Journal of X-Ray Science and Technology - Volume 27, issue 5

Authors: Wang, Ting | Gong, Jing | Duan, Hui-Hong | Wang, Li-Jia | Ye, Xiao-Dan | Nie, Sheng-Dong

Article Type: Research Article

Abstract: OBJECTIVE: Radiogenomics investigates radiographic imaging phenotypes associated with gene expression patterns. This study aims to explore relationships between CT imaging radiomics features and gene expression data in non-small cell lung cancer (NSCLC). METHODS: Eighty-nine NSCLC patients are included in the study. Radiomics features are extracted and selected to quantify the phenotype of tumors on CT-scans. Co-expressed genes are also clustered and the first principal component of the cluster is represented, which is defined as a metagene. Then, statistical analysis was performed to assess association of CT radiomics features with metagenes. In addition, predictive models are built and metagene …enrichment are conducted to further evaluate performance of NSCLC radiogenomics statistically and biologically. RESULTS: There are 187 significant pairwise correlations between a CT radiomics feature and a metagene of NSCLC, where eighteen metagenes are annotated with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms. Metagenes are predicted in terms of radiomics features with an accuracy of 41.89% –89.93%. CONCLUSIONS: This study reveals the associations between CT imaging radiomics features and NSCLC co-expressed gene sets. The findings suggest that CT radiomics features can reflect important biological information of NSCLC patients, which may have a significant clinical impact as CT is routinely used in clinical practice, assisting in improving medical decision-support at low cost. Show more

Keywords: Radiogenomics, radiomics features, computed tomography, non-small cell lung cancer

DOI: 10.3233/XST-190526

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 773-803, 2019

Authors: Matenine, Dmitri | Schmittbuhl, Matthieu | Bedwani, Stéphane | Després, Philippe | de Guise, Jacques A.

Article Type: Research Article

Abstract: BACKGROUND: Iterative reconstruction is well-established in diagnostic multidetector computed tomography (MDCT) for dose reduction and image quality enhancement. Its application to diagnostic cone beam computed tomography (CBCT) is only emerging and warrants a quantitative evaluation. METHODS: Several phantoms and a canine head specimen were imaged using a commercially available small-field CBCT scanner. Raw projection data were reconstructed using the Feldkamp-Davis-Kress (FDK) method with different filters, including denoising via total variation (TV) minimization (FDK-TV). Iterative reconstruction was carried out using the TV-regularized ordered subsets convex technique (OSC-TV). Signal-to-noise ratio (SNR), noise power spectrum (NPS) and spatial resolution of images …were estimated. Dose levels were measured via the weighted computed tomography dose index, while low-dose image quality degradation was estimated via structural similarity (SSIM). RESULTS: OSC-TV and FDK-TV were shown to significantly improve image signal-to-noise ratio (SNR) compared to FDK with a standard filter, 5.8 and 4.0 times, respectively. Spatial resolution attained with different algorithms varied moderately across different experiments. For low-dose acquisitions, image quality decreased dramatically for FDK but not for FDK-TV nor OSC-TV. For low-dose canine head images acquired using about 1/5 of the dose compared to a reference image, SSIM dropped to about 0.3 for FDK, while remaining at 0.92 for FDK-TV and 0.96 for OSC-TV. CONCLUSION: OSC-TV was shown to improve image quality compared to FDK and FDK-TV. Moreover, this iterative approach allowed for significant dose reduction while maintaining image quality. Show more

Keywords: Cone beam CT, few-view CT, low-dose CT, iterative reconstruction

DOI: 10.3233/XST-190523

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 805-819, 2019

Authors: Tan, Lu | Liang, Antoni | Li, Ling | Liu, Wanquan | Kang, Hanwen | Chen, Chao

