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Editorial Office of Computerized Tomography Theory and Application
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- Best Articles of CT Theory and Application in 2021
- Outstanding Editors and Outstanding Reviewers of CT Theory and Application in 2022
- Editor ZHAO Xing and His Team Won the First Place in AAPM 2022 "Deep Learning Spectral CT" Contest
- Outstanding Editors of CT Theory and Application 2020-2021
- Editor WANG Zhenchang, Editor ZHANG Li and Editor XING Yuxiang Won the Second Prize of "National Science and Technology Progress Award"
Natural Gas Hydrate CT Image Threshold Segmentation Based on Time Evolution
Micro-scale X-ray computed tomography (CT) has been widely used to study the occurrence forms of gas hydrate-bearing sediments. However, the similarity between the X-ray attenuation coefficient of hydrate and that of water leads to a strong non-uniqueness in their phase differentiation in CT images. To improve threshold segmentation accuracy between hydrate and water in CT images, this study proposes a CT image and histogram normalized method by analyzing the histogram characteristics of CT images at different times during the growth process of natural gas hydrate. First, the peak gray value baseline of methane gas and quartz sand was selected. Then, a Gaussian function was used to fit the curves corresponding to methane gas and quartz sand in the current CT image histogram to obtain the peak gray values. In addition, the peak gray values of methane gas and quartz sand in the current CT image histogram were normalized to the chosen peak gray baseline. Subsequently, the normalized histogram was used to normalize the corresponding CT images. Finally, according to the changing trend of normalized gray histogram curves, the increasing gray ranges of hydrate and decreasing gray ranges of gas-water in CT images were obtained quantitatively, which guided threshold segmentation of CT images. Experimental results show that the proposed threshold segmentation method can provide a basis for phase differentiation between hydrate and water in CT images, improving the threshold segmentation accuracy.
Adaptive Weight Multi-channel Matching Pursuit Algorithm-Based Strong Shielding Removal Method
The strata with large impedance differences are presented as strong amplitude seismic events on the seismic profile, which obscure useful information of nearby reservoirs and need interpretive target processing to remove the strong shielding. Therefore, this study proposes a multi-channel matching pursuit algorithm based on adaptive weight to remove strong shielding. Moreover, to address the problem of poor matching accuracy and spatial continuity of normal multi-channel matching pursuit at area where strong tectonic changes occur, a multi-channel matching pursuit de-strong shielding method based on adaptive weights is proposed. First, we used the layer structure information to flatten the strong reflection layer locally to weaken the influence of stratigraphic structure changes on the extraction of the strong reflection layer. Subsequently, we introduced a correlation coefficient between adjacent seismic traces and the central trace as the weight of multi trace averaging, which improved the stability and lateral continuity of the matching results. The result analysis of model processing tests and practical seismic data application shows that the proposed method can effectively strip the strong reflections and highlight the effective reservoir information; the well seismic match degree is significantly improved with higher matching accuracy, better spatial continuity, and better striping effect than those of the conventional matching pursuit algorithm.
Application of Electromagnetic Waves for Karst Exploration in Urban Tunnels
With rapid urbanization, the contradiction between traffic and the environmental pollution caused by it is becoming increasingly prominent. To preserve ground buildings, an increasing number of tunnel schemes are adopted. Urban Karst exploration is based on drilling, supplemented by traditional geophysical methods such as high-density electrical method and shallow seismic reflection method, which are inefficient and difficult to implement owing to site conditions. As a geophysical exploration technology developed in recent years, electromagnetic wave technology has the advantages of high resolution and convenient field operation, which can better reveal the development scale and characteristics of underground Karst. Based on traditional data processing, setting the minimum value, choosing the reflection projection result as the initial model, using the low-pass filtering and angle-limiting technology, and adopting the structure program of continuous survey mode to carry out normalized calculation processing can greatly improve the accuracy of electromagnetic wave CT data interpretation. The findings of this study show that the electromagnetic wave detection technology can be applied effectively in Karst exploration, and its detection results have great guiding significance in urban tunnel engineering.
Rapid and Continuous Detection Method for Soil-compaction Degrees of Fill Foundation Based on Multichannel Transient Rayleigh Wave Detecting
To address the large treatment area and tight construction period of large-scale engineering site filling foundations and to ensure the quality and progress of the project, understanding the foundation-reinforcement treatment quickly and accurately is essential. Additionally, to ensure the safety and stability of projects, large-scale projects often have higher requirements for the uniformity of the foundation-soil reinforcement effect. The quality-evaluation indices of foundation-soil compaction and reinforcement mainly include the foundation-bearing capacity, foundation-soil deformation modulus, and compaction coefficient. Conventional testing methods primarily include in-situ loading tests, in-situ sand filling, and soil-sample testing. These methods are either labor-intensive and time-consuming or harmful to the reinforced foundation-soil mass, preventing rapid and continuous detection of the foundation-soil mass. To perform rapid and continuous detection of the compaction and reinforcement effects of foundation-soil mass, the multichannel transient Rayleigh wave-detection method, considering the time difference phase between channels, was used in this study. Additionally, the method was supplemented by the sampling tests of soil mass at selected points in this study. Consequently, continuous three-dimensional imaging of the elastic wave velocity of the foundation-soil mass was obtained, along with the horizontal slice of the Rayleigh wave phase velocity imaging and the horizontal-distribution imaging of the depth-average compaction coefficient of the foundation-soil mass. The results reveal that the foundation-soil mass imaging can accurately reflect the compaction and reinforcement effects of the foundation-soil mass, thereby providing a reliable basis for evaluating the quality of foundation-soil mass reinforcement.
Application of AVO Information-constrained Matching Pursuit Technique in Rich Coal Reservoir Characterization
To address the low accuracy of reservoir characterization in XiHu Sag in a coal-rich environment, this study developed a matching pursuit technology based on AVO information constraints combined with the AVO intercept and gradient characteristics of coal. It can suppress the strong reflectance lithologic artifacts caused by coal and highlight actual and effective reservoir signals. Based on the negative intercept P and positive gradient G of the AVO of coal, the seismic–sensitive factor P–G of coal identification was developed to amplify the seismic response of coal and suppress the high-amplitude response of non-coal. Then, to accurately identify the location of coal, the seismic information of coal was used as the original signal that needs to be decomposed and reconstructed by matching pursuit. Additionally, the efficiency of signal-matching decomposition was improved using the technology of complex seismic track analysis. Finally, the strong reflection elimination of coal was completed. Model trials and practical applications indicate that this method could accurately identify the seismic response location of coal and improve the efficiency of the matching pursuit algorithm. Moreover, the coal-eliminated seismic data can better highlight the lateral distribution changes of the reservoir and improve the vertical characterization accuracy of the main gas layer.
