Dual-energy CT Imaging Research Articles

Practice variations in salivary gland imaging and utility of virtual unenhanced dual energy CT images for the detection of major salivary gland stones.

Background There are variations in computed tomography (CT) protocols used for evaluating sialolithiasis, with some protocols including acquisitions before and after IV contrast administration. Dual-energy CT (DECT) can be used to generate virtual unenhanced (VUE) images, potentially precluding the need for an uninfused scan. Purpose In this study, we performed a survey in order to assess variations in the imaging approach for sialolithiasis and evaluated the accuracy of DECT VUE images for the detection of salivary stones. Material and Methods Practice variations were evaluated by an online survey of the membership of the American Society of Neuroradiology. We then identified 28 patients with salivary gland calcifications matched with 28 negative controls that had both an unenhanced and a contrast-enhanced acquisition performed as DECT. A total of 123 major salivary gland calcifications and 85 tonsilloliths were evaluated and the true unenhanced series was used as gold standard. Results The survey revealed substantial variations in CT protocols used for sialolithiasis. On a per-patient basis, DECT VUE had 96.4% sensitivity and 100% specificity. On a per-calcification basis, sensitivity and specificity was 100% for stones > 2 mm but dropped for smaller calcifications. The false-negative cases corresponded to clinically insignificant, intra-glandular parotid calcifications. Inter-reader agreement was excellent (0.9256). Conclusion This study confirms that there are significant variations in CT protocols used for evaluation of sialolithiasis. A single contrast-enhanced DECT acquisition with reconstruction of VUE may represent an attractive, streamlined alternative and enable the elimination of the true unenhanced phase and associated radiation exposure.

Dual Energy Spectral CT Imaging in the assessment of Gastric Cancer and cell proliferation: A Preliminary Study

Gastric cancer is one of the main diseases leading to cancer-related death. The recently introduced dual-energy spectral CT (DEsCT), allows to obtain many quantitative measurements from iodine-based material decomposition (MD) images, which contribute to improve the accuracy of staging of GC comparing to multidetector spiral CT. And Ki-67 is a well-recognized nuclear antigen-specific biomarker reflecting cellular proliferation for estimating growth fractions of various tumor types. In the present study we analyzed the features of quantitative measurements (the curve slope (λHU), IC, normalized iodine concentrations (NIC)) obtained from DEsCT and levels of Ki-67 protein expression. We demonstrated that the values between advanced gastric cancer (AGC) and early gastric cancer (EGC) were significantly different both in venous phase (VP) and delayed phase (DP). The values of different level of Ki-67 expression grade were significantly different both in VP and DP. The rank correlation analysis between Ki-67 grade and IC, NIC and λHU values showed significantly positive correlation in VP and DP. These results suggested that quantitative parameters (IC, NIC and λHU) in dual-energy CT imaging can be used to differentiate EGC from AGC, and have significantly positive correlation with Ki-67 antigen expression levels in gastric cancer for indicating tumor cellular proliferation.

Murine vs human tissue compositions: implications of using human tissue compositions for photon energy absorption in mice.

Dual energy CT (DECT) images of 9 female mice were used to extract the effective atomic number Zeff and the relative electron density ρe for each voxel in the images. To investigate the influence of the tissue compositions on the absorbed radiation dose for a typical kilovoltage photon beam, mass energy-absorption coefficients μen/ρ were calculated for 10 different tissues in each mouse. Differences between human and murine tissue compositions can lead to errors around 7.5 % for soft tissues and 20.1 % for bone tissues in μen/ρ values for kilovoltage photon beams. When considering the spread within tissues, these errors can increase up to 17.5 % for soft tissues and 53.9 % for bone tissues within only a single standard deviation away from the mean tissue value. This study illustrates the need for murine reference tissue data. However, assigning only a single mean reference value to an entire tissue can still lead to large errors in dose calculations given the large spread within tissues of μen/ρ values found in this study. Therefore, new methods such as DECT and spectral CT imaging need to be explored, which can be important next steps in improving tissue assignment for dose calculations in small animal radiotherapy. This is the first study that investigates the implications of using human tissue compositions for dose calculations in mice for kilovoltage photon beams.

