scholarly journals Chest CT : Imaging and Reading of the Lung CT in the Radiological(Interpreting Medical Images for Radiological Technologists)

2005 ◽  
Vol 61 (8) ◽  
pp. 1059-1072
Author(s):  
ISAO YAMAGUCHI
Keyword(s):  
Medical Images ◽  
Ct Imaging ◽  
Chest Ct ◽  
Lung Ct

scholarly journals Computed Tomography Features of COVID-19 in Children: A Systematic Review and Meta-analysis

2020 ◽  
Author(s):  
Ji-Gan Wang ◽  
Yu-Fang Mo ◽  
Yu-heng Su ◽  
Li-chuang Wang ◽  
Guang-bing Liu ◽  
...  
Keyword(s):  
Pleural Effusion ◽  
Assessment Tool ◽  
Meta Analysis ◽  
Ct Imaging ◽  
Chest Ct ◽  
Ground Glass ◽  
Imaging Features ◽  
Lung Lesions ◽  
Lung Lobe ◽  
Lung Ct

Objectives: To systematically analyze the chest CT imaging features of children with COVID-19 and provide references for clinical practice. Methods: We searched PubMed, Web of Science, and Embase; data published by Johns Hopkins University; and Chinese databases CNKI, Wanfang, and Chongqing Weipu. Reports on chest CT imaging features of children with COVID-19 from January 1, 2020, to August 10, 2020, were analyzed retrospectively and a meta-analysis carried out using Stata12.0 software. Results: Thirty-seven articles (1747 children) were included in this study. The overall rate of abnormal lung CT findings was 63.2% (95% confidence interval [CI]: 55.8-70.6%), with a rate of 61.0% (95% CI: 50.8-71.2%) in China and 67.8% (95% CI: 57.1-78.4%) in the rest of the world in the subgroup analysis. The incidence of ground-glass opacities was 39.5% (95% CI: 30.7-48.3%), multiple lung lobe lesions 65.1% (95% CI: 55.1-67.9%), and bilateral lung lesions 61.5% (95% CI: 58.8-72.2%). Other imaging features included nodules (25.7%), patchy shadows (36.8%), halo sign (24.8%), consolidation (24.1%), air bronchogram signs (11.2%), cord-like shadows (9.7%), crazy-paving pattern (6.1%), and pleural effusion (9.1%). Two articles reported three cases of white lung, another reported two cases of pneumothorax, and another one case of bullae. CONCLUSION: The lung CT results of children with COVID-19 are usually normal or slightly atypica, with a low sensitivity and specificity compared with that in adults. The lung lesions of COVID-19 pediatric patients mostly involve both lungs or multiple lobes, and the common manifestations are patchy shadows, ground-glass opacities, consolidation, partial air bronchogram signs, nodules, and halo signs; white lung, pleural effusion, and paving stone signs are rare. CLINICAL IMPACT: Therefore, chest CT has limited value as a screening tool for children with COVID-19 and can only be used as an auxiliary assessment tool.

scholarly journals The role of CT imaging for management of COVID-19 in epidemic area: early experience from a University Hospital

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Vikram rao Bollineni ◽  
Koenraad Hans Nieboer ◽  
Seema Döring ◽  
Nico Buls ◽  
Johan de Mey
Keyword(s):  
Ct Scan ◽  
Predictive Value ◽  
Ct Imaging ◽  
Chest Ct ◽  
University Hospital ◽  
Rt Pcr ◽  
Ct Findings ◽  
Epidemic Area ◽  
Chest Ct Scan ◽  
Pcr Test

Abstract Background To evaluate the clinical value of the chest CT scan compared to the reference standard real-time polymerase chain reaction (RT-PCR) in COVID-19 patients. Methods From March 29th to April 15th of 2020, a total of 240 patients with respiratory distress underwent both a low-dose chest CT scan and RT-PCR tests. The performance of chest CT in diagnosing COVID-19 was assessed with reference to the RT-PCR result. Two board-certified radiologists (mean 24 years of experience chest CT), blinded for the RT-PCR result, reviewed all scans and decided positive or negative chest CT findings by consensus. Results Out of 240 patients, 60% (144/240) had positive RT-PCR results and 89% (213/240) had a positive chest CT scans. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of chest CT in suggesting COVID-19 were 100% (95% CI: 97–100%, 144/240), 28% (95% CI: 19–38%, 27/240), 68% (95% CI: 65–70%) and 100%, respectively. The diagnostic accuracy of the chest CT suggesting COVID-19 was 71% (95% CI: 65–77%). Thirty-three patients with positive chest CT scan and negative RT-PCR test at baseline underwent repeat RT-PCR assay. In this subgroup, 21.2% (7/33) cases became RT-PCR positive. Conclusion Chest CT imaging has high sensitivity and high NPV for diagnosing COVID-19 and can be considered as an alternative primary screening tool for COVID-19 in epidemic areas. In addition, a negative RT-PCR test, but positive CT findings can still be suggestive of COVID-19 infection.

