Conventional Single-energy Computed Tomography Research Articles

AAPM Task Group Report 299: Quality control in multi-energy computed tomography.

Multi-energy computed tomography (MECT) offers the opportunity for advanced visualization, detection, and quantification of select elements (e.g., iodine) or materials (e.g., fat) beyond the capability of standard single-energy computed tomography (CT). However, the use of MECT requires careful consideration as substantially different hardware and software approaches have been used by manufacturers, including different sets of user-selected or hidden parameters that affect the performance and radiation dose of MECT. Another important consideration when designing MECT protocols is appreciation of the specific tasks being performed; for instance, differentiating between two different materials or quantifying a specific element. For a given task, it is imperative to consider both the radiation dose and task-specific image quality requirements. Development of a quality control (QC) program is essential to ensure the accuracy and reproducibility of these MECT applications. Although standard QC procedures have been well established for conventional single-energy CT, the substantial differences between single-energy CT and MECT in terms of system implementations, imaging protocols, and clinical tasks warrant QC tests specific to MECT. This task group was therefore charged with developing a systematic QC program designed to meet the needs of MECT applications. In this report, we review the various MECT approaches that are commercially available, including information about hardware implementation, MECT image types, image reconstruction, and postprocessing techniques that are unique to MECT. We address the requirements for MECT phantoms, review representative commercial MECT phantoms, and offer guidance regarding homemade MECT phantoms. We discuss the development of MECT protocols, which must be designed carefully with proper consideration of MECT technology, imaging task, and radiation dose. We then outline specific recommended QC tests in terms of general image quality, radiation dose, differentiation and quantification tasks, and diagnostic and therapeutic applications.

Synthesis of virtual monoenergetic images from kilovoltage peak images using wavelet loss enhanced CycleGAN for improving radiomics features reproducibility.

Dual-energy computed tomography (CT) can provide a range of image information beyond conventional CT through virtual monoenergetic images (VMIs). The purpose of this study was to investigate the impact of material decomposition in detector-based spectral CT on radiomics features and effectiveness of using deep learning-based image synthesis to improve the reproducibility of radiomics features. In this paper, spectral CT image data from 45 esophageal cancer patients were collected for investigation retrospectively. First, we computed the correlation coefficient of radiomics features between conventional kilovoltage peak (kVp) CT images and VMI. Then, a wavelet loss-enhanced CycleGAN (WLL-CycleGAN) with paired loss terms was developed to synthesize virtual monoenergetic CT images from the corresponding conventional single-energy CT (SECT) images for improving radiomics reproducibility. Finally, the radiomic features in 6 different categories, including gray-level co-occurrence matrix (GLCM), gray-level difference matrix (GLDM), gray-level run-length matrix (GLRLM), gray-level size-zone matrix (GLSZM), neighborhood gray-tone difference matrix (NGTDM), and wavelet, were extracted from the gross tumor volumes from conventional single energy CT, synthetic virtual monoenergetic CT images, and virtual monoenergetic CT images. Comparison between errors in the VMI and synthetic VMI (sVMI) suggested that the performance of our proposed deep learning method improved the radiomic feature accuracy. Material decomposition of dual-layer dual-energy CT (DECT) can substantially influence the reproducibility of the radiomic features, and the degree of impact is feature dependent. The average reduction of radiomics errors for 15 patients in testing sets was 96.9% for first-order, 12.1% for GLCM, 12.9% for GLDM, 15.7% for GLRLM, 50.3% for GLSZM, 53.4% for NGTDM, and 6% for wavelet features. The work revealed that material decomposition has a significant effect on the radiomic feature values. The deep learning-based method reduced the influence of material decomposition in VMIs and might improve the robustness and reproducibility of radiomic features in esophageal cancer. Quantitative results demonstrated that our proposed wavelet loss-enhanced paired CycleGAN outperforms the original CycleGAN.

Improved GAN: Using a transformer module generator approach for material decomposition

Dual-energy computed tomography (CT) can be used for material decomposition, allowing for the precise quantitative mapping of body substances; this has a wide range of clinical applications, including disease diagnosis, treatment response evaluation and prognosis prediction. However, dual-energy CT has not yet become the mainstream technique in most clinical settings due to its limited accessibility. To fully take advantage of material quantification, researchers have attempted to use deep learning to generate material decomposition maps from conventional single-energy CT images, mainly by synthesizing another single-energy CT image from a conventional single-energy CT image to form a dual-energy CT image first and then generate material decomposition maps. This is not a straightforward process, and it potentially introduces many inaccuracies after multiple steps. In this work, we proposed a generative adversarial network (GAN) framework as the base and improved its generator; this approach combines convolutional neural networks (CNNs) and a transformer module to directly generate material decomposition maps from conventional single-energy CT images. Our model pays attention to both local and global information. Then, we compared our method with 6 competitive deep learning methods on water (calcium) and calcium (water) substrate density image datasets. The average PSNR, SSIM, MAE, and RMSE of the generated and ground truth of the water (calcium) substrate density images were 32.7207, 0.9685, 0.0323, and 0.0555, respectively. Furthermore, the average PSNR, SSIM, MAE, and RMSE of the generated and ground truth of the calcium (water) substrate density images were 30.2823, 0.9449, 0.0652, and 0.0715, respectively. Our model achieved better performance and stronger stability than competing approaches.

