overcome several limitations of single-energy CT. (©)RSNA, 2016.

Single Phase Dual-energy CT Angiography: One-stop-shop Tool for Evaluating Aneurysmal Subarachnoid Hemorrhage

Aneurysmal subarachnoid hemorrhages have extremely high case fatality in clinic. Early and rapid identifications of ruptured intracranial aneurysms seem to be especially important. Here we evaluate clinical value of single phase contrast-enhanced dual-energy CT angiograph (DE-CTA) as a one-stop-shop tool in detecting aneurysmal subarachnoid hemorrhage. One hundred and five patients who underwent true non-enhanced CT (TNCT), contrast-enhanced DE-CTA and digital subtraction angiography (DSA) were included. Image quality and detectability of intracranial hemorrhage were evaluated and compared between virtual non-enhanced CT (VNCT) images reconstructed from DE-CTA and TNCT. There was no statistical difference in image quality (P > 0.05) between VNCT and TNCT. The agreement of VNCT and TNCT in detecting intracranial hemorrhage reached 98.1% on a per-patient basis. With DSA as reference standard, sensitivity and specificity on a per-patient were 98.3% and 97.9% for DE-CTA in intracranial aneurysm detection. Effective dose of DE-CTA was reduced by 75.0% compared to conventional digital subtraction CTA. Thus, single phase contrast-enhanced DE-CTA is optimal reliable one-stop-shop tool for detecting intracranial hemorrhage with VNCT and intracranial aneurysms with DE-CTA with substantial radiation dose reduction compared with conventional digital subtraction CTA.

MDCT imaging of traumatic brain injury

The aim of emergency imaging is to detect treatable lesions before secondary neurological damage occurs. CT plays a primary role in the acute setting of head trauma, allowing accurate detection of lesions requiring immediate neurosurgical treatment. CT is also accurate in detecting secondary injuries and is therefore essential in follow-up. This review discusses the main characteristics of primary and secondary brain injuries.

Dual- and Multi-Energy CT: Principles, Technical Approaches, and Clinical Applications

In x-ray computed tomography (CT), materials having different elemental compositions can be represented by identical pixel values on a CT image (ie, CT numbers), depending on the mass density of the material. Thus, the differentiation and classification of different tissue types and contrast agents can be extremely challenging. In dual-energy CT, an additional attenuation measurement is obtained with a second x-ray spectrum (ie, a second "energy"), allowing the differentiation of multiple materials. Alternatively, this allows quantification of the mass density of two or three materials in a mixture with known elemental composition. Recent advances in the use of energy-resolving, photon-counting detectors for CT imaging suggest the ability to acquire data in multiple energy bins, which is expected to further improve the signal-to-noise ratio for material-specific imaging. In this review, the underlying motivation and physical principles of dual- or multi-energy CT are reviewed and each of the current technical approaches is described. In addition, current and evolving clinical applications are introduced.

Dual-Source Dual-Energy CT Angiography of the Supra-Aortic Arteries with Tin Filter: Impact of Tube Voltage Selection

RATIONALE AND OBJECTIVES

Automatic bone and plaque subtraction (BPS) in computed tomographic angiographic (CTA) examinations using dual-energy CT (DECT) remains challenging because of beam-hardening artifacts in the shoulder region and close proximity of the internal carotid artery to the base of the skull. The selection of the tube voltage combination in dual-source CT influences the spectral separation and the susceptibility for artifacts. The purpose of this study was to assess which tube voltage combination leads to an optimal image quality of head and neck DECT angiograms after bone subtraction.

MATERIALS AND METHODS

Fifty-one patients received tin-filter-enhanced DECT angiograms of the supra-aortic arteries using two voltage protocols: 24 patients were studied using 80/Sn140 kV and 27 using a 100/Sn140 kV protocol, both protocols with an additional tin filter. A commercially available DE-CTA BPS algorithm was used. Artificial vessel erosions in BPS maximum intensity projections (four-level Likert scale with CTA source data as reference) and vessel signal-to-noise ratio (SNR) were assessed in the level of the shoulders and the base of the skull in each patient and compared.

RESULTS

At the level of the shoulder, 100/Sn140 kV achieved higher SNR (23.4 ± 6.4 at 80/Sn140 kV vs. 35.1 ± 11.8 at 100/Sn140 kV; P < .0001) with less erosions (erosion score 3.9 ± 0.4 in 80/Sn140 kV vs. 2.1 ± 1.3 in 100/Sn140 kV; P < .0001) than 80/Sn140 kV. At the level of the skull base, erosion scores and objective image quality of arterial segments were comparable with both protocols (P = .14).

CONCLUSIONS

The 100/Sn140 kV protocol achieved more favorable results for BPS of the supra-aortic arteries than the 80/Sn140 kV protocol.

Evaluation of Virtual Noncontrast Images Obtained from Dual-Energy CTA for Diagnosing Subarachnoid Hemorrhage

BACKGROUND AND PURPOSE

The virtual noncontrast images generated with iodine subtraction from dual-energy CTA images are expected to replace the true noncontrast images for radiation-dose reduction. This study assessed the feasibility of virtual noncontrast images for diagnosing SAH.