Article Type: Research Article

Abstract: BACKGROUND: Segmentation of prostate from magnetic resonance images (MRI) is a critical process for guiding prostate puncture and biopsy. Currently, the best results are obtained by Convolutional Neural Network (CNN). However, challenges still exist when applying CNN to segment prostate, such as data distribution issue caused by insubstantial and inconsistent intensity levels and vague boundaries in MRI. OBJECTIVE: To segment prostate gland from a MRI dataset including different prostate images with limited resolution and quality. METHODS: We propose and apply a global histogram matching approach to make intensity distribution of the MRI dataset closer to uniformity. …To capture the real boundaries and improve segmentation accuracy, we employ a module of variational models to help improve performance. RESULTS: Using seven evaluation metrics to quantify improvements of our proposed fusion approach compared with the state of art V-net model resulted in increase in the Dice Coefficient (11.2%), Jaccard Coefficient (13.7%), Volumetric Similarity (12.3%), Adjusted Rand Index (11.1%), Area under ROC Curve (11.6%), and reduction of the Mean Hausdorff Distance (16.1%) and Mahalanobis Distance (2.8%). The 3D reconstruction also validates the advantages of our proposed framework, especially in terms of smoothness, uniformity, and accuracy. In addition, observations from the selected examples of 2D visualization show that our segmentation results are closer to the real boundaries of the prostate, and better represent the prostate shapes. CONCLUSIONS: Our proposed approach achieves significant performance improvements compared with the existing methods based on the original CNN or pure variational models. Show more

Keywords: Automatic prostate segmentation, convolutional neural networks, variational models

DOI: 10.3233/XST-190524

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 821-837, 2019

Authors: Tao, Chao | Chen, Ke | Han, Lin | Peng, Yulan | Li, Cheng | Hua, Zhan | Lin, Jiangli

Article Type: Research Article

Abstract: BACKGROUND: Breast cancer has the highest cancer prevalence rate among the women worldwide. Early detection of breast cancer is crucial for successful treatment and reducing cancer mortality rate. However, tumor detection of breast ultrasound (US) image is still a challenging work in computer-aided diagnosis (CAD). OBJECTIVE: This study aims to develop a novel automated algorithm for breast tumor detection based on deep learning. METHODS: We proposed a new deep learning network named One-step model which have one input and two outputs, the first one was the segmentation result and the other one was used for false-positive …reduction. The proposed One-step model includes three key components: Base-net, Seg-net, and Cls-net based on Anchor Box. The model chose DenseNet to construct Base-net, the decoder part of RefineNet as Seg-net, and connected several middle layers of Base-net and Seg-net to Cls-net. From the first output acquired by Base-net and Seg-net, the model detected a series of suspicious lesion regions. Then the second output from the Cls-net was used to recognize and reduce the false-positive regions. RESULTS: Experimental results showed that the new model achieved competitive detection result with 90.78% F1 score, which was 8.55% higher than Single Shot MultiBox Detector (SSD) method. In addition, running new model is also computational efficient and has comparative cost effect as SSD. CONCLUSIONS: We established a novel One-step model which improves location accuracy by generating more precise bounding box via Seg-net and removing false targets by another object detection network (Cls-net). On the other hand, a real-time detection of tumor is achieved by sharing the common Base-net. The experimental results showed that the new model performed well on various irregular and blurred ultrasound images. As a result, this study demonstrated feasibility of applying deep learning scheme to detect breast lesions depicting on US image. Show more

Keywords: Automatic location, breast tumor, deep learning, fully connected convolutional networks, segmentation, ultrasound image, Anchor Box

DOI: 10.3233/XST-190548

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 839-856, 2019

Authors: Barysheva, M.M. | Chkhalo, N.I. | Drozdov, M.N. | Mikhailenko, M.S. | Pestov, A.E. | Salashchenko, N.N. | Vainer, Y.A. | Yunin, P.A. | Zorina, M.V.

Article Type: Research Article

Abstract: Anomalously high x-ray scattering at a wavelength of 0.154 nm by super-polished substrates of fused silica, which were etched by the argon ions with the energy of 300 eV, is detected. The scattering intensity increases monotonically with increasing of the etching depth. The effect is explained by the scattering on the volume inhomogeneities with the lateral size greater than 0.5 μm of the subsurface “damaged” layer. The concentration of volume inhomogeneities increases with the increase of the fluence of argon ions, but the concentration of implanted argon atoms in the layer quickly reaches the maximum value and then begins a trend of …going down. The thickness of the “damaged” layer is approximately equal to the penetration depth of the Ar atoms and can be directly determined from the x-ray specular reflection. It is shown that the presence of volume inhomogeneities of the subsurface “damaged” layer does not affect the geometric roughness of the surface. The observed effect imposes limitations on the usage of grazing incidence x-ray optics without reflective coatings and of the diffuse x-ray scattering (DXRS) method for studying the substrate roughness. A new method that potentially enables to evaluate the applicability of the DXRS method in practice is proposed. Show more