Gout: Update on Dual-Energy Computed Tomography with Emphasis on Artifact Identification

Gout is the most common inflammatory arthritis and is increasing in prevalence and incidence in many countries worldwide. Accurate diagnosis is important to direct treatment that may include chronic medication. Burden quantification and treatment monitoring are key in the effective care of patients with gout. This review highlights the positive impact of dual-energy computed tomography (DECT) on the evaluation of gout patients and discusses common imaging artifacts that limit this imaging modality. DECT has become the most accurate imaging method for confirming or excluding gout. Of note, however, it has reduced sensitivity in early disease, including initial attacks. Burden quantification is another important role of DECT, which can now be performed using automated software methods, allowing for a more reliable assessment of treatment effect. However, the analysis of gout DECT images can be impeded by artifacts related to the DECT reconstruction technique. DECT is the most sensitive and specific imaging modality for diagnosis, burden quantification, and treatment monitoring in patients with gout. A working knowledge of common DECT artifacts is essential for mitigating their occurance and misinterpretation.

Dual-Energy CT Urography With 50% Reduced Iodine Dose Versus Single-Energy CT Urography With Standard Iodine Dose

The purpose of this study was to compare dual-energy CT (DECT) urography with a 50% reduced iodine dose to single-energy CT (SECT) urography with a standard iodine dose with respect to attenuation of renal vascular and urinary tract structures and with respect to image quality. The study included 62 patients undergoing evaluation of urinary tract lithiasis, tumor, or hematuria. Thirty-one patients underwent DECT urography with a 50% reduced iodine dose and reconstruction at 50 and 77 keV. These subjects were sex, age, and size matched to a group of 31 patients who underwent 120-kVp SECT urography with a standard iodine dose. The mean iodine dose was 22 g for DECT and 44 g for SECT. Attenuation was measured at seven locations in the renal arteries, renal veins, and urinary tract. Two reviewers subjectively scored the image quality parameters image noise, sharpness of urinary tract contours, enhancement of urinary structures, and streak artifacts. Mean DECT attenuation at 50 keV was the same as or greater than SECT attenuation at each of the seven locations. Measured image noise was highest at 50-keV DECT but was the same for 77-keV DECT and 120-kVp SECT. Mean subjective scores for DECT image quality parameters were the same as or higher than those of SECT, except for streak artifact and sharpness of urinary tract contours. DECT urography with a 50% reduced iodine dose may result in measured renal vascular and urinary tract attenuation the same as or higher than and image quality measurements and scores similar to those obtained with 120-kVp SECT urography with a standard iodine dose.

The effect of different image reconstruction techniques on pre-clinical quantitative imaging and dual-energy CT.

To analyse the effect of different image reconstruction techniques on image quality and dual energy CT (DECT) imaging metrics. A software platform for pre-clinical cone beam CT X-ray image reconstruction was built using the open-source reconstruction toolkit. Pre-processed projections were reconstructed with filtered back-projection and iterative algorithms, namely Feldkamp, Davis, and Kress (FDK), Iterative FDK, simultaneous algebraic reconstruction technique (SART), simultaneous iterative reconstruction technique and conjugate gradient. Imaging metrics were quantitatively assessed, using a quality assurance phantom, and DECT analysis was performed to determine the influence of each reconstruction technique on the relative electron density (ρe) and effective atomic number (Zeff) values. Iterative reconstruction had favourable results for the DECT analysis: a significantly smaller spread for each material in the ρe-Zeff space and lower Zeff and ρe residuals (on average 24 and 25% lower, respectively). In terms of image quality assurance, the techniques FDK, Iterative FDK and SART provided acceptable results. The three reconstruction methods showed similar geometric accuracy, uniformity and CT number results. The technique SART had a contrast-to-noise ratio up to 76% higher for solid water and twice as high for Teflon, but resolution was up to 28% lower when compared to the other two techniques. Advanced image reconstruction can be beneficial, but the benefit is small, and calculation times may be unacceptable with current technology. The use of targeted and downscaled reconstruction grids, larger, yet practicable, pixel sizes and GPU are recommended. An iterative CBCT reconstruction platform was build using RTK.

Spot and Diffuse Signs: Quantitative Markers of Intracranial Hematoma Expansion at Dual-Energy CT.