MATERIALS AND METHODS

Eighty-four patients with or without SAH underwent true noncontrast brain CT (the criterion standard for diagnosing SAH). Among them, 37 patients underwent an additional head dual-energy angiography, and the other patients underwent head and neck dual-energy angiography. Virtual noncontrast images were produced on a dedicated dual-energy postprocessing workstation and reconstructed in orientation and section width identical to those in true noncontrast images. The findings on the virtual noncontrast and true noncontrast images were compared at both the individual level and the lesion level. Image noise of the virtual noncontrast and true noncontrast images was also measured and compared. The volume CT dose index and dose-length product were recorded for the radiation-dose analysis.

RESULTS

The sensitivity, specificity, positive predictive value, and negative predictive value of virtual noncontrast images at the individual level and the lesion level were 94.5%, 100%, 100%, 90.6% and 86.7%, 96.9%, 91.8%, 94.8%, respectively. The agreement in the diagnosis of SAH on true noncontrast and virtual noncontrast images reached 92.3% at the individual level and 85.1% at the lesion level. The virtual noncontrast images showed a higher image noise level. The volume CT dose index and dose-length product were obviously reduced without the true noncontrast brain CT scan.

CONCLUSIONS

Virtual noncontrast images are a reliable tool for diagnosing SAH, with the advantage of reducing the radiation dose.

Dual-Energy CT: What the Neuroradiologist Should Know

Because of the different attenuations of tissues at different energy levels, dual-energy CT offers tissue differentiation and characterization, reduction of artifacts, and remodeling of contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR), hereby creating new opportunities and insights in CT imaging. The applications for dual-energy imaging in neuroradiology are various and still expanding. Automated bone removal is used in CT angiography and CT venography of the intracranial vessels. Monoenergetic reconstructions can be used in patients with or without metal implants in the brain and spine to reduce artifacts, improve CNR and SNR, or to improve iodine conspicuity. Differentiation of iodine and hemorrhage is used in high-density lesions, after intra-arterial recanalization in stroke patients or after administration of contrast media. Detection of underlying (vascular and non-vascular) pathology and spot sign can be used in patients presenting with (acute) intracranial hemorrhage.

Clinical applications of dual-energy CT in head and neck imaging

Dual-energy CT provides insights into the material properties of the tissues and can differentiate between tissues that have similar attenuation on conventional, single energy CT imaging. It has several useful and promising applications in head and neck imaging that an otolaryngologist could use to deliver improved clinical care. These applications include metal artifact reduction, atherosclerotic plaque and tumor characterization, detection of parathyroid lesions, and delineation of paranasal sinus ventilation. Dual-energy CT can potentially improve image quality, reduce radiation dose, and provide specific diagnostic information for certain head and neck lesions. This article reviews some current and potential otolaryngology applications of dual-energy CT.

Dual-energy cone-beam CT with a flat-panel detector: effect of reconstruction algorithm on material classification

PURPOSE

Cone-beam CT (CBCT) with a flat-panel detector (FPD) is finding application in areas such as breast and musculoskeletal imaging, where dual-energy (DE) capabilities offer potential benefit. The authors investigate the accuracy of material classification in DE CBCT using filtered backprojection (FBP) and penalized likelihood (PL) reconstruction and optimize contrast-enhanced DE CBCT of the joints as a function of dose, material concentration, and detail size.

METHODS

Phantoms consisting of a 15 cm diameter water cylinder with solid calcium inserts (50-200 mg/ml, 3-28.4 mm diameter) and solid iodine inserts (2-10 mg/ml, 3-28.4 mm diameter), as well as a cadaveric knee with intra-articular injection of iodine were imaged on a CBCT bench with a Varian 4343 FPD. The low energy (LE) beam was 70 kVp (+0.2 mm Cu), and the high energy (HE) beam was 120 kVp (+0.2 mm Cu, +0.5 mm Ag). Total dose (LE+HE) was varied from 3.1 to 15.6 mGy with equal dose allocation. Image-based DE classification involved a nearest distance classifier in the space of LE versus HE attenuation values. Recognizing the differences in noise between LE and HE beams, the LE and HE data were differentially filtered (in FBP) or regularized (in PL). Both a quadratic (PLQ) and a total-variation penalty (PLTV) were investigated for PL. The performance of DE CBCT material discrimination was quantified in terms of voxelwise specificity, sensitivity, and accuracy.

RESULTS

Noise in the HE image was primarily responsible for classification errors within the contrast inserts, whereas noise in the LE image mainly influenced classification in the surrounding water. For inserts of diameter 28.4 mm, DE CBCT reconstructions were optimized to maximize the total combined accuracy across the range of calcium and iodine concentrations, yielding values of ∼ 88% for FBP and PLQ, and ∼ 95% for PLTV at 3.1 mGy total dose, increasing to ∼ 95% for FBP and PLQ, and ∼ 98% for PLTV at 15.6 mGy total dose. For a fixed iodine concentration of 5 mg/ml and reconstructions maximizing overall accuracy across the range of insert diameters, the minimum diameter classified with accuracy >80% was ∼ 15 mm for FBP and PLQ and ∼ 10 mm for PLTV, improving to ∼ 7 mm for FBP and PLQ and ∼ 3 mm for PLTV at 15.6 mGy. The results indicate similar performance for FBP and PLQ and showed improved classification accuracy with edge-preserving PLTV. A slight preference for increased smoothing of the HE data was found. DE CBCT discrimination of iodine and bone in the knee was demonstrated with FBP and PLTV at 6.2 mGy total dose.