Keywords: X-ray optics, X-Ray diffuse scattering, supersmooth surface, Ion polishing, Roughness, Ion implantation

DOI: 10.3233/XST-190495

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 857-870, 2019

Authors: Lei, Pinggui | Jiao, Jun | Li, Hong | Wang, Pingxian | Duan, Qinghong | Liu, Jing | Zhou, Shi | Wei, Qian | Wang, Xiaolin

Article Type: Research Article

Abstract: OBJECTIVE: This study aims to assess the value of ultrasound real-time shear wave elastography (US-SWE) for evaluation of nonalcoholic fatty liver disease (NAFLD) in a rabbit model compared with multislice computed tomography (MSCT). MATERIAL AND METHODS: Twenty-six rabbits were fed with high-fat, high-cholesterol diet and six rabbits were fed with a standard diet. All rabbits were performed with MSCT and US-SWE at various time points to measure changes in liver parenchyma. The diagnostic efficiency of US-SWE was analyzed using receiver operating characteristics (ROC) curves compared with MSCT based on the liver pathology. RESULTS: The statistically significant …differences in the areas under the ROC curves between using MSCT and US-SWE modalities were detected to discriminate between normal vs. NAFLD or higher severity pathology. Similarly, for normal or NAFLD vs. borderline or NASH livers, statistically significant differences between using US-SWE and MSCT modalities were also detected for nonalcoholic steatohepatitis (NASH) vs. lower severity pathology. CONCLUSIONS: MSCT, but not US-SWE, had a better ability to differentiate normal or NAFLD livers from higher severity NAFLD livers. However, the diagnostic efficiency of US-SWE was superior to that of MSCT for differentiating NASH from normal or lower severity NAFLD. Show more

Keywords: Shear wave elastography, nonalcoholic fatty liver disease, nonalcoholic steatohepatitis, multislice computed tomography, diagnostic efficiency

DOI: 10.3233/XST-190502

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 871-883, 2019

Authors: Choi, Hyunho | Jeong, Jechang

Article Type: Research Article

Abstract: Ultrasound imaging has been used for diagnosing lesions in the human body. In the process of acquiring ultrasound images, speckle noise may occur, affecting image quality and auto-lesion classification. Despite the efforts to resolve this, conventional algorithms exhibit poor speckle noise removal and edge preservation performance. Accordingly, in this study, a novel algorithm is proposed based on speckle reducing anisotropic diffusion (SRAD) and a Bayes threshold in the wavelet domain. In this algorithm, SRAD is employed as a preprocessing filter, and the Bayes threshold is used to remove the residual noise in the resulting image. Compared to the conventional filtering …techniques, experimental results showed that the proposed algorithm exhibited superior performance in terms of peak signal-to-noise ratio (average = 28.61 dB) and structural similarity (average = 0.778). Show more

Keywords: Ultrasound imaging, speckle noise, discrete wavelet transform, srad, bayes threshold

DOI: 10.3233/XST-190515

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 885-898, 2019

Authors: Yu, Wei-Ye | Zhang, Qian Qian | Xiao, Yong | Tan, Wei-Guo | Li, Xiang-Dong | Lu, Pu-Xuan