Purpose To compare dual-energy CT with iodine quantification to single-energy CT for evaluation of the spot sign for intracranial hematoma expansion. Materials and Methods In this retrospective study, 42 patients (mean age, 66 years ± 15 [standard deviation]; 19 women) were referred for dual-energy CT assessment of intracranial hemorrhage from October 2014 to January 2017. A machine learning approach (naive Bayes classifier) was used to identify iodine markers of extravasation for risk of hematoma expansion. Specificity and sensitivity of these markers were then independently validated in 65 new patients from February 2017 to February 2018. Results Analysis of dual-energy CT images identified two features of iodine extravasation: total iodine concentration within the hematoma (Ih) and focal iodine concentration in the brightest spot in the hematoma (Ibs) as predictors of expansion. The I2 score derived from these features provided a measure of expansion probability. Optimal classification threshold was an I2 score of 20 (95% confidence interval [CI]: 18, 23), leading to correct identification of 39 of 46 (85%; 95% CI: 71%, 94%) of the hematomas on the training set (sensitivity of 79% [11 of 14; 95% CI: 57%, 100%] and specificity of 88% [28 of 32; 95% CI: 76%, 99%]), and 62 of 70 (89%; 95% CI: 79%, 95%) of the hematomas on the validation set (sensitivity of 71% [10 of 14; 95% CI: 48%, 95%] and specificity of 93% [52 of 56; 95% CI: 86%, 100%]). Sensitivity, specificity, and accuracy of conventional spot sign were, respectively, 57% (eight of 14), 90% (29 of 32), and 80% (37 of 46) on the training set and 57% (eight of 14), 83% (47 of 56), and 75% (53 of 70) on the validation set. Conclusion This study identified two quantitative markers of intracranial hemorrhage expansion at dual-energy CT of the brain. The I2 score derived from these markers highlights the utility of dual-energy CT measurements of iodine content for high sensitivity risk assessment. © RSNA, 2018 Online supplemental material is available for this article.

Axial Spondyloarthritis: Dual-Energy Virtual Noncalcium CT in the Detection of Bone Marrow Edema in the Sacroiliac Joints.

Purpose To determine the diagnostic performance of dual-energy virtual noncalcium (VNCa) CT in the detection of bone marrow edema in study participants with sacroiliitis associated with axial spondyloarthritis. Materials and Methods In this prospective study, 47 consecutive participants (mean age, 27 years; age range, 14-41 years [28 male; mean age, 24 years; age range, 14-37 years] [19 female; mean age, 29 years; age range, 17-41 years]) underwent dual-energy CT and 3.0-T MRI between April 2016 and December 2017. Two independent readers visually evaluated all sacroiliac joints for the presence of abnormal marrow attenuation on dual-energy VNCa images using a four-point classification system (0, no edema; 1, mild edema; 2, moderate edema; 3, severe edema). CT numbers on VNCa images were determined with region-of-interest-based quantitative analysis. MRI was the reference standard for presence of bone marrow edema. Results Sensitivity, specificity, and accuracy of readers 1 and 2, respectively, in the identification of bone edema at CT were 87% and 93% (48 and 51 of 55), 94% and 91% (32 and 31 of 34), and 90% and 92% (80 and 82 of 89). Interobserver agreement was excellent (κ = 0.81). CT numbers from VNCa images increased from no edema to severe edema (P < .001). The area under the receiver operating characteristic curve was 0.93 for reader 1 and 0.91 for reader 2 in differentiation of the presence of bone marrow edema from no edema. A cutoff value of -33 HU derived from reader 1 yielded overall sensitivity, specificity, and accuracy of 90% (49 of 55), 83% (28 of 34), and 87% (77 of 89) in the detection of any extent of edema in the sacroiliac joints. Conclusion Dual-energy VNCa CT images had excellent diagnostic performance in evaluation of the extent of bone marrow edema in study participants with sacroiliitis associated with axial spondyloarthritis. © RSNA, 2018 See also the editorial by Guggenberger in this issue.

Optimal Virtual Monochromatic Image in “Twin-Beam” Imaging of Dual-Energy CT for Head-and-Neck Cancer Radiation Therapy