Split-filter dual-energy CT pulmonary angiography for the diagnosis of acute pulmonary embolism: a study on image quality and radiation dose.

Computed tomography (CT) pulmonary angiography is the diagnostic reference standard in suspected pulmonary embolism (PE). Favorable results for dual-energy CT (DECT) images have been reported for this condition. Nowadays, dual-energy data acquisition is feasible with different technical options, including a single-source split-filter approach. Therefore, the aim of this retrospective study was to investigate image quality and radiation dose of thoracic split-filter DECT in comparison to conventional single-energy CT in patients with suspected PE. A total of 110 CT pulmonary angiographies were accomplished either as standard single-energy CT with automatic tube voltage selection (ATVS) (n=58), or as split-filter DECT (n=52). Objective [pulmonary artery CT attenuation, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)] and subjective image quality [four-point Likert scale; three readers (R)] were compared among the two study groups. Size-specific dose estimates (SSDE), dose-length-product (DLP) and volume CT dose index (CTDIvol) were assessed for radiation dose analysis. Split-filter DECT images yielded 67.7% higher SNR (27.0 vs. 16.1; P<0.001) and 61.9% higher CNR (22.5 vs. 13.9; P<0.001) over conventional single-energy images, whereas CT attenuation was significantly lower (344.5 vs. 428.2 HU; P=0.013). Subjective image quality was rated good or excellent in 93.0%/98.3%/77.6% (R1/R2/R3) of the single-energy CT scans, and 84.6%/82.7%/80.8% (R1/R2/R3) of the split-filter DECT scans. SSDE, DLP and CTDIvol were significantly lower for conventional single-energy CT compared to split-filter DECT (all P<0.05), which was associated with 26.7% higher SSDE. In the diagnostic workup of acute PE, the split-filter allows for dual-energy data acquisition from single-source single-layer CT scanners. The existing opportunity to assess pulmonary "perfusion" based on analysis of iodine distribution maps is associated with higher radiation dose in terms of increased SSDE than conventional single-energy CT with ATVS. Moreover, a proportion of up to 3.8% non-diagnostic examinations in the current reference standard test for PE is not negligible.

Overcoming calcium blooming and improving the quantification accuracy of percent area luminal stenosis by material decomposition of multi-energy computed tomography datasets.

Purpose: Conventional stenosis quantification from single-energy computed tomography (SECT) images relies on segmentation of lumen boundaries, which suffers from partial volume averaging and calcium blooming effects. We present and evaluate a method for quantifying percent area stenosis using multienergy CT (MECT) images. Approach: We utilize material decomposition of MECT images to measure stenosis based on the ratio of iodine mass between vessel locations with and without a stenosis, thereby eliminating the requirement for segmentation of iodinated lumen. The method was first assessed using simulated MECT images created with different spatial resolutions. To experimentally assess this method, four phantoms with different stenosis severity (30% to 51%), vessel diameters (5.5 to 14mm), and calcification densities (700 to ) were fabricated. Conventional SECT images were acquired using a commercial CT system and were analyzed with commercial software. MECT images were acquired using a commercial dual-energy CT (DECT) system and also from a research photon-counting detector CT (PCD-CT) system. Three-material-decomposition was performed on MECT data, and iodine density maps were used to quantify stenosis. Clinical radiation doses were used for all data acquisitions. Results: Computer simulation verified that this method reduced partial volume and blooming effects, resulting in consistent stenosis measurements. Phantom experiments showed accurate and reproducible stenosis measurements from MECT images. For DECT and two-threshold PCD-CT images, the estimation errors were 4.0% to 7.0%, 2.0% to 9.0%, 10.0% to 18.0%, and to (ground truth: 51%, 51%, 51%, and 30%). For four-threshold PCD-CT images, the errors were 1.0% to 3.0%, 4.0% to 6.0%, to 9.0%, and 0.0% to 6.0%. Errors using SECT were much larger, ranging from 4.4% to 46%, and were especially worse in the presence of dense calcifications. Conclusions: The proposed approach was shown to be insensitive to acquisition parameters, demonstrating the potential to improve the accuracy and precision of stenosis measurements in clinical practice.