Articles Online First have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
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doi: 10.15953/j.ctta.2022.236
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doi: 10.15953/j.ctta.2022.215
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2023, 32(2): 153-169.
doi: 10.15953/j.ctta.2022.190
Abstract:
The total variation (TV) minimization algorithm is an effective CT image reconstruction algorithm that can reconstruct sparse or noisy projection data with high accuracy. However, in some cases, the TV algorithm produces stepped artifacts. The relative TV algorithm outperforms TV algorithm in the field of image denoising. In view of this, the relative TV model is introduced into image reconstruction, a relative TV minimum optimization model is proposed, and the corresponding solution algorithm is designed under the framework of adaptive gradient descent projection to the convex set (ASD-POCS) to further improve reconstruction accuracy. The reconstruction experiments were conducted with Shepp Logan, Forbild, and real CT image simulation models to verify the anti-crime ability of the algorithm and evaluate the sparse reconstruction and anti-noise abilities of the algorithm. The experimental findings reveal that the algorithm outperforms the TV method in terms of anti-crime capability and the ability to reconstruct sparse or noisy projection data with high precision. Compared with the TV algorithm, the algorithm can achieve higher reconstruction accuracy.
The total variation (TV) minimization algorithm is an effective CT image reconstruction algorithm that can reconstruct sparse or noisy projection data with high accuracy. However, in some cases, the TV algorithm produces stepped artifacts. The relative TV algorithm outperforms TV algorithm in the field of image denoising. In view of this, the relative TV model is introduced into image reconstruction, a relative TV minimum optimization model is proposed, and the corresponding solution algorithm is designed under the framework of adaptive gradient descent projection to the convex set (ASD-POCS) to further improve reconstruction accuracy. The reconstruction experiments were conducted with Shepp Logan, Forbild, and real CT image simulation models to verify the anti-crime ability of the algorithm and evaluate the sparse reconstruction and anti-noise abilities of the algorithm. The experimental findings reveal that the algorithm outperforms the TV method in terms of anti-crime capability and the ability to reconstruct sparse or noisy projection data with high precision. Compared with the TV algorithm, the algorithm can achieve higher reconstruction accuracy.
2023, 32(2): 171-178.
doi: 10.15953/j.ctta.2022.062
Abstract:
Micro-scale X-ray computed tomography (CT) has been widely used to study the occurrence forms of gas hydrate-bearing sediments. However, the similarity between the X-ray attenuation coefficient of hydrate and that of water leads to a strong non-uniqueness in their phase differentiation in CT images. To improve threshold segmentation accuracy between hydrate and water in CT images, this study proposes a CT image and histogram normalized method by analyzing the histogram characteristics of CT images at different times during the growth process of natural gas hydrate. First, the peak gray value baseline of methane gas and quartz sand was selected. Then, a Gaussian function was used to fit the curves corresponding to methane gas and quartz sand in the current CT image histogram to obtain the peak gray values. In addition, the peak gray values of methane gas and quartz sand in the current CT image histogram were normalized to the chosen peak gray baseline. Subsequently, the normalized histogram was used to normalize the corresponding CT images. Finally, according to the changing trend of normalized gray histogram curves, the increasing gray ranges of hydrate and decreasing gray ranges of gas-water in CT images were obtained quantitatively, which guided threshold segmentation of CT images. Experimental results show that the proposed threshold segmentation method can provide a basis for phase differentiation between hydrate and water in CT images, improving the threshold segmentation accuracy.
Micro-scale X-ray computed tomography (CT) has been widely used to study the occurrence forms of gas hydrate-bearing sediments. However, the similarity between the X-ray attenuation coefficient of hydrate and that of water leads to a strong non-uniqueness in their phase differentiation in CT images. To improve threshold segmentation accuracy between hydrate and water in CT images, this study proposes a CT image and histogram normalized method by analyzing the histogram characteristics of CT images at different times during the growth process of natural gas hydrate. First, the peak gray value baseline of methane gas and quartz sand was selected. Then, a Gaussian function was used to fit the curves corresponding to methane gas and quartz sand in the current CT image histogram to obtain the peak gray values. In addition, the peak gray values of methane gas and quartz sand in the current CT image histogram were normalized to the chosen peak gray baseline. Subsequently, the normalized histogram was used to normalize the corresponding CT images. Finally, according to the changing trend of normalized gray histogram curves, the increasing gray ranges of hydrate and decreasing gray ranges of gas-water in CT images were obtained quantitatively, which guided threshold segmentation of CT images. Experimental results show that the proposed threshold segmentation method can provide a basis for phase differentiation between hydrate and water in CT images, improving the threshold segmentation accuracy.
2023, 32(2): 179-188.
doi: 10.15953/j.ctta.2022.120
Abstract:
The strata with large impedance differences are presented as strong amplitude seismic events on the seismic profile, which obscure useful information of nearby reservoirs and need interpretive target processing to remove the strong shielding. Therefore, this study proposes a multi-channel matching pursuit algorithm based on adaptive weight to remove strong shielding. Moreover, to address the problem of poor matching accuracy and spatial continuity of normal multi-channel matching pursuit at area where strong tectonic changes occur, a multi-channel matching pursuit de-strong shielding method based on adaptive weights is proposed. First, we used the layer structure information to flatten the strong reflection layer locally to weaken the influence of stratigraphic structure changes on the extraction of the strong reflection layer. Subsequently, we introduced a correlation coefficient between adjacent seismic traces and the central trace as the weight of multi trace averaging, which improved the stability and lateral continuity of the matching results. The result analysis of model processing tests and practical seismic data application shows that the proposed method can effectively strip the strong reflections and highlight the effective reservoir information; the well seismic match degree is significantly improved with higher matching accuracy, better spatial continuity, and better striping effect than those of the conventional matching pursuit algorithm.
