Evaluation of CT Imaging Characteristics and Effect of CTDI Phantom Size on Contrast Materials

Objectives: To describe the characteristics of computed tomography (CT) in patients with 2019 novel coronavirus (COVID-19) pneumonia and their changes during disease progression. Patients and Methods: A total of 96 chest CT scans of 61 pneumonia patients associated with COVID-19 were reviewed to identify CT features associated with the time of symptom onset and the evolution of disease. Results: The initial CTs of 61 patients were obtained during 1 to 11 days after the onset. The main CT pattern of initial CT obtained during 1 - 3 days after the symptom onset was single (7/23, 35%) or multiple ground-glass opacity (GGO, 8/23, 35%). At 4 - 7 days after the symptom onset, the main imaging features were crazy paving GGO mixed with partial consolidation pattern (15/32, 47%). At 8 - 11 days after the symptom onset, the CT images showed consolidation pattern (3/6, 50%). A total of 35 follow up CTs were collected. The mean interval time between each follow up CT was 3 ± 2 days. The CT patterns also changed with the evolution of the disease: the features of GGO manifested at the early stage (1 - 3d). The crazy paving GGO pattern, consolidation pattern and mixed with partial consolidation pattern were found 4 to 14 days after the onset. In the absorption stage (15 - 24d), both density and extent of lesions were reduced. Conclusion: The CT imaging features are associated with the time of symptom onset and evolution of disease. Understanding the imaging characteristics of each stage is very helpful for understanding the development of disease.

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MR and CT imaging characteristics and ablation zone volumetry of locally advanced pancreatic cancer treated with irreversible electroporation

European Radiology ◽

10.1007/s00330-016-4581-2 ◽

2016 ◽

Vol 27 (6) ◽

pp. 2521-2531 ◽

Cited By ~ 23

Author(s):

Laurien G. P. H. Vroomen ◽

Hester J. Scheffer ◽

Marleen C. A. M. Melenhorst ◽

Marcus C. de Jong ◽

Janneke E. van den Bergh ◽

...

Keyword(s):

Pancreatic Cancer ◽

Locally Advanced ◽

Irreversible Electroporation ◽

Advanced Pancreatic Cancer ◽

Ct Imaging ◽

Locally Advanced Pancreatic Cancer ◽

Ablation Zone ◽

Imaging Characteristics

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Biodistribution and Ct-Imaging Characteristics of Iopromide-Carrying Liposomes in Rats

Journal of Liposome Research ◽

10.3109/08982109609039920 ◽

1996 ◽

Vol 6 (4) ◽

pp. 665-680 ◽

Cited By ~ 8

Author(s):

Jens Leike ◽

Andreas Sachse ◽

Claudia Ehritt

Keyword(s):

Ct Imaging ◽

Imaging Characteristics

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Optimized Backprojection Filtration Algorithm for Postoperative Reduction and Analysis of Respiratory Infection-Related Factors of Pelvic Fractures by CT Imaging

Scientific Programming ◽

10.1155/2021/3554718 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Aihua Pu ◽

Hua Wang ◽

Jichong Ying

Keyword(s):

Pelvic Fracture ◽

Ct Images ◽

Ct Imaging ◽

Pelvic Fractures ◽

Conventional Group ◽

Ct Image ◽

Diagnosis Group ◽

Imaging Characteristics ◽

Conventional Ct ◽

Projection Filtering

To explore the computed tomography (CT) imaging characteristics and BPF algorithm fine lung CT image efficiency for the diagnosis of pelvic fracture patients and assist clinicians to carry out the disease care and treatment, CT images based on optimized back-projection filtering (BPF) algorithm were utilized to diagnose postoperative reduction of pelvic fractures and penetrating lung infection caused by long-term bed rest. A total of 100 patients with pelvic fracture were selected and all of them underwent pelvic fracture surgery and were rolled into conventional CT diagnosis group (conventional group) and BPF algorithm optimized CT image diagnosis group (BPF group). One group used conventional CT images to guide pelvic reduction and detect lung infections, and the other used BPF algorithm to optimize the images. The results showed that the BPF group was superior to the conventional CT group in both image clarity and shadow area, and the peak signal-to-noise ratio (PSNR) was significantly better than that of the conventional group ( P < 0.05 ). Nine more cases were detected in the algorithm group than in the conventional group, and the incidence of complications was 48% in the conventional group and 28% in the BPF group, with a statistical difference of 20% between the two groups ( P < 0.05 ). In addition, the satisfaction of returning patients was 96% in the BPF group and 77% in the conventional group ( P < 0.05 ). The diagnosis of pulmonary infection was more obvious in the BPF group, indicating that BPF optimization of the CT image was suitable for clinical diagnosis and had a practical application value.