scholarly journals CORONARY CALCIFICATION IS COMMON AND MAY BE UNDER-REPORTED ON NON-GATED CHEST CT IMAGING

2015 ◽  
Vol 65 (10) ◽  
pp. A1473
Author(s):  
Revathi Balakrishnan ◽  
Brian Nguyen ◽  
Roy Raad ◽  
Robert Donnino ◽  
David Naidich ◽  
...  
Keyword(s):  
Coronary Calcification ◽  
Ct Imaging ◽  
Chest Ct

scholarly journals Motion correction for routine X-ray lung CT imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Doil Kim ◽  
Jiyoung Choi ◽  
Duhgoon Lee ◽  
Hyesun Kim ◽  
Jiyoung Jung ◽  
...  
Keyword(s):  
Motion Estimation ◽  
Motion Correction ◽  
Ct Imaging ◽  
Motion Artifacts ◽  
Ct Scans ◽  
Breath Hold ◽  
X Ray ◽  
Wide Range ◽  
Thorax Ct ◽  
Lung Ct

AbstractA novel motion correction algorithm for X-ray lung CT imaging has been developed recently. It was designed to perform for routine chest or thorax CT scans without gating, namely axial or helical scans with pitch around 1.0. The algorithm makes use of two conjugate partial angle reconstruction images for motion estimation via non-rigid registration which is followed by a motion compensated reconstruction. Differently from other conventional approaches, no segmentation is adopted in motion estimation. This makes motion estimation of various fine lung structures possible. The aim of this study is to explore the performance of the proposed method in correcting the lung motion artifacts which arise even under routine CT scans with breath-hold. The artifacts are known to mimic various lung diseases, so it is of great interest to address the problem. For that purpose, a moving phantom experiment and clinical study (seven cases) were conducted. We selected the entropy and positivity as figure of merits to compare the reconstructed images before and after the motion correction. Results of both phantom and clinical studies showed a statistically significant improvement by the proposed method, namely up to 53.6% (p < 0.05) and up to 35.5% (p < 0.05) improvement by means of the positivity measure, respectively. Images of the proposed method show significantly reduced motion artifacts of various lung structures such as lung parenchyma, pulmonary vessels, and airways which are prominent in FBP images. Results of two exemplary cases also showed great potential of the proposed method in correcting motion artifacts of the aorta which is known to mimic aortic dissection. Compared to other approaches, the proposed method provides an excellent performance and a fully automatic workflow. In addition, it has a great potential to handle motions in wide range of organs such as lung structures and the aorta. We expect that this would pave a way toward innovations in chest and thorax CT imaging.

scholarly journals Predictors of COVID-19 Infection: A Prevalence Study of Hospitalized Patients

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Huilan Tu ◽  
Hong Zhao ◽  
Junwei Su ◽  
Wenrui Wu ◽  
Kaijin Xu ◽  
...  
Keyword(s):  
Ct Imaging ◽  
Chest Ct ◽  
Hospitalized Patients ◽  
Prevalence Study ◽  
Nucleic Acid Detection ◽  
Bilateral Involvement ◽  
Resource Limited ◽  
Laboratory Test Results ◽  
Independent Risk Factors ◽  
Exposure History

Aim. To find the predictors of coronavirus disease 2019 (COVID-19) in hospitalized patients. Methods. A prevalence study compared the characteristics of COVID-19 patients with non-COVID-19 patients from January 19, 2020, to February 18, 2020, during the COVID-19 outbreak. Laboratory test results and pulmonary chest imaging of confirmed COVID-19 and non-COVID-19 patients were collected by retrieving medical records in our center. Results. 96 COVID-19 patients and 122 non-COVID-19 patients were enrolled in this study. COVID-19 patients were older (53 vs. 39; P  < 0.001) and had higher body mass index (BMI) than non-COVID-19 group (24.21 ± 3.51 vs. 23.00 ± 3.27, P  = 0.011); however, differences in gender were not observed between the two groups. Logistic regression analysis showed that exposure history (OR: 23.34, P  < 0.001), rhinorrhea (odds radio (OR): 0.12, P  = 0.006), alanine aminotransferase (ALT) (OR: 1.03, P  = 0.049), lactate dehydrogenase (LDH) (OR: 1.01, P  = 0.020), lymphocyte (OR: 0.27, P  = 0.007), and bilateral involvement on chest CT imaging (OR: 23.01, P  < 0.001) were independent risk factors for COVID-19. Moreover, bilateral involvement on chest CT imaging (AUC = 0.904, P  < 0.001) had significantly higher AUC than others in predicting COVID-19. Conclusions. Exposure history, elevated ALT and LDH, absence of rhinorrhea, lymphopenia, and bilateral involvement on chest CT imaging provide robust evidence for the diagnosis of COVID-19, especially in resource-limited conditions where nucleic acid detection is not readily available.

scholarly journals COVIDNet-CT: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases From Chest CT Images

2020 ◽  
Vol 7 ◽  
Author(s):  
Hayden Gunraj ◽  
Linda Wang ◽  
Alexander Wong
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Network Architecture ◽  
Ct Images ◽  
Ct Imaging ◽  
Chest Ct ◽  
Deep Convolutional Neural Network ◽  
Screening Tools ◽  
Screening Methods ◽  
Rt Pcr