The strata with large impedance differences are presented as strong amplitude seismic events on the seismic profile, which obscure useful information of nearby reservoirs and need interpretive target processing to remove the strong shielding. Therefore, this study proposes a multi-channel matching pursuit algorithm based on adaptive weight to remove strong shielding. Moreover, to address the problem of poor matching accuracy and spatial continuity of normal multi-channel matching pursuit at area where strong tectonic changes occur, a multi-channel matching pursuit de-strong shielding method based on adaptive weights is proposed. First, we used the layer structure information to flatten the strong reflection layer locally to weaken the influence of stratigraphic structure changes on the extraction of the strong reflection layer. Subsequently, we introduced a correlation coefficient between adjacent seismic traces and the central trace as the weight of multi trace averaging, which improved the stability and lateral continuity of the matching results. The result analysis of model processing tests and practical seismic data application shows that the proposed method can effectively strip the strong reflections and highlight the effective reservoir information; the well seismic match degree is significantly improved with higher matching accuracy, better spatial continuity, and better striping effect than those of the conventional matching pursuit algorithm.
2023, 32(2): 189-197.
doi: 10.15953/j.ctta.2022.218
Abstract:
To address the low accuracy of reservoir characterization in XiHu Sag in a coal-rich environment, this study developed a matching pursuit technology based on AVO information constraints combined with the AVO intercept and gradient characteristics of coal. It can suppress the strong reflectance lithologic artifacts caused by coal and highlight actual and effective reservoir signals. Based on the negative intercept P and positive gradient G of the AVO of coal, the seismic–sensitive factor P–G of coal identification was developed to amplify the seismic response of coal and suppress the high-amplitude response of non-coal. Then, to accurately identify the location of coal, the seismic information of coal was used as the original signal that needs to be decomposed and reconstructed by matching pursuit. Additionally, the efficiency of signal-matching decomposition was improved using the technology of complex seismic track analysis. Finally, the strong reflection elimination of coal was completed. Model trials and practical applications indicate that this method could accurately identify the seismic response location of coal and improve the efficiency of the matching pursuit algorithm. Moreover, the coal-eliminated seismic data can better highlight the lateral distribution changes of the reservoir and improve the vertical characterization accuracy of the main gas layer.
To address the low accuracy of reservoir characterization in XiHu Sag in a coal-rich environment, this study developed a matching pursuit technology based on AVO information constraints combined with the AVO intercept and gradient characteristics of coal. It can suppress the strong reflectance lithologic artifacts caused by coal and highlight actual and effective reservoir signals. Based on the negative intercept P and positive gradient G of the AVO of coal, the seismic–sensitive factor P–G of coal identification was developed to amplify the seismic response of coal and suppress the high-amplitude response of non-coal. Then, to accurately identify the location of coal, the seismic information of coal was used as the original signal that needs to be decomposed and reconstructed by matching pursuit. Additionally, the efficiency of signal-matching decomposition was improved using the technology of complex seismic track analysis. Finally, the strong reflection elimination of coal was completed. Model trials and practical applications indicate that this method could accurately identify the seismic response location of coal and improve the efficiency of the matching pursuit algorithm. Moreover, the coal-eliminated seismic data can better highlight the lateral distribution changes of the reservoir and improve the vertical characterization accuracy of the main gas layer.
2023, 32(2): 198-208.
doi: 10.15953/j.ctta.2022.083
Abstract:
To improve the accuracy and efficiency of identifying the relationship between the root of the impacted mandibular third molar (M3M) and the mandibular canal in panoramic radiographs, we proposed an automatic method based on a deep convolutional neural network. This method treats the automatic identification of the relationship between the root of the M3M and the mandibular canal as a combination of regression and classification tasks. It uses the YOLOv5 (You Only Look Once) network as a framework for constructing a deep convolutional neural network that can accomplish detection and classification tasks simultaneously. This network, which takes the spatial relationship information extracted from the corresponding cone-beam CT images as the ground-truth, was trained to learn the nonlinear relationship between image features and the root of the M3M contacting the mandibular canal. When inputting a newly acquired panoramic radiograph into the trained network, the network will output the probability value for the root of the M3M contacting the mandibular canal. In the meantime, the region that includes the root of the M3M contacting the mandibular canal can be predicted. The experimental results show that the proposed method can provide an accurate judgment of whether the roots of impacted mandibular wisdom teeth in the panoramic radiographs are in contact with the mandibular canal and the location of regions in which the roots of the M3M are in contact with the mandibular canals; compared to manual diagnosis and the other methods, the proposed method can obtain more accurate results.
To improve the accuracy and efficiency of identifying the relationship between the root of the impacted mandibular third molar (M3M) and the mandibular canal in panoramic radiographs, we proposed an automatic method based on a deep convolutional neural network. This method treats the automatic identification of the relationship between the root of the M3M and the mandibular canal as a combination of regression and classification tasks. It uses the YOLOv5 (You Only Look Once) network as a framework for constructing a deep convolutional neural network that can accomplish detection and classification tasks simultaneously. This network, which takes the spatial relationship information extracted from the corresponding cone-beam CT images as the ground-truth, was trained to learn the nonlinear relationship between image features and the root of the M3M contacting the mandibular canal. When inputting a newly acquired panoramic radiograph into the trained network, the network will output the probability value for the root of the M3M contacting the mandibular canal. In the meantime, the region that includes the root of the M3M contacting the mandibular canal can be predicted. The experimental results show that the proposed method can provide an accurate judgment of whether the roots of impacted mandibular wisdom teeth in the panoramic radiographs are in contact with the mandibular canal and the location of regions in which the roots of the M3M are in contact with the mandibular canals; compared to manual diagnosis and the other methods, the proposed method can obtain more accurate results.