Article Type: Research Article

Abstract: OBJECTIVE: To explore the difference of 18F-FDG PET/CT images between the symptomatic and asymptomatic pulmonary tuberculosis, as well as the correlation between the standard uptake value (SUV) and the symptomatic/asymptomatic pulmonary tuberculosis. METHODS: A study dataset of 57 pulmonary tuberculosis cases was retrospectively assembled and analyzed. Among these cases, 30 were diagnosed having symptomatic pulmonary tuberculosis and 27 were asymptomatic pulmonary tuberculosis. PET/CT was performed in all 57 cases. The clinical data, CT images and PET/CT radioactive uptake data were analyzed using statistical data analysis software. RESULTS: All 57 cases showed radioactively high uptake, with the …maximum standard uptake value (SUVmax) of the lesion ranging from 1.60 to 27.30 and a mean value of 6.63±4.82. The symptomatic cases had an SUVmax of 8.76±4.97 and the asymptomatic cases had an SUVmax of 4.27±3.39. The SUVmax as well as singular or multiple lesions showed statistical differences between symptomatic and asymptomatic cases. CONCLUSION: The symptomatic pulmonary tuberculosis cases show significantly higher SUVmax than the asymptomatic cases. Based on the criteria of SUVmax greater than 2.0 to define active lesions, 100% of symptomatic cases might have active lesions while 70.4% of asymptomatic cases might have active lesions. Therefore, focused attention should be clinically paid on the asymptomatic cases of pulmonary tuberculosis to avoid miss diagnosis and delayed treatment. Show more

Keywords: PET/CT, active, pulmonary tuberculosis

DOI: 10.3233/XST-190543

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 899-906, 2019

Authors: Kim, Tae-Hoon | Ryu, Jong-Hyun | Jeong, KilHwan | Kim, Kyu Gyeom | Jeong, Chang-Won | Yoon, Kwon-Ha | Kim, Dae-Won

Article Type: Research Article

Abstract: BACKGROUND: Intraoperative computed tomography (iCT) system has been developed focusing on combining the advanced imaging techniques for the best imaging modality. However, the use of iCT system in the operating rooms is limited due to the lack of flexible mobility. OBJECTIVE: This study aims to develop a mobile iCT imaging system and assess its imaging performance in a phantom study. METHODS: The mobile iCT system with mecanum omni-directional wheels has three major components namely, a rotating gantry, a slip-ring and a stationary gantry. Performance of mecanum iCT system was evaluated using the indices of signal-to-noise (SNR), …contrast-to noise (CNR), and spatial resolution (MTF). Anatomical landmarks on phantom images were assessed using a 5-point scale (5 = definitely seen; 4 = probably seen; 3 = equivocal; 2 = probably not seen; and 1 = definitely not seen). RESULTS: The mecanum iCT system can be conveniently used for a whole-body scan under intraoperative conditions even in narrow operating rooms due to a smaller turning radius. The image quality of the mecanum iCT system was found to be acceptable for clinical applications (with SNR = 162.72, CNR = 134.29 and MTF = 694 μm). The diagnostic scores on the phantom images were ‘definitely seen’ value. CONCLUSIONS: The proposed mecanum iCT system achieved the improved flexible mobility and has potential to better serve as a useful imaging tool in the clinical intraoperative setting. Show more

Keywords: Intraoperative computed tomography (iCT) system, brain, body, operating room, mobile CT

DOI: 10.3233/XST-190514

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 907-918, 2019

Authors: Edey, D.R. | Pollmann, S.I. | Lorusso, D. | Drangova, M. | Flemming, R.L. | Holdsworth, D.W.

Article Type: Research Article

Abstract: BACKGROUND: X-ray computed tomography (CT) can non-destructively examine objects by producing three-dimensional images of their internal structure. Although the availability of biomedical micro-CT offers the increased access to scanners, CT images of dense objects are susceptible to artifacts particularly due to beam hardening. OBJECTIVE: This study proposes and evaluates a simple semi-empirical correction method for beam hardening and scatter that can be applied to biomedical scanners. METHODS: Novel calibration phantoms of varying diameters were designed and built from aluminum and poly[methyl-methacrylate]. They were imaged using two biomedical micro-CT scanners. Absorbance measurements made through different phantom sections …were fit to polynomial and inversely exponential functions and used to determine linearization parameters. Corrections based on the linearization equations were applied to the projection data before reconstruction. RESULTS: Correction for beam hardening was achieved when applying both scanners with the correction methods to all test objects. Among them, applying polynomial correction method based on the aluminum phantom provided the best improvement. Correction of sample data demonstrated a high agreement of percent-volume composition of dense metallic inclusions between using the Bassikounou meteorite from the micro-CT images (13.7%) and previously published results using the petrographic thin sections (14.6% 8% metal and 6.6% troilite). CONCLUSIONS: Semi-empirical linearization of X-ray projection data with custom calibration phantoms allows accurate measurements to be obtained on the radiodense samples after applying the proposed correction method on biomedical micro-CT images. Show more