Monochromatic images synthesized from dual-energy CT (DECT) data have the potential to reduce beam-hardening artifacts and to provide quantitative measurements. The “twin-beam” imaging scheme in DECT is to simultaneously capture two CT images with different energy spectra, which can eliminate patient motion problem between two CT images. The purpose of this study is to investigate the new “twin-beam” imaging scheme of DECT in head-and-neck radiotherapy workflow and choose optimal monochromatic image for organ-at-risk (OAR) delineation in treatment planning. We synthesized monochromatic images at various energies from “twin-beam” DECT images. Specifically, we generated monochromatic images 40 keV to 190 keV at 5keV increment, and totally obtained 30 monochromatic images for each DECT image. We collected the Hounsfield unit (HU) numbers of OARs (brain stem, mandible, spinal cord and parotid glands), the HU numbers of marginal regions outside OARs and the noise levels for each monochromatic image. We then calculated the contrast-to-noise ratio (CNR) for the different OARs at each energy level to generate a serial of spectral curves for each OAR. Based on these spectral curves of CNR, the mono-energy corresponding to the curve peak (max CNR) was identified for each OAR of each patient. The virtual images at these identified mono-energy are the optimal monochromatic images for the delineations of corresponding OARs. Ten head-and-neck cancer patients scanned with the “twin-beam” imaging scheme were used to test the optimal monochromatic image for the delineation of OARs. Based on the maximized CNR, the optimal energy values were 81.86±2.58 keV for brain stem, 75.63±4.96 keV for mandible, 85.00±4.63 keV for spinal cord, and 83.13±2.59 keV for parotid glands. Overall, the optimal energy value for the delineation of these OARs for head-and-neck cancer patients was 81.41±5.12 keV. We have investigated this new “twin-beam” imaging scheme of DECT in head-and-neck radiotherapy workflow and demonstrated its clinical feasibility of choosing optimal virtual monochromatic images for improving OAR delineation in the head-and-neck radiotherapy planning. This could help us enable a stepwise clinical implementation of optimized “twin-beam” protocol for head-and-neck cancer patients, and has the potential to improve head-and-neck radiotherapy.

Bone density measurements adjacent to acetabular cups in total hip arthroplasty using dual-energy CT: an in vivo reliability and agreement study.

BackgroundMeasuring bone mineral density (BMD) around acetabular prosthetic components with computed tomography (CT) is challenged by the complex anatomy and metal artifacts. Three-dimensional (3D) segmentation is required for the analysis, but it is usually not practically applicable on current CT workstationsPurposeTo test the between-scan agreement and reliability of custom segmentation software for BMD measurements adjacent to cemented and uncemented acetabular cups in dual-energy CT (DECT).Material and MethodsTwenty-four male patients with total hip arthroplasty were scanned and rescanned using 130-keV virtual monochromatic DECT images. Hemispherical regions of interest were defined slice-by-slice and BMD was calculated around the acetabular cup using custom segmentation software.ResultsIn the uncemented cup, the mean BMD was 153 mg/cm3 with a between-scan difference of 10 mg/cm3 (P < 0.0001). In the cemented cup, the mean BMD was 186 mg/cm3 with a between-scan difference of 6 mg/cm3 (P = 0.15). In both uncemented and cemented cups the intraclass correlation coefficient between repeated measurements was >0.95 and narrow Bland–Altman Limits of Agreement.ConclusionBMD can be measured with high absolute between-scan agreement and good reliability adjacent to acetabular cemented and uncemented cups using DECT and segmentation software.

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.

Investigating a novel split-filter dual-energy CT technique for improving pancreas tumor visibility for radiation therapy.

PurposeTumor delineation using conventional CT images can be a challenge for pancreatic adenocarcinoma where contrast between the tumor and surrounding healthy tissue is low. This work investigates the ability of a split‐filter dual‐energy CT (DECT) system to improve pancreatic tumor contrast and contrast‐to‐noise ratio (CNR) for radiation therapy treatment planning.Materials and methodsMultiphasic scans of 20 pancreatic tumors were acquired using a split‐filter DECT technique with iodinated contrast medium, OMNIPAQUE TM. Analysis was performed on the pancreatic and portal venous phases for several types of DECT images. Pancreatic gross target volume (GTV) contrast and CNR were calculated and analyzed from mixed 120 kVp‐equivalent images and virtual monoenergetic images (VMI) at 57 and 40 keV. The role of iterative reconstruction on DECT images was also investigated. Paired t‐tests were used to assess the difference in GTV contrast and CNR among the different images.ResultsThe VMIs at 40 keV had a 110% greater image noise compared to the mixed 120 kVp‐equivalent images (P < 0.0001). VMIs at 40 keV increased GTV contrast from 15.9 ± 19.9 HU to 93.7 ± 49.6 HU and CNR from 1.37 ± 2.05 to 3.86 ± 2.78 in comparison to the mixed 120 kVp‐equivalent images. The iterative reconstruction algorithm investigated decreased noise in the VMIs by about 20% and improved CNR by about 30%.ConclusionsPancreatic tumor contrast and CNR were significantly improved using VMIs reconstructed from the split‐filter DECT technique, and the use of iterative reconstruction further improved CNR. This gain in tumor contrast may lead to more accurate tumor delineation for radiation therapy treatment planning.