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Correlation between Imaging Features and Pathological Stages of Primary Lung Tumors Based on Nanocontrast Agents

Computational and Mathematical Methods in Medicine ◽

10.1155/2021/2343299 ◽

2021 ◽

Vol 2021 ◽

pp. 1-5

Author(s):

Jin Li ◽

Qian Xu ◽

Cunhua Mao ◽

Yuliang Liu

Keyword(s):

Lung Cancer ◽

Contrast Agents ◽

Adverse Reactions ◽

Lung Tumors ◽

Ct Imaging ◽

Ct Scans ◽

Imaging Features ◽

Display Time ◽

Imaging Characteristics ◽

Primary Lung Tumors

As one of the conventional methods of lung cancer detection, computed tomography (CT) usually requires the use of contrast agents to enhance the imaging effect. Conventional iodine contrast agents have poor signal-to-noise ratio and are prone to adverse reactions. It is necessary to find more effective and safe contrast agents for CT scans. The gold nanoparticles with secondary electron effect and photoelectric absorption effect can prolong the display time of the patient’s blood circulation after being injected into the patient’s body, which makes the nanocontrast agent a research hotspot in the field of CT imaging. In this study, ultrasmall gold nanoclusters with a diameter of about 5 nm were used as the contrast agent in CT scans. It was found that CT scans based on nanocontrast agents can obtain high-quality lung cancer imaging images, and the patient has no obvious adverse reactions. When observing the CT image, it was found that the stage of lung cancer patients can be clearly distinguished through the CT scan image. When analyzing the consistency of CT imaging and pathological classification, the Kappa value was 0.810, indicating that the two have a high degree of consistency. Therefore, this study believes that the imaging characteristics of primary lung tumors based on nanocontrast agents are highly correlated with their pathological types.

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Use CT Imaging to Predict the Short-Term Outcome of Concurrent Chemoradiotherapy in Patients With Locally Advanced Esophageal Squamous Cell Carcinoma

Dose-Response ◽

10.1177/1559325819897175 ◽

2019 ◽

Vol 17 (4) ◽

pp. 155932581989717

Author(s):

Xiaolan Cao ◽

Xindi Li ◽

Xiaoyue Wang ◽

Jinghao Duan ◽

Shouhui Zhu ◽

...

Keyword(s):

Concurrent Chemoradiotherapy ◽

Locally Advanced ◽

Training Group ◽

Ct Imaging ◽

Imaging Features ◽

Validation Group ◽

Short Term ◽

Term Outcome ◽

Short Term Outcome ◽

Imaging Characteristics

Objective: To extract the computed tomography (CT) imaging features of the primary lesions in patients with advanced esophageal squamous cell carcinoma (ESCC) and to study whether these imaging features can predict the short-term outcome after concurrent chemoradiotherapy (CCRT). Methods: From January 2014 to December 2015, a total of 49 patients with locally advanced ESCC who underwent CCRT were analyzed retrospectively. They were randomly categorized into the training and validation groups. Collection of CT imaging of patients before and intermediate stage undergoing radiotherapy. The correlations between imaging characteristics and short-term outcome were analyzed. The accuracy of cutoff value was verified by imaging characteristics of patients in validation group. Result: There were 38 patients in the training group and 11 patients in the validation group. 13 patients in the training group were classified as responders and 25 patients as nonresponders. According to the CT imaging before radiotherapy, there are no significant differences between responders and nonresponders. According to the CT imaging in the middle stage of radiotherapy, responders showed significantly higher Roundness than nonresponders ( P = .004, 95% confidence interval [CI] = 0.0419-0.212). The areas under the ROC curves for the ability to predict significantly tumor response were 0.768 for Roundness ( P = .001, 95% CI = 0.603-0.889). The cutoff value of Roundness is 0.3099. Roundness showed no significant associations with survival parameters. Conclusions: Computed tomography imaging in the middle stage of radiotherapy can predict the short-term outcome of concurrent chemoradiotherapy for patients with locally advanced ESCC but have no predictive effect on the total survival time.

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