Keywords: Micro-computed tomography, beam hardening, geomaterials, empirical correction, astromaterials, meteorites

DOI: 10.3233/XST-190511

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 919-934, 2019

Authors: Ben, Ren-Jy | Jao, Jo-Chi | Chang, Chiung-Yun | Tzeng, Jiun-Siang | Hwang, Lain-Chyr | Chen, Po-Chou

Article Type: Research Article

Abstract: BACKGROUND: Arterial embolism is a major cause of ischemic stroke. Currently, digital subtraction angiography (DSA) is the gold standard in clinical arterial embolization examinations. However, it is invasive and risky. OBJECTIVE: This study aims to longitudinally assess the progression of carotid artery embolism in middle cerebral artery occlusion animal model (MCAO) using magnetic resonance imaging (MRI) techniques. METHODS: Turbo spin echo (TSE), time of flight magnetic resonance angiography (TOF-MRA) and diffusion weighted magnetic resonance imaging (DWI) were used to evaluate the image characteristics of cerebral tissues at 1, 2, 3, 7, 14, 21 and 28 days …after MCAO microsurgery on Sprague-Dawley (SD) rats. Quantitative analysis was performed and compared in MCAO hemisphere and contralateral normal hemisphere. Furthermore, pathologic section using triphenyl tetrazolium chloride (TTC) stain was performed as well. RESULTS: TOF-MRA showed carotid signal void in the embolism side, which is evidence of artery occlusion. The used MRI techniques showed that edema gradually dissipated within one week, but there was no significant change afterwards. The time-varying signal intensity of MRI techniques in MCAO hemisphere changed significantly, but there were no significant changes in contralateral normal hemisphere. Cerebral injury was also confirmed by analysis of pathology images. CONCLUSIONS: The MCAO animal model was successfully established on SD rats using the microsurgery to assess arterial embolization of intracranial tissue injury. Show more

Keywords: Time of flight magnetic resonance angiography, diffusion weighted magnetic resonance imaging, apparent diffusion coefficient, Sprague-Dawley rat, middle cerebral artery occlusion animal model, ischemic stroke

DOI: 10.3233/XST-190538

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 935-947, 2019

Authors: Gao, Juan | Zhang, Qiyang | Liu, Qiegen | Zhang, Xuezhu | Zhang, Mengxi | Yang, Yongfeng | Liang, Dong | Liu, Xin | Zheng, Hairong | Hu, Zhanli

Article Type: Research Article

Abstract: PURPOSE: To reduce the cost of positron emission tomography (PET) scanning systems, image reconstruction algorithms for low-sampled data have been extensively studied. However, the current method based on total variation (TV) minimization regularization nested in the maximum likelihood-expectation maximization (MLEM) algorithm cannot distinguish true structures from noise resulting losing some fine features in the images. Thus, this work aims to recover fine features lost in the MLEM-TV algorithm from low-sampled data. METHOD: A feature refinement (FR) approach previously developed for statistical interior computed tomography (CT) reconstruction is applied to PET imaging to recover fine features in this study. …The proposed method starts with a constant initial image and the FR step is performed after each MLEM-TV iteration to extract the desired structural information lost during TV minimization. A feature descriptor is specifically designed to distinguish structure from noise and artifacts. A modified steepest descent method is adopted to minimize the objective function. After evaluating the impacts of different patch sizes on the outcome of the presented method, an optimal patch size of 7×7 is selected in this study to balance structure-detection ability and computational efficiency. RESULTS: Applying MLEM-TV-FR algorithm to the simulated brain PET imaging using an emission activity phantom, a standard Shepp-Logan phantom, and mouse results in the increased peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) as comparing to using the conventional MLEM-TV algorithm, as well as the substantial reduction of the used sampling numbers, which improves the computational efficiency. CONCLUSIONS: The presented algorithm can achieve image quality superior to that of the MLEM and MLEM-TV approaches in terms of the preservation of fine structure and the suppression of undesired artifacts and noise, indicating its useful potential for low-sampled data in PET imaging. Show more

