Journal of X-Ray Science and Technology - Volume 30, issue 6

Authors: Hu, Ying | Yang, Yifeng | Hou, Xuewen | Zhou, Yan | Nie, Shengdong

Article Type: Research Article

Abstract: OBJECTIVE: To investigate relationships between the severity of white matter hyperintensities (WMH), functional brain activity, and cognition in cerebral small vessel disease (CSVD) based on resting-state functional magnetic resonance imaging (rs-fMRI) data. METHODS: A total of 103 subjects with CSVD were included. The amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo), functional connectivity (FC) and their graph properties were applied to explore the influence of WMH burden on functional brain activity. We also investigated whether there are correlations between different functional brain characteristics and cognitive assessments. Finally, we selected disease-related rs-fMRI features in combination with ensemble learning …to classify CSVD patients with low WMH load and with high WMH load. RESULTS: The high WMH load group demonstrated significantly abnormal functional brain activity based on rs-MRI data, relative to the low WMH load group. ALFF and graph properties in specific brain regions were significantly correlated with patients’ cognitive assessments in CSVD. Moreover, altered rs-fMRI signal can help predict the severity of WMH in CSVD patients with an overall accuracy of 92.23%. CONCLUSIONS: This study provided a comprehensive analysis and evidence for a pattern of altered functional brain activity under different WMH load in CSVD based on rs-fMRI data, enabling accurately individual prediction of status of WMH. Show more

Keywords: Cerebral small vessel disease, white matter hyperintensities, rs-fMRI, cognition, aging

DOI: 10.3233/XST-221218

Citation: Journal of X-Ray Science and Technology, vol. 30, no. 6, pp. 1213-1227, 2022

Authors: Liu, Yi | Kang, Jiaqi | Li, Zhiyuan | Zhang, Quan | Gui, Zhiguo

Article Type: Research Article

Abstract: BACKGROUND: Low-dose computed tomography (LDCT) is an effective method for reducing radiation exposure. However, reducing radiation dose leads to considerable noise in the reconstructed image that can affect doctor’s judgment. OBJECTIVE: To solve this problem, this study proposes a local total variation and improved wavelet residual convolutional neural network (LTV-WRCNN) denoising model. METHODS: The model first introduces local total variation (LTV) to decompose the LDCT image into cartoon and texture image. Next, the texture image is filtered using the non-local mean (NLM). Then, the cartoon image is added to the filtered texture image to obtain the …preprocessing image. Finally, the pre-processed image is fed into the improved wavelet residual neural network (WRCNN) to obtain an improved image. Additionally, we also introduce a compound loss in wavelet domain that combines mean squared error loss and directional regularization loss to separate the structural details from noise more thoroughly. RESULTS: Compared with state-of-the-art methods, the peak-signal-to-noise ratio (PSNR) value and the structure similarity (SSIM) value of the processed CT images using the new proposed model are 33.4229 dB and 0.9158. Study also shows that applying new model obtains better results visually and numerically, especially in terms of the preservation of structural details. CONCLUSIONS: The proposed new model is feasible and effective in improving the quality of LDCT images. Show more

Keywords: Low-dose computed tomography (LDCT), Local total variation (LTV), Wavelet residual convolutional neural network (WRCNN), non-local mean (NLM), compound loss, image denoising

DOI: 10.3233/XST-221233

Citation: Journal of X-Ray Science and Technology, vol. 30, no. 6, pp. 1229-1242, 2022

Authors: Yu, Yalan | Chen, Zhong | Zhuang, Yan | Yi, Heng | Han, Lin | Chen, Ke | Lin, Jiangli

Article Type: Research Article

Abstract: BACKGROUND: Standard planes (SPs) are crucial for the diagnosis of fetal brain malformation. However, it is very time-consuming and requires extensive experiences to acquire the SPs accurately due to the large difference in fetal posture and the complexity of SPs definitions. OBJECTIVE: This study aims to present a guiding approach that could assist sonographer to obtain the SPs more accurately and more quickly. METHODS: To begin with, sonographer uses the 3D probe to scan the fetal head to obtain 3D volume data, and then we used affine transformation to calibrate 3D volume data to the standard …body position and established the corresponding 3D head model in ‘real time’. When the sonographer uses the 2D probe to scan a plane, the position of current plane can be clearly show in 3D head model by our RLNet (regression location network), which can conduct the sonographer to obtain the three SPs more accurately. When the three SPs are located, the sagittal plane and the coronal planes can be automatically generated according to the spatial relationship with the three SPs. RESULTS: Experimental results conducted on 3200 2D US images show that the RLNet achieves average angle error of the transthalamic plane was 3.91±2.86°, which has a obvious improvement compared other published data. The automatically generated coronal and sagittal SPs conform the diagnostic criteria and the diagnostic requirements of fetal brain malformation. CONCLUSIONS: A guiding scanning method based deep learning for ultrasonic brain malformation screening is firstly proposed and it has a pragmatic value for future clinical application. Show more

Keywords: Guiding approach, ultrasound scan, fetal brain malformation, standard planes, regression location network

DOI: 10.3233/XST-221278

Citation: Journal of X-Ray Science and Technology, vol. 30, no. 6, pp. 1243-1260, 2022

Authors: Liu, Zhi-Chao | Zhao, Sai | Ma, Ze-Peng | Zhang, Tian-Le | Zhao, Yong-Xia

Article Type: Research Article

Abstract: OBJECTIVES: To compare image quality, radiation dose, and iodine intake of coronary computed tomography angiography (CCTA) acquired by wide-detector using different tube voltages and different concentrations of contrast medium (CM) for overweight patients. MATERIALS AND METHODS: A total of 150 overweight patients (body mass index≥25 kg/m2 ) who underwent CCTA are enrolled and divided into three groups according to scan protocols namely, group A (120 kVp, 370 mgI/ml CM); group B (100 kVp, 350 mgI/ml CM); and group C (80 kVp, 320 mgI/ml CM). The CT values, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and figure-of-merit (FOM) of all images …are calculated. Images are subjectively assessed using a 5-point scale. In addition, the CT dose index volume (CTDIvol) and dose length product (DLP) of each patient are recorded. The effective radiation dose (ED) is also calculated. Above data are then statistically analyzed. RESULTS: The mean CT values, SNR, CNR, and subjective image quality of group A are significantly lower than those of groups B and C (P  < 0.001), but there is no significant difference between groups B and C (P  > 0.05). FOMs show a significantly increase trend from group A to C (P  < 0.001). The ED values and total iodine intake in groups B and C are 30.34% and 68.53% and 10.22% and 16.85% lower than those in group A, respectively (P  < 0.001). CONCLUSION: The lower tube voltage and lower concentration of CM based on wide-detector allows for significant reduction in iodine load and radiation dose in CCTA for overweight patients comparing to routine scan protocols. It also enhances signal intensity of CCTA and maintains image quality. Show more

Keywords: Computed tomography angiography, contrast medium, radiation dosage, image quality

DOI: 10.3233/XST-221263

Citation: Journal of X-Ray Science and Technology, vol. 30, no. 6, pp. 1261-1272, 2022

Authors: Yu, Jiadong | He, Yaqun | Hao, Juan | Liu, Fengyongzheng | Li, Hong | Wang, Chao | Wang, Haifeng

Article Type: Retraction

DOI: 10.3233/XST-221307

Citation: Journal of X-Ray Science and Technology, vol. 30, no. 6, pp. 1273-1273, 2022