2023, 32(2): 209-215.
doi: 10.15953/j.ctta.2022.070
Abstract:
Objective: To explore the clinical value of whole-body 18F-FDG PET/CT combined with neuroantibody detection in the diagnosis and treatment of paraneoplastic neurological syndromes (PNS). Methods: Clinical, laboratory, and imaging data of 56 hospitalized patients with suspected PNS who underwent systemic 18F-FDG PET/CT and neuropathic tumor antibody detection were retrospectively collected and followed-up on. ROC curve analysis was performed to compare the diagnostic efficacy of PET/CT, neuronal antibodies, and their combined detection results. Results: Among the 56 patients with suspected PNS, there were 20 with malignant tumors, including 19 cases complicated with PNS and 1 patient with spinal cord metastasis which also le d to neurological symptoms. 18F-FDG PET/CT imaging indicated tumors or possible tumors in 23 cases, of which 20 cases were true positive, 3 cases were false positive (the follow-up results were reflux esophagitis, reactive bone changes, or inflammatory lesions in the neck), and the remaining 33 cases were true negative. The sensitivity, specificity, and accuracy of PET/CT were 100%, 91.7%, and 94.6%, respectively. There were 33 cases with positive neuroantibodies, including 8 cases of tumors with PNS (3 cases with anti-amphiphysin antibody encephalitis, 2 cases with anti-GABAb antibody encephalitis, 1 case with anti-Yo antibody encephalitis, and 2 cases with anti-Hu antibody encephalitis). Moreover, there were 25 cases without tumors (10 cases with LGI1 antibody encephalitis, 3 cases with anti-amphiphysin antibody encephalitis, 1 case with anti-Hu antibody encephalitis, 3 cases with anti-GABAb antibody encephalitis, 3 cases with anti-Yo antibody encephalitis, 1 case with Anti-caspr2, 1 case with GAD65, 1 case with NMDA, 1 case with PNMA, and 1 case with SOX1 antibody (1 case each). Of these, 23 cases were negative (12 cases with tumor). The sensitivity, specificity, and accuracy of the neuronal antibody test were 40.0%, 30.6%, and 33.9%, respectively. Furthermore, the sensitivity, specificity, and accuracy of the combined detection were 100.0%, 33.3%, 57.1%, 50%, 94.4%, and 78.6%, respectively. ROC analysis showed that the AUC was 0.958 (P=0.000<0.05; 95% CI 0.904~1.000), 0.353 (P=0.070>0.05; 95% CI 0.199~0.506), 0.667 (P=0.040<0.05; 95% CI 0.528~0.806), and 0.672 (P=0.034<0.05; 95% CI 0.514~0.830). Conclusion: Whole-body 18F-FDG PET/CT has the potential to be the first choice for noninvasive tumor screening in patients with suspected PNS.
Objective: To explore the clinical value of whole-body 18F-FDG PET/CT combined with neuroantibody detection in the diagnosis and treatment of paraneoplastic neurological syndromes (PNS). Methods: Clinical, laboratory, and imaging data of 56 hospitalized patients with suspected PNS who underwent systemic 18F-FDG PET/CT and neuropathic tumor antibody detection were retrospectively collected and followed-up on. ROC curve analysis was performed to compare the diagnostic efficacy of PET/CT, neuronal antibodies, and their combined detection results. Results: Among the 56 patients with suspected PNS, there were 20 with malignant tumors, including 19 cases complicated with PNS and 1 patient with spinal cord metastasis which also le d to neurological symptoms. 18F-FDG PET/CT imaging indicated tumors or possible tumors in 23 cases, of which 20 cases were true positive, 3 cases were false positive (the follow-up results were reflux esophagitis, reactive bone changes, or inflammatory lesions in the neck), and the remaining 33 cases were true negative. The sensitivity, specificity, and accuracy of PET/CT were 100%, 91.7%, and 94.6%, respectively. There were 33 cases with positive neuroantibodies, including 8 cases of tumors with PNS (3 cases with anti-amphiphysin antibody encephalitis, 2 cases with anti-GABAb antibody encephalitis, 1 case with anti-Yo antibody encephalitis, and 2 cases with anti-Hu antibody encephalitis). Moreover, there were 25 cases without tumors (10 cases with LGI1 antibody encephalitis, 3 cases with anti-amphiphysin antibody encephalitis, 1 case with anti-Hu antibody encephalitis, 3 cases with anti-GABAb antibody encephalitis, 3 cases with anti-Yo antibody encephalitis, 1 case with Anti-caspr2, 1 case with GAD65, 1 case with NMDA, 1 case with PNMA, and 1 case with SOX1 antibody (1 case each). Of these, 23 cases were negative (12 cases with tumor). The sensitivity, specificity, and accuracy of the neuronal antibody test were 40.0%, 30.6%, and 33.9%, respectively. Furthermore, the sensitivity, specificity, and accuracy of the combined detection were 100.0%, 33.3%, 57.1%, 50%, 94.4%, and 78.6%, respectively. ROC analysis showed that the AUC was 0.958 (P=0.000<0.05; 95% CI 0.904~1.000), 0.353 (P=0.070>0.05; 95% CI 0.199~0.506), 0.667 (P=0.040<0.05; 95% CI 0.528~0.806), and 0.672 (P=0.034<0.05; 95% CI 0.514~0.830). Conclusion: Whole-body 18F-FDG PET/CT has the potential to be the first choice for noninvasive tumor screening in patients with suspected PNS.
2023, 32(2): 217-222.
doi: 10.15953/j.ctta.2022.219
Abstract:
Objective: To investigate the risk factors of plaque progression in patients with angina pectoris and their relationships with coronary computed tomography (CT) angiography. Methods: Clinical data of 236 patients with angina pectoris were retrospectively analyzed from January 2017 to January 2020. All patients were grouped according to whether plaque progression occurred, and the general information and coronary CT angiography indexes were compared between the two groups. A logistic regression model was used to evaluate the independent risk factors of plaque progression in patients with angina pectoris. The receiver operating characteristic (ROC) curve was delineated to analyze the clinical value of the prediction model based on coronary CT angiography indicators in predicting plaque progression risk. Results: There were significant differences in sex, the proportion of hyperlipidemia, proportion of statins, degree of stenosis, minimum lumen area, total plaque volume, RI, and CT-derived fractional flow reserve (FFR) between the two groups. The results of single factor analysis showed that the degree of stenosis, the minimum lumen area, plaque volume, the volume of non-calcified plaque, RI, and CT-FFR levels were related to the plaque progression in patients with angina pectoris. Univariate analysis showed that the degree of stenosis, minimum lumen area, plaque volume, non-calcified plaque volume, RI, and CT-FFR levels were associated with plaque progression in patients with angina pectoris. Multivariate analysis showed that RI and CT-FFR levels were independent factors of plaque progression in patients with angina pectoris. ROC curve analysis showed that the combination of stenosis degree + RI + CT-FFR was better than that of simple stenosis degree and stenosis degree + RI in predicting the area under the curve of plaque progression. Conclusion: RI and CT-FFR levels are important factors leading to plaque progression in patients with angina pectoris. The prediction model based on RI and CT-FFR can more accurately identify plaque progression.