P015] Contrast of dual energy CT in carotid artery analysis, a phantom study

Purpose Dual Energy Computed Tomography (DECT) has high tissue characterization properties compared to traditional computed tomography (CT). In CT angiography (CTA), this property is important for analyzing the stage of atherosclerosis. The goal of this project was to study the significance of DECT technology in CTA especially for atherosclerosis diagnosis. Methods A self-made phantom was designed to model the neck area and carotid arteries. Main organs in the neck area were built by using various materials. Agar was used to mimic soft tissue, cattle bone to spine, empty plastic bottle to trachea, oil to lipid, and two small plastic tubes to mimic left and right carotid arteries. A human tooth was placed in the phantom to study the artefacts. The artery tubes contained water and diluted iodine as contrast agent. A 300 mg/ml iodine concentration was diluted to 6 mg/ml to meet the image contrast obtained in arteries of the patients using SECT CTA procedure. The phantom was then scanned with CTA SECT and DECT protocols. Images were analyzed using image processing tool. Results Image resulted from DECT show changes in material contrast compared to SECT. The contrast agent, bone, air and tooth have lower HU when scanned with DECT, while water, oil and agar show increased HU values. Improvement in oil contrast is highly visible on DECT image. The artefact from beam hardening effect caused by tooth and bone was reduced significantly by the DECT technology. Conclusions DECT seems to produce better image quality for studying carotid arteries than SECT. DECT images have higher material contrast and lower artefact from beam hardening effect. Both properties are important in atherosclerosis analysis.

Automatic contrast medium extraction system using electron density data with dual-energy CT.

The purpose of the current study is to create a contrast medium extraction method using raw-data-based electron density (rED) and CT number from dual-energy CT (DECT) for automatic delineation of the contrast region. A CT-ED phantom containing tissue-equivalent inserts and an acrylic phantom with an iodinated contrast medium were scanned by DECT. The contrast medium extraction system was created using Python. The accuracy of the contrast medium extraction was evaluated by measuring the diameter in terms of the full width at half maximum (FWHM) and the ratio of the volume (ROV). Mean-2SD CT numbers and the difference of the CT numbers (DCT) of the contrast medium at 0-130mgml-1 contrast medium concentration and the bone materials were more than -33 and -20 HU, respectively. In the correlation of rED and CT number, the gradient with the contrast medium phantom was greater than that with the CT-ED phantom. The accuracy of the contrast medium at 80 kV/135 kV and 100 kV/135 kV tube voltages. The gradient of the CT-ED and contrast medium phantoms were different. The gradient in the CT-ED phantom and the contrast medium was 0.0012 and 0.0003 at 80 kV/135 kV, and 0.0015 and 0.0005 at 100 kV/135 kV tube voltages, respectively. The ratio of the measured to the actual diameter in FWHM and ROV was 0.98-1.00 at 2-130 mg ml-1. At a tube voltage of 100 kV/135 kV. The ratio of the measured to the actual diameter in ROV was 0.66 and FWHM was 0.90 at 2mgml-1 contrast medium concentration. The ratio of the measured to the actual diameter in FWHM and ROV was 0.98-1.00 at 3-130 mg ml-1. We created the contrast medium extraction method with rED and CT number images. The contrast medium extraction method could be used with DECT images at 80 kV/135 kV. The method is expected to only extract images from the region containing the contrast medium. We created the contrast medium extraction method using raw-data-based electron density and CT number from DECT and it is expected to only extract information from the region containing the contrast medium.

Dual-Energy Computed Tomography-Based Display of Bone Marrow Edema in Incidental Vertebral Compression Fractures: Diagnostic Accuracy and Characterization in Oncological Patients Undergoing Routine Staging Computed Tomography.