Comparison of image quality between split-filter twin beam dual energy and single energy images in abdominal CT

PurposeTo compare the objective and subjective image quality between composed images from split-filter twin beam dual energy (TBDE) and single-energy computed tomography (SECT) in abdominal CT. MethodsIn this prospective study, 103 patients were imaged using TBDE (n = 51) or SECT (n = 52). The CT number and noise were measured for the following six abdominal structures: liver, spleen, fat, muscle, aorta and portal vein. The normalised noise level for the liver was separately measured and compared. The consistency of the SNR and CT number was compared between the two groups. The subjective image quality was evaluated using six aspects in a blinded manner. Cohen’s Kappa statistic was used to determine the level of agreement between the two radiologists. ResultsFor the objective image quality comparison, the SNR of all structures was higher using TBDE compared to SECT (p < 0.05). The CT value for different structures were comparable between the two groups (p > 0.05). Among all patient sizes, the noise level for TBDE images was significantly lower (7–17% reduction) compared to the SECT images (p < 0.01). Furthermore, noise reduction’s magnitude increases with body size. For image quality’s subjective evaluation, TBDE images are superior for certain aspects. Cohen’s Kappa values (0.7634–0.8460) suggest an adequate level of agreement between the two observers. ConclusionsTBDE scan mode can yield similar or even better objective and subjective image quality at the same level of radiation than conventional SECT. Quantitatively, TBDE images have a 7–17% reduction in noise, depending on the size of the scanned body regions.

Improved repeatability of subsolid nodule measurement in low-dose lung screening with monoenergetic images: a phantom study.

To investigate whether monoenergetic images captured with dual-layer spectral computed tomography (CT) can improve the repeatability of subsolid nodule measurement, and whether this approach can further reduce the radiation dose of CT while maintaining its measurement repeatability. An anthropomorphic phantom with simulated subsolid nodules at three different levels was repeatedly scanned with both conventional single-energy CT and dual-layer spectral CT. A proxy for the measurement repeatability in the National Lung Screening Trial (proxy for NLST) was calculated with the typical CT protocol used in NLST. Using the dual-layer spectral CT, monoenergetic images of 40 to 110 keV, with an interval of 10 keV, were generated. The average diameter and volume of a total of 15,120 nodules in 840 CT images were measured by using a commercially-available computer-aided detection (CAD) system. The repeatability coefficient (RC), %RC, and 95% confidence intervals (CIs) of each image set were calculated and compared. At the same tube voltage and tube current-time product, monoenergetic images resulted in significantly lower RC than the proxy for NLST, indicating that measurement repeatability was enhanced. When the radiation dose was lowered by 30% or 55%, monoenergetic images showed significantly lower RC at high-energy keV than the proxy for NLST. The estimated measurement repeatability from monoenergetic images with 30% or 55% lower radiation dose was comparable to the repeatability from conventional single-energy CT images with standard radiation dose and iterative reconstruction. Monoenergetic images captured by using dual-layer spectral CT can improve the repeatability of subsolid nodule measurement. The use of monoenergetic images would allow lung cancer screening with a lower radiation dose, while maintaining comparable measurement repeatability.

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

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

Advanced Computed Tomography Techniques: Overview of Dual-Energy CT

AbstractDual-energy computed tomography (DECT) is an advanced form of computed tomography (CT), in which image acquisition is performed at two different energy spectra, instead of a single-energy spectrum using conventional single-energy CT (SECT). This enables the creation of different reconstructions and quantitative spectral tissue analysis beyond what is possible with SECT. In adults, there are increasing clinical applications of DECT for all organ systems, including neuroimaging and head and neck imaging. However, there are relatively few studies evaluating applications of DECT for pediatric imaging and little to none in neuroimaging or head and neck imaging. The purpose of this article is to provide an overview and familiarize the readers with DECT. This article will review the fundamental principles behind DECT, including different DECT acquisition systems and principles of DECT material characterization. This will be followed by a review of potential applications of DECT, many based on imaging the head and neck. The objectives are to familiarize the readers with this exciting technology and hopefully serve as a primer for investigations and applications of DECT for pediatric neuro and head and neck imaging.

Spectral Signal Density of Carotid Plaque Using Dual-Energy Computed Tomography.

Plaque characterization using virtual monochromatic imaging derived from dual-energy computed tomography (CT) angiography requires the determination of normal signal density values of each plaque component. We sought to explore the signal density values of carotid plaque components using dual-energy compared to conventional single-energy CT angiography (CTA), and to establish the energy level with the largest differences between plaque components. The present prospective study involved consecutive patients referred for carotid artery evaluation by CTA. Two scans (single-energy and dual-energy CTA) were performed in all patients, and a single radiologist analyzed the data. Single-source dual-energy CTA allowed the generation of virtual monochromatic images from 40 to 140 keV. A total of 35 internal carotid artery lesions were examined in 20 symptomatic patients. The mean age was 72.3 ± 6.7 years, and 9 (45%) patients were male. Internal carotid artery geometrical variables including lumen area (P = .96), vessel area (P = .97), and percent area stenosis (P = .99) did not differ between groups (single-energy CTA, and dual-energy CTA at 40, 70, 100, and 140 keV). Differences between signal densities of different tissues were largest at 40 keV (calcium/lumen, P < .0001; fat/noncalcified, P < .0001). In the present pilot investigation, virtual monochromatic imaging at low-energy levels derived from dual-energy CTA allowed the largest differences in attenuation levels between tissues, without affecting vessel or plaque geometry.