Keywords: Positron emission tomography (PET), maximum likelihood-expectation maximization (MLEM), low-sampled data, total variation (TV), feature extraction

DOI: 10.3233/XST-190527

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 949-963, 2019

Authors: Yang, Fuqiang | Zhang, Dinghua | Zhang, Hua | Huang, Kuidong

Article Type: Research Article

Abstract: Based on the structural tensor of projection, this study aims to address and test a new improved algorithm applying to the distort projection data to generate a high qualified image by reducing the artifacts and noise from scattering in the cone-beam computed tomography (CBCT). Since the scattering information has a large relationship with the structure of the object, which is reflected by the projection, regional model knowledge for scattering is accomplished by finding the relationship between projection and scattering. As the tensor, the gradient of projection is first calculated in the process for estimating the direction and structural edge of …the object. Then, the Determinant and Traces of the tensor map with different characteristics are computed to determine the different regions. By modeling and fitting the regions of scattering distribution, the knowledge of scattering parameters corresponding to a different region is obtained. Based on the similarity of scattering distribution in adjacent angles, the scatterings with angle sequence are completed by interpolating the prior knowledge obtained through the sparse sampling. By performing the studies on polychromatic X-ray to test the performance of the scattering estimation algorithm, the results show a significant improvement in the images that are reconstructed from the corrected projection. The root mean square error (RMSE) of the proposed method is reduced by 21.8% and 39.8%, respectively. Peak signal to noise ratio (PSNR), and universal quality index (UQI) also indicate better uniformity, where the PSNR is increased by 7.4% and 56.7%, UQI is increased by 70.8% and 262.3% for experimental #Wheel and #Cylinder , respectively. Show more

Keywords: Scattering estimation, angular sequence, structural tensor, cone-beam computed tomography, corrected projection

DOI: 10.3233/XST-190528

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 965-979, 2019

Authors: Zhao, Yongxia | Geng, Xue | Zhang, Tianle | Wang, Xiuzhi | Xue, Yize | Dong, Kexin

Article Type: Research Article

Abstract: OBJECTIVE: To compare image quality, radiation dose, and iodine intake of head-neck CT angiography (CTA) acquired by wide-detector with the gemstone spectral imaging (GSI) combination with low iodine intake or routine scan protocol. METHODS: Three hundred patients who had head-neck CTA were enrolled and divided into three groups according to their BMI values: group A (18.5 kg/m2 ≦ BMI <24.9 kg/m2 ), group B (24.9 kg/m2 ≦ BMI <29.9 kg/m2 ) and group C (29.9 kg/m2 ≦ BMI ≦ 34.9 kg/m2 ) with 100 patients in each group. Patients in each group were randomly divided into two subgroups (n  = 50) …namely, A1, A2, B1, B2, C1 and C2. The patients in subgroups A1, B1 and C1 underwent GSI with low iodine intake (270 mgI/ml, 50 ml) and combined with the ASiR-V algorithm. Other patients underwent three dimensional (3D) smart mA modulation with routine iodine intake (350 mgI/ml, 60 ml). Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of all images were calculated after angiography. Images were then subjectively assessed using a 5-point scale. CT dose index of volume and dose-length product (DLP) was converted to the effective dose (ED) and then compared. RESULTS: The mean CT values, SNR, CNR and subjective image quality in subgroups A2, B2 and C2 are significantly lower than in subgroups A1, B1, and C1 (P  < 0.01), respectively. The ED values in subgroup A1, B1, and C1 are 55.18%, 61.89%, and 69.64% lower than those in A2, B2, and C2, respectively (P  < 0.01). The total iodine intakes in subgroups A1, B1, and C1 are 35.72% lower than those in subgroups A2, B2, and C2. CONCLUSIONS: The gemstone spectral imaging with monochromatic images at 53–57 keV combined with ASiR-V algorithm allows significant reduction in iodine load and radiation dose in head-neck CT angiography than those yielded in routine scan protocol. It also enhances signal intensity of head-neck CTA and maintains image quality. Show more

Keywords: Gemstone spectral imaging, radiation dose, image quality, low iodine intake, head-neck CT angiography

DOI: 10.3233/XST-190541

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 5, pp. 981-993, 2019