The aim of this study was to evaluate the diagnostic performance of virtual noncalcium (VNCa) dual-energy computed tomography (DECT) reconstructions enabling visualization of bone marrow edema for characterization of incidental thoracolumbar compression fractures in routine thoracoabdominal staging computed tomography (CT). We retrospectively analyzed 51 oncological patients without suspected fracture or indicative complaints presenting at least 1 thoracolumbar compression fracture on routine thoracoabdominal staging DECT who had been examined between October 2015 and June 2017 using third-generation dual-source CT, had a previous CT within 3 months before, and also had undergone additional magnetic resonance imaging within 14 days, which served as the standard of reference. Three independent and blinded radiologists initially evaluated all vertebrae on conventional grayscale DECT series; after at least 8 weeks, observers reevaluated all cases using grayscale and color-coded VNCa DECT images. The age of each fracture was determined as either acute, chronic, or inconclusive. Specificity, sensitivity, and intraobserver and interobserver agreements were calculated taking into account clustering. A total of 98 vertebral compression fractures were detected in 51 patients (20 women, 31 men; median of 1 fracture per patient). The reference standard defined 45 as acute and 53 as chronic. For identification of only acute fractures (cutoff 1), the combination of grayscale and VNCa image series showed a higher sensitivity (91% vs 47%; P < 0.001) but equal specificity (both 100%) compared with analysis of grayscale images alone. When defining a positive finding as a fracture considered either acute or inconclusive (cutoff 2), combined analysis of grayscale and VNCa images showed similar sensitivity (96% vs 93%; P = 0.28) but significantly higher specificity (96% vs 75%; P < 0.001) compared with evaluation of grayscale images alone. Area under the curve analysis for detection of vertebral compression fractures showed superior results for reading of grayscale and VNCa image series (0.98) compared with analysis of grayscale images alone (0.89; P < 0.001). Dual-energy CT-derived color-coded VNCa reconstructions substantially improve the characterization of incidental thoracolumbar compression fractures seen on routine thoracoabdominal staging DECT by allowing for visualization of bone marrow edema.

The acceleration algorithm for projection decomposition of dual-energy computed tomography image reconstruction based on projection matching

Dual-energy computed tomography (CT) reconstruction imaging technology is an important development direction in the field of CT imaging. The mainstream model of dual-energy CT reconstruction algorithm is the basis material decomposition model, and the projection decomposition is the crucial technique. The projection decomposition algorithm based on projection matching was a general method. With establishing the energy spectrum lookup table, we can obtain the stable solution by the least squares matching method. But the computation cost will increase dramatically when size of lookup table enlarges and it will slow down the computer. In this paper, an acceleration algorithm based on projection matching is proposed. The proposed algorithm makes use of linear equations and plane equations to fit the lookup table data, so that the projection value of the decomposition coefficients can be calculated quickly. As the result of simulation experiment, the acceleration algorithm can greatly shorten the running time of the program to get the stable and correct solution.

Histogram-pattern analysis of the lung perfused blood volume for assessment of pulmonary thromboembolism.

We aimed to evaluate the usefulness of histograms of lung perfused blood volume (HLPBV) based on the presence of pulmonary thromboembolism (PTE) and the pulmonary embolic burden. A total of 168 patients (55 males; mean age, 62.9 years) underwent contrast-enhanced dual-energy computed tomography (DECT) between January 1 2012 and October 31 2014. Initial DECT images were three-dimensionally reconstructed, and the HLPBV patterns were divided into three types, including the symmetric type (131 patients, 78.0%), gradual type (25 patients, 14.9%), and asymmetric type (12 patients, 7.1%). Acute PTE was diagnosed in all 12 patients with asymmetric type (100%), 19 of the 25 patients with gradual type (76%) and 24 of the 131 patients with symmetric type (18.3%). HLPBV pattern exhibited correlations with the right/left ventricular diameter ratio (r=0.36, P = 0.007) and CT obstruction index (r=0.63, P < 0.001) in patients with PTEs. When the gradual and asymmetric types were regarded as positive for PTE, the specificity, positive predictive value, negative predictive value, and accuracy were 92.9%, 83.8%, 87.6%, and 81.0%, respectively. Histogram-pattern analysis using DECT might be a useful application to diagnose PTE.