Objective: To investigate the risk factors of plaque progression in patients with angina pectoris and their relationships with coronary computed tomography (CT) angiography. Methods: Clinical data of 236 patients with angina pectoris were retrospectively analyzed from January 2017 to January 2020. All patients were grouped according to whether plaque progression occurred, and the general information and coronary CT angiography indexes were compared between the two groups. A logistic regression model was used to evaluate the independent risk factors of plaque progression in patients with angina pectoris. The receiver operating characteristic (ROC) curve was delineated to analyze the clinical value of the prediction model based on coronary CT angiography indicators in predicting plaque progression risk. Results: There were significant differences in sex, the proportion of hyperlipidemia, proportion of statins, degree of stenosis, minimum lumen area, total plaque volume, RI, and CT-derived fractional flow reserve (FFR) between the two groups. The results of single factor analysis showed that the degree of stenosis, the minimum lumen area, plaque volume, the volume of non-calcified plaque, RI, and CT-FFR levels were related to the plaque progression in patients with angina pectoris. Univariate analysis showed that the degree of stenosis, minimum lumen area, plaque volume, non-calcified plaque volume, RI, and CT-FFR levels were associated with plaque progression in patients with angina pectoris. Multivariate analysis showed that RI and CT-FFR levels were independent factors of plaque progression in patients with angina pectoris. ROC curve analysis showed that the combination of stenosis degree + RI + CT-FFR was better than that of simple stenosis degree and stenosis degree + RI in predicting the area under the curve of plaque progression. Conclusion: RI and CT-FFR levels are important factors leading to plaque progression in patients with angina pectoris. The prediction model based on RI and CT-FFR can more accurately identify plaque progression.
2023, 32(2): 223-230.
doi: 10.15953/j.ctta.2022.245
Abstract:
Objective: To analyze the clinical characteristics and imaging features of primary orbital lymphoma in order to improve early diagnosis of the disease. Methods: Eighty-two patients were recruited from January 2015 to May 2022 who were diagnosed with orbital lymphomas via histopathology. The data on clinical characteristics, pathological subtypes, and imaging features for those patients were analyzed including symptoms, uni- or bilateral eye involvement, single or multiple lesions, tumor location, growth pattern, MRI signal intensity and MRI/CT enhancement patterns. Results: Eyelid swelling (52/82, 63.4%) and proptosis (43/82, 52.4%) were the two most common symptoms for primary orbital lymphomas, whose pathologic subtypes were mainly B-cell lymphomas, especially mucosa-associated lymphoid tissue lymphoma (60/82, 73.2%), and 59 cases (59/82, 72.0%) had unilateral eye involvement. Conjunctiva was the most common location (29/82, 35.4%), followed by eyelid (16/82, 19.5%) and muscle cone (11/82, 13.4%). Of the 66 cases who underwent MRI examinations, 60 showed iso-intensity on T1WI (90.9%), and 51 showed hyper-intensity on T2WI (77.3%). The tumors showed obvious enhancement on contrast-enhanced MRI or CT with 74.2% and 70.5%, respectively. Two other cases showed adjacent bone involvement on CT. Conclusion: B-cell lymphoma, especially mucosa-associated lymphoid tissue lymphoma was the most common primary orbital lymphoma subtype. The tumors mostly had unilateral eye involvement and the conjunctiva was the most common location. The typical imaging features were obvious enhancement on contrast-enhanced MRI or CT that would facilitate tumor diagnosis and treatment decision.
Objective: To analyze the clinical characteristics and imaging features of primary orbital lymphoma in order to improve early diagnosis of the disease. Methods: Eighty-two patients were recruited from January 2015 to May 2022 who were diagnosed with orbital lymphomas via histopathology. The data on clinical characteristics, pathological subtypes, and imaging features for those patients were analyzed including symptoms, uni- or bilateral eye involvement, single or multiple lesions, tumor location, growth pattern, MRI signal intensity and MRI/CT enhancement patterns. Results: Eyelid swelling (52/82, 63.4%) and proptosis (43/82, 52.4%) were the two most common symptoms for primary orbital lymphomas, whose pathologic subtypes were mainly B-cell lymphomas, especially mucosa-associated lymphoid tissue lymphoma (60/82, 73.2%), and 59 cases (59/82, 72.0%) had unilateral eye involvement. Conjunctiva was the most common location (29/82, 35.4%), followed by eyelid (16/82, 19.5%) and muscle cone (11/82, 13.4%). Of the 66 cases who underwent MRI examinations, 60 showed iso-intensity on T1WI (90.9%), and 51 showed hyper-intensity on T2WI (77.3%). The tumors showed obvious enhancement on contrast-enhanced MRI or CT with 74.2% and 70.5%, respectively. Two other cases showed adjacent bone involvement on CT. Conclusion: B-cell lymphoma, especially mucosa-associated lymphoid tissue lymphoma was the most common primary orbital lymphoma subtype. The tumors mostly had unilateral eye involvement and the conjunctiva was the most common location. The typical imaging features were obvious enhancement on contrast-enhanced MRI or CT that would facilitate tumor diagnosis and treatment decision.