The coronavirus disease 2019 (COVID-19) pandemic continues to have a tremendous impact on patients and healthcare systems around the world. In the fight against this novel disease, there is a pressing need for rapid and effective screening tools to identify patients infected with COVID-19, and to this end CT imaging has been proposed as one of the key screening methods which may be used as a complement to RT-PCR testing, particularly in situations where patients undergo routine CT scans for non-COVID-19 related reasons, patients have worsening respiratory status or developing complications that require expedited care, or patients are suspected to be COVID-19-positive but have negative RT-PCR test results. Early studies on CT-based screening have reported abnormalities in chest CT images which are characteristic of COVID-19 infection, but these abnormalities may be difficult to distinguish from abnormalities caused by other lung conditions. Motivated by this, in this study we introduce COVIDNet-CT, a deep convolutional neural network architecture that is tailored for detection of COVID-19 cases from chest CT images via a machine-driven design exploration approach. Additionally, we introduce COVIDx-CT, a benchmark CT image dataset derived from CT imaging data collected by the China National Center for Bioinformation comprising 104,009 images across 1,489 patient cases. Furthermore, in the interest of reliability and transparency, we leverage an explainability-driven performance validation strategy to investigate the decision-making behavior of COVIDNet-CT, and in doing so ensure that COVIDNet-CT makes predictions based on relevant indicators in CT images. Both COVIDNet-CT and the COVIDx-CT dataset are available to the general public in an open-source and open access manner as part of the COVID-Net initiative. While COVIDNet-CT is not yet a production-ready screening solution, we hope that releasing the model and dataset will encourage researchers, clinicians, and citizen data scientists alike to leverage and build upon them.

scholarly journals Airway Count and Emphysema Assessed by Chest CT Imaging Predicts Clinical Outcome in Smokers

CHEST Journal ◽  
2010 ◽  
Vol 138 (4) ◽  
pp. 880-887 ◽  
Author(s):  
Alejandro A. Diaz ◽  
Clarissa Valim ◽  
Tsuneo Yamashiro ◽  
Raúl San José Estépar ◽  
James C. Ross ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Ct Imaging ◽  
Chest Ct

scholarly journals Evaluation of Radiation Dose and Image Quality using High-Pitch 70-kV Chest CT in Immunosuppressed Patients

2018 ◽  
Vol 191 (02) ◽  
pp. 122-129 ◽  
Author(s):  
Ibrahim Yel ◽  
Simon Martin ◽  
Julian Wichmann ◽  
Lukas Lenga ◽  
Moritz Albrecht ◽  
...  
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Image Data ◽  
Ct Imaging ◽  
Chest Ct ◽  
Control Group ◽  
High Pitch ◽  
Dose Length Product ◽  
Subjective Image Quality ◽  
Immunosuppressed Patients

Purpose The aim of the study was to evaluate high-pitch 70-kV CT examinations of the thorax in immunosuppressed patients regarding radiation dose and image quality in comparison with 120-kV acquisition. Materials and Methods The image data from 40 patients (14 women and 26 men; mean age: 40.9 ± 15.4 years) who received high-pitch 70-kV CT chest examinations were retrospectively included in this study. A control group (n = 40), matched by age, gender, BMI, and clinical inclusion criteria, had undergone standard 120-kV chest CT imaging. All CT scans were performed on a third-generation dual-source CT unit. For an evaluation of the radiation dose, the CT dose index (CTDIvol), dose-length product (DLP), effective dose (ED), and size-specific dose estimates (SSDE) were analyzed in each group. The objective image quality was evaluated using signal-to-noise (SNR) and contrast-to-noise ratios (CNR). Three blinded and independent radiologists evaluated subjective image quality and diagnostic confidence using 5-point Likert scales. Results The mean dose parameters were significantly lower for high-pitch 70-kV CT examinations (CTDIvol, 2.9 ± 0.9 mGy; DLP, 99.9 ± 31.0 mGyxcm; ED, 1.5 ± 0.6 mSv; SSDE, 3.8 ± 1.2 mGy) compared to standard 120-kV CT imaging (CTDIvol, 8.8 ± 3.7mGy; DLP, 296.6 ± 119.3 mGyxcm; ED, 4.4 ± 2.1 mSv; SSDE, 11.6 ± 4.4 mGy) (P≤ 0.001). The objective image parameters (SNR: 7.8 ± 2.1 vs. 8.4 ± 1.8; CNR: 7.7 ± 2.4 vs. 8.3 ± 2.8) (P≥ 0.065) and the cumulative subjective image quality (4.5 ± 0.4 vs. 4.7 ± 0.3) (p = 0.052) showed no significant differences between the two protocols. Conclusion High-pitch 70-kV thoracic CT examinations in immunosuppressed patients resulted in a significantly reduced radiation exposure compared to standard 120-kV CT acquisition without a decrease in image quality. Key Points:  Citation Format

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