CONCLUSIONS

For iodine concentrations >5 mg/ml and detail size ∼ 20 mm, material classification accuracy of >90% was achieved in DE CBCT with both FBP and PL at total doses <10 mGy. Optimal performance was attained by selection of reconstruction parameters based on the differences in noise between HE and LE data, typically favoring stronger smoothing of the HE data, and by using penalties matched to the imaging task (e.g., edge-preserving PLTV in areas of uniform enhancement).

Peering through the glare: using dual-energy CT to overcome the problem of metal artefacts in bone radiology

OBJECTIVE

Imaging of patients with large metal implants remains one of the most difficult endeavours for radiologists. This article reviews the theory of dual-energy CT (DECT) and its ability to reduce metal artefact, thus enhancing the diagnostic value of musculoskeletal imaging. The strengths, weaknesses, and alternative applications of DECT, as well as areas requiring further research, will also be reviewed.

CONCLUSION

Currently, DECT stands as the frontier for metal artefact reduction in musculoskeletal imaging. DECT requires no additional radiation and provides significantly enhanced image acquisition. When considered along with its other capabilities, DECT is a promising new tool for musculoskeletal and trauma radiologists.

[Modern imaging of kidney tumors]

If a renal mass is suspected on clinical examination or ultrasound the finding has to be confirmed by cross-sectional imaging. Methods that are used include multidetector-row computed tomography (MDCT) and magnetic resonance imaging (MRI). Also contrast-enhanced ultrasound has been successfully implemented in renal imaging and now plays a major role in the differentiation of benign from malignant renal masses. In expert hands it can be used to show very faint vascularization and subtle enhancement. The MDCT technique benefits from the recently introduced dual energy technology that allows superior characterization of renal masses in a single-phase examination, thereby greatly reducing radiation exposure. For young patients and persons allergic to iodine MRI should be used and it provides excellent soft tissue contrast and visualizes contrast enhancement kinetics in multiphase examinations.This article aims at giving a comprehensive overview of these different imaging modalities, their clinical indications and contraindications, as well as a description of imaging findings of various renal masses.

Molecular imaging based on x-ray fluorescent high-Z tracers

We propose a novel x-ray fluorescence imaging setup for the in vivo detection of high-Z tracer distributions. The main novel aspect is the use of an analyzer-based, energy-resolved detection method together with a radial, scatter reducing collimator. The aim of this work is to show the feasibility of this method by measuring the Bragg reflected K-fluorescence signal of an iodine solution sample in a proof of principle experiment and to estimate the potential of the complete imaging setup using a Monte Carlo simulation, including a quantification of the minimal detectable tracer concentration for in vivo imaging. The proof of principle experiment shows that even for a small detector area of approximately 7 mm(2), the collimated and Bragg reflected K-fluorescence signal of a sample containing an iodine solution with a concentration of 50 µg ml(-1) can be detected. The Monte Carlo simulation also shows that the proposed x-ray fluorescence imaging setup has the potential to image distributions of high-Z tracers in vivo at a radiation dose of a few mGy and at tracer concentrations down to 1 µg ml(-1) for iodine in small animals.

Automated subtraction CT angiography for visualization of the whole brain vasculature: a feasibility study

RATIONALE AND OBJECTIVES

To develop an automated computed tomography angiography (CTA) imaging protocol that allows visualization of the whole brain vasculature and evaluate the clinical usefulness of the technique for delineation of intracranial vessels in patients with cerebrovascular disorders.

MATERIALS AND METHODS

We prospectively included 100 patients who underwent automated subtraction CTA for suspected cerebrovascular disorders. The nonenhanced and contrast enhanced scans were obtained with the same table feeding speed. The x-ray tube start angles of the two scans were matched to enable accurate registration and subtraction of the CTA datasets. Subtracted CTA datasets were reformatted as three-dimensional volume rendering and maximum intensity projection images for further review. Two independent readers assessed the quality of subtraction and delineation of intracranial vessels. The visibility of ophthalmic arteries was also assessed.

RESULTS

Subtraction was successful in all patients. The image quality of bone removal was rated excellent in 95 patients, with no or minimal bone remnants. Incomplete bone removal was observed in five patients because of severe motions between the scans. In 97 of 100 patients, arterial segments at the circle of Willis could be clearly visualized. Excellent delineation of bilateral ophthalmic arteries was possible in 81 of 100 patients.

CONCLUSIONS

The whole brain vasculature would be clearly visualized by using the optimized automated CTA protocol. Our automated, single-source, dual-energy subtraction CTA protocol is a fully automated subtraction method that is capable of delineating major intracranial vessels as well as very small arteries.