2023, 32(2): 231-239.
doi: 10.15953/j.ctta.2022.158
Abstract:
Objective: To observe the CT and MRI findings in newly diagnosed patients with IgG4-related sclerosing cholangitis (IgG4-SC) and explore their correlations with serum IgG4 and IgG levels. Methods: The clinical, laboratory, and imaging data of 50 newly diagnosed IgG4-SC patients were retrospectively summarized. The type of lesions, shape of lumen stenosis, degree of dilatation of the diseased bile ducts on MRCP, characteristics and enhancement patterns of the thickened bile duct walls, and the number of other coexisting IgG4-RDs on enhanced MRI and CT were observed. Subsequently, the correlations of the patients' baseline serum IgG4 and IgG levels with the severity of bile duct lesions and the number of other coexisting IgG4-RDs were analyzed. Results: Forty-one patients underwent MRCP examinations, and the following types of IgG4-SC were identified: type Ⅰ in 28 cases, type Ⅱa in 11, type Ⅲ in 1, and type Ⅳ in 1. Extrahepatic bile duct stenosis was funnel-shaped in 37 cases and truncated in 4 cases. Moreover, all the stenotic segments were long (≥1.0 cm) and one diverticulum-like outpouching was seen in the pancreatic segment stenosis. Upstream bile ducts of the stenosis showed dilatation in 37 cases, while the other 4 cases did not show this. Contrast-enhanced MRI and CT examinations showed continuous thickening of the extrahepatic bile duct walls in 42 cases, and diffuse thickening of the intrahepatic bile duct walls was simultaneously observed in 15 cases among them. The thickness of the bile duct walls was uniformly concentric. Meanwhile, other accompanying IgG4-RDs included AIP in 50 cases, kidney involvement in 19, salivary gland involvement in 7, retroperitoneal fibrosis in 5, liver involvement in 4, lung involvement in 4, prostate involvement in 2, sclerosing mediastinitis in 2, thickened gallbladder wall (without stones) in 20, and enlarged upper abdominal lymph nodes in 15 cases. Moreover, higher baseline serum IgG4 and IgG levels were positively correlated with the number of other coexisting IgG4-RDs, but not with the bile duct wall thickness and stenotic segment length. Conclusions: Localized stenosis of the bile ducts with dilatation or non-dilation of the upstream bile ducts, as well as diffuse thickening of the bile duct walls, are the MRI and CT features of newly diagnosed patients with IgG4-SC. Furthermore, higher baseline serum IgG4 and IgG levels are not related to the severity of the diseased bile ducts but are related to the number of other coexisting IgG4-RDs.
Objective: To observe the CT and MRI findings in newly diagnosed patients with IgG4-related sclerosing cholangitis (IgG4-SC) and explore their correlations with serum IgG4 and IgG levels. Methods: The clinical, laboratory, and imaging data of 50 newly diagnosed IgG4-SC patients were retrospectively summarized. The type of lesions, shape of lumen stenosis, degree of dilatation of the diseased bile ducts on MRCP, characteristics and enhancement patterns of the thickened bile duct walls, and the number of other coexisting IgG4-RDs on enhanced MRI and CT were observed. Subsequently, the correlations of the patients' baseline serum IgG4 and IgG levels with the severity of bile duct lesions and the number of other coexisting IgG4-RDs were analyzed. Results: Forty-one patients underwent MRCP examinations, and the following types of IgG4-SC were identified: type Ⅰ in 28 cases, type Ⅱa in 11, type Ⅲ in 1, and type Ⅳ in 1. Extrahepatic bile duct stenosis was funnel-shaped in 37 cases and truncated in 4 cases. Moreover, all the stenotic segments were long (≥1.0 cm) and one diverticulum-like outpouching was seen in the pancreatic segment stenosis. Upstream bile ducts of the stenosis showed dilatation in 37 cases, while the other 4 cases did not show this. Contrast-enhanced MRI and CT examinations showed continuous thickening of the extrahepatic bile duct walls in 42 cases, and diffuse thickening of the intrahepatic bile duct walls was simultaneously observed in 15 cases among them. The thickness of the bile duct walls was uniformly concentric. Meanwhile, other accompanying IgG4-RDs included AIP in 50 cases, kidney involvement in 19, salivary gland involvement in 7, retroperitoneal fibrosis in 5, liver involvement in 4, lung involvement in 4, prostate involvement in 2, sclerosing mediastinitis in 2, thickened gallbladder wall (without stones) in 20, and enlarged upper abdominal lymph nodes in 15 cases. Moreover, higher baseline serum IgG4 and IgG levels were positively correlated with the number of other coexisting IgG4-RDs, but not with the bile duct wall thickness and stenotic segment length. Conclusions: Localized stenosis of the bile ducts with dilatation or non-dilation of the upstream bile ducts, as well as diffuse thickening of the bile duct walls, are the MRI and CT features of newly diagnosed patients with IgG4-SC. Furthermore, higher baseline serum IgG4 and IgG levels are not related to the severity of the diseased bile ducts but are related to the number of other coexisting IgG4-RDs.
2023, 32(2): 241-248.
doi: 10.15953/j.ctta.2022.099
Abstract:
Objective: To explore the value of the artificial intelligence (AI) volumetric density method in determining the invasion of pulmonary hyposolid nodules (SSNs). Methods: A total of 108 SSNs and the pathological results of 106 patients were reviewed, and these were divided into a glandular prodromal lesions group and an adenocarcinoma group. Pulmonary nodule AI software was used to measure and compare the CT quantitative parameters of the two groups, including the maximum CT value, minimum CT value, average CT value, kurtosis, skewness, Perc.25%, Perc.50%, Perc.75%, Perc.90%, nodule volume, and mean nodule diameter. Moreover, a receiver operating characteristic curve (ROC) was obtained by MedCalc software to evaluate the sensitivity, specificity, positive predictive value, and negative predictive value for the diagnosis of SSN infiltration, and their diagnostic performance was evaluated by logistic regression analysis. Results: There were significant differences in most CT quantitative parameters of SSNs. The highest diagnostic efficiency was Perc.25% and the AUC was 0.797, while the AUC was 0.787 for Perc.50% and the mean CT value. Logistic regression analysis showed that Perc.25% with the highest diagnostic efficiency was combined with Perc.50% and the mean CT value. The model with Perc.25% and the mean CT value had the highest diagnostic efficiency, and the combined diagnostic model had a higher diagnostic efficiency than Perc.25% and the mean CT value alone. According to MedCalc software, SSNs with Perc.25% ≥−578 HU and mean CT values ≥ −468 HU were more likely to be in the adenocarcinoma group. In this study, Perc.25% was combined with the mean diameter of nodules, and a very valuable combined diagnostic model II was obtained to judge the infiltration of SSNs. Conclusion: The AI volume density method has a high diagnostic value for SSN invasion. Moreover , the combination of Perc.25% and mean CT value can accurately judge the invasion than the use of average CT value alone, providing a quantitative basis for the clinical management of SSNs.