Monte Carlo proton dose calculations using a radiotherapy specific dual-energy CT scanner for tissue segmentation and range assessment

Proton beam ranges derived from dual-energy computed tomography (DECT) images from a dual-spiral radiotherapy (RT)-specific CT scanner were assessed using Monte Carlo (MC) dose calculations. Images from a dual-source and a twin-beam DECT scanner were also used to establish a comparison to the RT-specific scanner. Proton ranges extracted from conventional single-energy CT (SECT) were additionally performed to benchmark against literature values. Using two phantoms, a DECT methodology was tested as input for Geant4 MC proton dose calculations. Proton ranges were calculated for different mono-energetic proton beams irradiating both phantoms; the results were compared to the ground truth based on the phantom compositions. The same methodology was applied in a head-and-neck cancer patient using both SECT and dual-spiral DECT scans from the RT-specific scanner. A pencil-beam-scanning plan was designed, which was subsequently optimized by MC dose calculations, and differences in proton range for the different image-based simulations were assessed. For phantoms, the DECT method yielded overall better material segmentation with >86% of the voxel correctly assigned for the dual-spiral and dual-source scanners, but only 64% for a twin-beam scanner. For the calibration phantom, the dual-spiral scanner yielded range errors below 1.2 mm (0.6% of range), like the errors yielded by the dual-source scanner (<1.1 mm, <0.5%). With the validation phantom, the dual-spiral scanner yielded errors below 0.8 mm (0.9%), whereas SECT yielded errors up to 1.6 mm (2%). For the patient case, where the absolute truth was missing, proton range differences between DECT and SECT were on average in −1.2 ± 1.2 mm (−0.5% ± 0.5%). MC dose calculations were successfully performed on DECT images, where the dual-spiral scanner resulted in media segmentation and range accuracy as good as the dual-source CT. In the patient, the various methods showed relevant range differences.

A unified material decomposition framework for quantitative dual‐ and triple‐energy CT imaging

Many clinical applications depend critically on the accurate differentiation and classification of different types of materials in patient anatomy. This work introduces a unified framework for accurate nonlinear material decomposition and applies it, for the first time, in the concept of triple-energy CT (TECT) for enhanced material differentiation and classification as well as dual-energy CT (DECT). We express polychromatic projection into a linear combination of line integrals of material-selective images. The material decomposition is then turned into a problem of minimizing the least-squares difference between measured and estimated CT projections. The optimization problem is solved iteratively by updating the line integrals. The proposed technique is evaluated by using several numerical phantom measurements under different scanning protocols. The triple-energy data acquisition is implemented at the scales of micro-CT and clinical CT imaging with commercial "TwinBeam" dual-source DECT configuration and a fast kV switching DECT configuration. Material decomposition and quantitative comparison with a photon counting detector and with the presence of a bow-tie filter are also performed. The proposed method provides quantitative material- and energy-selective images examining realistic configurations for both DECT and TECT measurements. Compared to the polychromatic kV CT images, virtual monochromatic images show superior image quality. For the mouse phantom, quantitative measurements show that the differences between gadodiamide and iodine concentrations obtained using TECT and idealized photon counting CT (PCCT) are smaller than 8 and 1mg/mL, respectively. TECT outperforms DECT for multicontrast CT imaging and is robust with respect to spectrum estimation. For the thorax phantom, the differences between the concentrations of the contrast map and the corresponding true reference values are smaller than 7mg/mL for all of the realistic configurations. A unified framework for both DECT and TECT imaging has been established for the accurate extraction of material compositions using currently available commercial DECT configurations. The novel technique is promising to provide an urgently needed solution for several CT-based diagnostic and therapy applications, especially for the diagnosis of cardiovascular and abdominal diseases where multicontrast imaging is involved.

Development of a Dual-Energy Computed Tomography-Based Segmentation Method for Collateral Ligaments: A Porcine Knee Model

The clinical value of dual-energy computed tomography (DECT) has gradually been recognized in many applications. In particular, DECT offers a new imaging method to improve the visualization of ligaments and tendons. However, limitations such as two-dimensional display and manual window adjustment hamper the evaluation of knee ligament injuries. In this study, we proposed a method to segment collateral ligaments from DECT images automatically. Based on various segmentation techniques, collateral ligaments can be visualized using the three-dimensional (3D) volume-rendering technique. To validate our methodology, we used a porcine knee model and focused on the detection of the medial collateral ligament (MCL) and lateral collateral ligament (LCL). Twenty porcine hind legs were scanned using DECT after specimens underwent surgery to cut either the MCL or the LCL. Using the proposed method, either a complete or a partial LCL rupture could be detected clearly, and a complete MCL rupture could be shown clearly. However, some cases might present some difficulty in identifying a partial MCL rupture since the MCL is a thin ligament. The proposed method can be used to automatically segment the main ligaments of the knee. In addition, the 3D volume rendering image makes DECT a valuable tool for the diagnosis of knee ligament injuries.