Multienergy CT acquisition and reconstruction with a stepped tube potential scan.

Based on an energy-dependent property of matter, one may obtain a pseudomonochromatic attenuation map, a material composition image, an electron-density distribution, and an atomic number image using a dual- or multienergy computed tomography (CT) scan. Dual- and multienergy CT scans broaden the potential of x-ray CT imaging. The development of such systems is very useful in both medical and industrial investigations. In this paper, the authors propose a new dual- and multienergy CT system design (segmental multienergy CT, SegMECT) using an innovative scanning scheme that is conveniently implemented on a conventional single-energy CT system. The two-step-energy dual-energy CT can be regarded as a special case of SegMECT. A special reconstruction method is proposed to support SegMECT. In their SegMECT, a circular trajectory in a CT scan is angularly divided into several arcs. The x-ray source is set to a different tube voltage for each arc of the trajectory. Thus, the authors only need to make a few step changes to the x-ray energy during the scan to complete a multienergy data acquisition. With such a data set, the image reconstruction might suffer from severe limited-angle artifacts if using conventional reconstruction methods. To solve the problem, they present a new prior-image-based reconstruction technique using a total variance norm of a quotient image constraint. On the one hand, the prior extracts structural information from all of the projection data. On the other hand, the effect from a possibly imprecise intensity level of the prior can be mitigated by minimizing the total variance of a quotient image. The authors present a new scheme for a SegMECT configuration and establish a reconstruction method for such a system. Both numerical simulation and a practical phantom experiment are conducted to validate the proposed reconstruction method and the effectiveness of the system design. The results demonstrate that the proposed SegMECT can provide both attenuation images and material decomposition images of reasonable image quality. Compared to existing methods, the new system configuration demonstrates advantages in simplicity of implementation, system cost, and dose control. This proposed SegMECT imaging approach has great potential for practical applications. It can be readily realized on a conventional CT system.

Substantial iodine volume load reduction in CT angiography with dual-energy imaging: insights from a pilot randomized study.

We explored whether dual-energy computed tomography (DECT) can allow a significant reduction in iodinated contrast volume during computed tomography angiography (CTA) without hampering image quality or assessibility. We prospectively randomized patients clinically referred to CTA to single energy computed tomography (SECT) with full iodine volume load (group A), DECT with 50 % iodine volume load (group B), DECT with 40 % iodine volume load (group C), and DECT with 30 % iodine volume load (group D); and compared image quality and assessibility. Eighty patients were enrolled and prospectively randomized. The mean age was 61.7 ± 15.0 years and 56 (71 %) patients were male. The demographical characteristics, body mass index, or mean radiation dose did not differ between groups. Significant reductions in total contrast volume were achieved in groups B, C, and D; with mean administrated contrast volumes of 90.3 ± 10.1, 39.5 ± 4.6, 28.3 ± 6.5, and 23.9 ± 6.0 mL, respectively, in groups A to D (p < 0.0001). With regard to image quality, no significant decrease in the Likert scale was observed with reductions of up to 60 % of the contrast volume (groups B and C). DECT at 50-60 keV in association with up to 60 % iodine load reduction, allowed similar signal density, image noise, and signal to noise ratio that SECT imaging with full iodine load. In this pilot, prospective, randomized study, dual energy CTA with up to 60 % iodine volume load reduction provided similar image quality and assessibility than full iodine load with conventional SECT imaging.

State of the art: dual-energy CT of the abdomen.

Recent technologic advances in computed tomography (CT)--enabling the nearly simultaneous acquisition of clinical images using two different x-ray energy spectra--have sparked renewed interest in dual-energy CT. By interrogating the unique characteristics of different materials at different x-ray energies, dual-energy CT can be used to provide quantitative information about tissue composition, overcoming the limitations of attenuation-based conventional single-energy CT imaging. In the past few years, intensive research efforts have been devoted to exploiting the unique and powerful opportunities of dual-energy CT for a variety of clinical applications. This has led to CT protocol modifications for radiation dose reduction, improved diagnostic performance for detection and characterization of diseases, as well as image quality optimization. In this review, the authors discuss the basic principles, instrumentation and design, examples of current clinical applications in the abdomen and pelvis, and future opportunities of dual-energy CT.