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 Chest CT imaging features and clinical outcome of coronavirus disease 2019 (COVID-19): A single-center case study in Ningbo, China

2021 ◽  
Vol 69 ◽  
pp. 27-32
Author(s):  
Maoqing Jiang ◽  
Ping Chen ◽  
Tianfu Li ◽  
Yifan Tang ◽  
Xueqin Chen ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Ct Imaging ◽  
Chest Ct ◽  
Imaging Features ◽  
Single Center

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 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 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

scholarly journals Does the presence of emphysema increase the risk of radiation pneumonitis in lung cancer patients?

2018 ◽  
Vol 25 (6) ◽  
Author(s):  
G. Kasymjanova ◽  
R. T. Jagoe ◽  
C. Pepe ◽  
L. Sakr ◽  
V. Cohen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Radiation Pneumonitis ◽  
Severe Disease ◽  
Ct Imaging ◽  
Chest Ct ◽  
Curative Intent ◽  
Treatment Protocols ◽  
Lung Cancer Patients ◽  
Increased Risk ◽  
High Doses

Introduction Radiotherapy (rt) plays an important role in the treatment of lung cancer. One of the most common comorbidities in patients with lung cancer is pulmonary emphysema. The literature offers conflicting data about whether emphysema increases the occurrence and severity of radiation pneumonitis (rp). As a result, whether high doses of rt (with curative intent) should be avoided in patients with emphysema is still unclear.Objective We measured the documented incidence of rp in patients with and without emphysema who received curative radiation treatment.Methods This retrospective cohort study considered patients in the lung cancer clinical database of the Peter Brojde Lung Cancer Centre. Data from the database has been used previously for research studies, including a recent publication about emphysema grading, based on the percentage of lung occupied by emphysema on computed tomography (ct) imaging.Results Using previously published methods, chest ct imaging for 498 patients with lung cancer was scored for the presence of emphysema. The analysis considered 114 patients who received at least 30 Gy radiation. Of those 114 patients, 64 (56%) had emphysema, with approximately 23% having severe or very severe disease. The incidence of rp was 34.4% in patients with emphysema (n = 22) and 32.0% in patients with no emphysema (n = 16, p = 0.48). No difference in the incidence of rp was evident between patients with various grades of emphysema (p = 0.96). Similarly, no difference in the incidence of rp was evident between the two treatment protocols—that is, definitive rt 17 (37%) and combined chemotherapy–rt 21 (31%, p = 0.5).Conclusions In our cohort, the presence of emphysema on chest ct imaging was not associated with an increased risk of rp. That finding suggests that patients with lung cancer and emphysema should be offered rt when clinically indicated. However, further prospective studies will be needed for confirmation.

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