Objective: To explore the value of the artificial intelligence (AI) volumetric density method in determining the invasion of pulmonary hyposolid nodules (SSNs). Methods: A total of 108 SSNs and the pathological results of 106 patients were reviewed, and these were divided into a glandular prodromal lesions group and an adenocarcinoma group. Pulmonary nodule AI software was used to measure and compare the CT quantitative parameters of the two groups, including the maximum CT value, minimum CT value, average CT value, kurtosis, skewness, Perc.25%, Perc.50%, Perc.75%, Perc.90%, nodule volume, and mean nodule diameter. Moreover, a receiver operating characteristic curve (ROC) was obtained by MedCalc software to evaluate the sensitivity, specificity, positive predictive value, and negative predictive value for the diagnosis of SSN infiltration, and their diagnostic performance was evaluated by logistic regression analysis. Results: There were significant differences in most CT quantitative parameters of SSNs. The highest diagnostic efficiency was Perc.25% and the AUC was 0.797, while the AUC was 0.787 for Perc.50% and the mean CT value. Logistic regression analysis showed that Perc.25% with the highest diagnostic efficiency was combined with Perc.50% and the mean CT value. The model with Perc.25% and the mean CT value had the highest diagnostic efficiency, and the combined diagnostic model had a higher diagnostic efficiency than Perc.25% and the mean CT value alone. According to MedCalc software, SSNs with Perc.25% ≥−578 HU and mean CT values ≥ −468 HU were more likely to be in the adenocarcinoma group. In this study, Perc.25% was combined with the mean diameter of nodules, and a very valuable combined diagnostic model II was obtained to judge the infiltration of SSNs. Conclusion: The AI volume density method has a high diagnostic value for SSN invasion. Moreover , the combination of Perc.25% and mean CT value can accurately judge the invasion than the use of average CT value alone, providing a quantitative basis for the clinical management of SSNs.
2023, 32(2): 249-255.
doi: 10.15953/j.ctta.2022.048
Abstract:
Objective: To study the CT and MRI findings of nuchal-type fibromas. Methods: Eight cases of surgically resected and pathologically confirmed nuchal-type fibroma were retrospectively analyzed. Results: All lesions were firm and located in the subcutaneous tissue of the sacrococcygeal region. Upon CT and MRI, local skin thickening was observed . The lesions were ill-defined and had irregular morphology. Moreover, the lesions showed slightly high density on CT, low signal intensity on T1WI and T2WI, and isosignal on DWI. Enhancement scanning was performed in two patients, with one mild and one moderate enhancement. Conclusion: The CT and MRI findings of nuchal-type fibromas have some characteristic features. Combined with medical history and clinical manifestations, these can assist in diagnosis
Objective: To study the CT and MRI findings of nuchal-type fibromas. Methods: Eight cases of surgically resected and pathologically confirmed nuchal-type fibroma were retrospectively analyzed. Results: All lesions were firm and located in the subcutaneous tissue of the sacrococcygeal region. Upon CT and MRI, local skin thickening was observed . The lesions were ill-defined and had irregular morphology. Moreover, the lesions showed slightly high density on CT, low signal intensity on T1WI and T2WI, and isosignal on DWI. Enhancement scanning was performed in two patients, with one mild and one moderate enhancement. Conclusion: The CT and MRI findings of nuchal-type fibromas have some characteristic features. Combined with medical history and clinical manifestations, these can assist in diagnosis
2023, 32(2): 256-262.
doi: 10.15953/j.ctta.2022.050
Abstract:
This study analyzes body composition information in patients on maintenance hemodialysis and explores the application value of QCT technology. Methods: A total of 62 patients on maintenance hemodialysis were selected and divided into three groups according to different dialysis durations. The bone density value, abdominal fat, and muscle content of patients were determined by quantitative CT technology and 62 cases of the health examination population matched by sex and age were selected for comparative analysis. Results: In the dialysis group, osteoporosis accounted for 17.70% (11 cases) and bone loss accounted for 30.60% (19 cases), while in the healthy control group, osteoporosis and bone loss accounted for 6.50% (4 cases) and 16.10% (10 cases), respectively. The difference between these two groups was statistically significant. Moreover, the intra-abdominal and subcutaneous fat content in the dialysis group were (113.70±63.29)cm² and (80.65±59.67)cm², respectively, which were lower than that of the healthy control group ((135.90±58.80)cm² and (122.26±54.94)cm², respectively). Additionally, the dialysis group had a significantly lower L3-SMA (107.00±30.70)cm² than the control group (121.37±32.87)cm², and the lumbar vertebral bone density value was significantly lower in male dialysis patients (156.11±51.94)mg/cm³ than in female dialysis patients (124.29±50.89)mg/cm³. Moreover, the subcutaneous fat content was significantly higher in females than in males; however, the difference in intraperitoneal fat content between males and females was not statistically significant. Additionally, the difference between bone density values and L3-SMA changes in the dialysis group and the length of dialysis time were not statistically significant. Conclusion: The incidence of osteoporosis is higher in patients on maintenance hemodialysis than in healthy people, and the amount of abdominal fat and muscle content are lower than that in healthy people. Moreover, quantitative CT body composition monitoring has high accuracy and sensitivity.
This study analyzes body composition information in patients on maintenance hemodialysis and explores the application value of QCT technology. Methods: A total of 62 patients on maintenance hemodialysis were selected and divided into three groups according to different dialysis durations. The bone density value, abdominal fat, and muscle content of patients were determined by quantitative CT technology and 62 cases of the health examination population matched by sex and age were selected for comparative analysis. Results: In the dialysis group, osteoporosis accounted for 17.70% (11 cases) and bone loss accounted for 30.60% (19 cases), while in the healthy control group, osteoporosis and bone loss accounted for 6.50% (4 cases) and 16.10% (10 cases), respectively. The difference between these two groups was statistically significant. Moreover, the intra-abdominal and subcutaneous fat content in the dialysis group were (113.70±63.29)cm² and (80.65±59.67)cm², respectively, which were lower than that of the healthy control group ((135.90±58.80)cm² and (122.26±54.94)cm², respectively). Additionally, the dialysis group had a significantly lower L3-SMA (107.00±30.70)cm² than the control group (121.37±32.87)cm², and the lumbar vertebral bone density value was significantly lower in male dialysis patients (156.11±51.94)mg/cm³ than in female dialysis patients (124.29±50.89)mg/cm³. Moreover, the subcutaneous fat content was significantly higher in females than in males; however, the difference in intraperitoneal fat content between males and females was not statistically significant. Additionally, the difference between bone density values and L3-SMA changes in the dialysis group and the length of dialysis time were not statistically significant. Conclusion: The incidence of osteoporosis is higher in patients on maintenance hemodialysis than in healthy people, and the amount of abdominal fat and muscle content are lower than that in healthy people. Moreover, quantitative CT body composition monitoring has high accuracy and sensitivity.
2023, 32(2): 263-270.
doi: 10.15953/j.ctta.2023.017
Abstract:
Cronkhite-Canada syndrome (CCS) is a rare cause of chronic diarrhea and malabsorption where patients develop multiple polyps throughout the gastrointestinal (GI) tract, accompanied by ectodermal changes. Due to its rarity, its early detection and diagnosis can be challenging for physicians. This case report described a 58-year-old male patient with CCS who presented with chronic watery diarrhea, hematochezia, weight loss, and skin changes including nail dystrophy and hyperpigmen-tation. Laboratory results showed anemia and hypoalbuminemia. He underwent CT enterography (CTE) which identified diffuse edematous polyposis in the GI tract. The CTE results were highly suspicious of CCS and a subsequent endoscopic examination confirmed the diagnosis. The patient received supportive treatment which improved his symptoms. Based on CTE and endoscopy at 1-year follow-up, the patient was deemed to be in remission. We included a literature review of CCS. The case report aimed to improve the understanding of CCS and explored the key CTE features relevant to its early diagnosis.
Cronkhite-Canada syndrome (CCS) is a rare cause of chronic diarrhea and malabsorption where patients develop multiple polyps throughout the gastrointestinal (GI) tract, accompanied by ectodermal changes. Due to its rarity, its early detection and diagnosis can be challenging for physicians. This case report described a 58-year-old male patient with CCS who presented with chronic watery diarrhea, hematochezia, weight loss, and skin changes including nail dystrophy and hyperpigmen-tation. Laboratory results showed anemia and hypoalbuminemia. He underwent CT enterography (CTE) which identified diffuse edematous polyposis in the GI tract. The CTE results were highly suspicious of CCS and a subsequent endoscopic examination confirmed the diagnosis. The patient received supportive treatment which improved his symptoms. Based on CTE and endoscopy at 1-year follow-up, the patient was deemed to be in remission. We included a literature review of CCS. The case report aimed to improve the understanding of CCS and explored the key CTE features relevant to its early diagnosis.
2023, 32(2): 271-277.
doi: 10.15953/j.ctta.2023.011
Abstract:
This case report describes a rare case of cervical necrotizing fasciitis (CNF) of the nasopharynx. The patient presented with intractable chronic suppurative otitis media and underwent radiological examination including CT, MRI, and PET/CT. All of the images misdiagnosed this condition as nasopharyngeal carcinoma. Finally, the patient underwent a nasopharyngeal mass biopsy and CNF was diagnosed. A retrospective analysis of the radiological scans was performed and the causes of the misdiagnosis were evaluated. The CT, MRI, and PET/CT characteristics and key features for the early diagnosis of CNF were summarized. Our findings may contribute to current knowledge of the precise diagnosis of CNF.
This case report describes a rare case of cervical necrotizing fasciitis (CNF) of the nasopharynx. The patient presented with intractable chronic suppurative otitis media and underwent radiological examination including CT, MRI, and PET/CT. All of the images misdiagnosed this condition as nasopharyngeal carcinoma. Finally, the patient underwent a nasopharyngeal mass biopsy and CNF was diagnosed. A retrospective analysis of the radiological scans was performed and the causes of the misdiagnosis were evaluated. The CT, MRI, and PET/CT characteristics and key features for the early diagnosis of CNF were summarized. Our findings may contribute to current knowledge of the precise diagnosis of CNF.
2023, 32(2): 279-284.
doi: 10.15953/j.ctta.2022.037
Abstract:
Noninvasive coronary fractional flow reserve derived from CT angiography (FFRCT) is a major advance within cardiovascular imaging in recent years. It can identify pathology-specific ischemia and provide information for clinical decisions on revascularization, serving as a gatekeeper for invasive coronary angiography.This paper reviews the research progress of FFRCT and briefly discusses its limitations.
Noninvasive coronary fractional flow reserve derived from CT angiography (FFRCT) is a major advance within cardiovascular imaging in recent years. It can identify pathology-specific ischemia and provide information for clinical decisions on revascularization, serving as a gatekeeper for invasive coronary angiography.This paper reviews the research progress of FFRCT and briefly discusses its limitations.
2023, 32(2): 285-296.
doi: 10.15953/j.ctta.2022.131
Abstract:
In medical computed tomography imaging systems, Compton scattered photons generated by the interaction between X-rays and objects have a serious impact on image quality, especially in cone-beam computed tomography and multi-layer detector systems. Currently, there are many scattering artifact correction methods, which can be classified into three categories: hardware, software, and hybrid software and hardware correction methods. However, with the advances in computing power and development of deep learning in medical image processing, new methods of scattering artifact correction have appeared in recent years. This study first introduces traditional correction methods. Then, a method of scattering artifact correction based on deep learning is described in detail, which is divided into the correction method based on image domain and the correction method based on projection domain. Various deep-learning neural networks for this method are also introduced in detail. Finally, the application prospects of the deep learning method in multi-source computed tomography imaging scattering artifacts were probed .
In medical computed tomography imaging systems, Compton scattered photons generated by the interaction between X-rays and objects have a serious impact on image quality, especially in cone-beam computed tomography and multi-layer detector systems. Currently, there are many scattering artifact correction methods, which can be classified into three categories: hardware, software, and hybrid software and hardware correction methods. However, with the advances in computing power and development of deep learning in medical image processing, new methods of scattering artifact correction have appeared in recent years. This study first introduces traditional correction methods. Then, a method of scattering artifact correction based on deep learning is described in detail, which is divided into the correction method based on image domain and the correction method based on projection domain. Various deep-learning neural networks for this method are also introduced in detail. Finally, the application prospects of the deep learning method in multi-source computed tomography imaging scattering artifacts were probed .
