chest ct scan
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Author(s):  
Hooman Bahrami-Motlagh ◽  
Yashar Moharamzad ◽  
Golnaz Izadi Amoli ◽  
Sahar Abbasi ◽  
Alireza Abrishami ◽  
...  

Abstract Background Chest CT scan has an important role in the diagnosis and management of COVID-19 infection. A major concern in radiologic assessment of the patients is the radiation dose. Research has been done to evaluate low-dose chest CT in the diagnosis of pulmonary lesions with promising findings. We decided to determine diagnostic performance of ultra-low-dose chest CT in comparison to low-dose CT for viral pneumonia during the COVID-19 pandemic. Results 167 patients underwent both low-dose and ultra-low-dose chest CT scans. Two radiologists blinded to the diagnosis independently examined ultra-low-dose chest CT scans for findings consistent with COVID-19 pneumonia. In case of any disagreement, a third senior radiologist made the final diagnosis. Agreement between two CT protocols regarding ground-glass opacity, consolidation, reticulation, and nodular infiltration were recorded. On low-dose chest CT, 44 patients had findings consistent with COVID-19 infection. Ultra-low-dose chest CT had sensitivity and specificity values of 100% and 98.4%, respectively for diagnosis of viral pneumonia. Two patients were falsely categorized to have pneumonia on ultra-low-dose CT scan. Positive predictive value and negative predictive value of ultra-low-dose CT scan were respectively 95.7% and 100%. There was good agreement between low-dose and ultra-low-dose methods (kappa = 0.97; P < 0.001). Perfect agreement between low-dose and ultra-low-dose scans was found regarding diagnosis of ground-glass opacity (kappa = 0.83, P < 0.001), consolidation (kappa = 0.88, P < 0.001), reticulation (kappa = 0.82, P < 0.001), and nodular infiltration (kappa = 0.87, P < 0.001). Conclusion Ultra-low-dose chest CT scan is comparable to low-dose chest CT for detection of lung infiltration during the COVID-19 outbreak while maintaining less radiation dose. It can also be used instead of low-dose chest CT scan for patient triage in circumstances where rapid-abundant PCR tests are not available.


Biomedicines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1931
Author(s):  
Chiara Colarusso ◽  
Angelantonio Maglio ◽  
Michela Terlizzi ◽  
Carolina Vitale ◽  
Antonio Molino ◽  
...  

Purpose: SARS-CoV-2 infection induces in some patients a condition called long-COVID-19, herein post-COVID-19 (PC), which persists for longer than the negative oral-pharyngeal swab. One of the complications of PC is pulmonary fibrosis. The purpose of this study was to identify blood biomarkers to predict PC patients undergoing pulmonary fibrosis. Patients and Methods: We analyzed blood samples of healthy, anti-SARS-CoV-2 vaccinated (VAX) subjects and PC patients who were stratified according to the severity of the disease and chest computed tomography (CT) scan data. Results: The inflammatory C reactive protein (CRP), complement complex C5b-9, LDH, but not IL-6, were higher in PC patients, independent of the severity of the disease and lung fibrotic areas. Interestingly, PC patients with ground-glass opacities (as revealed by chest CT scan) were characterized by higher plasma levels of IL-1α, CXCL-10, TGF-β, but not of IFN-β, compared to healthy and VAX subjects. In particular, 19 out of 23 (82.6%) severe PC and 8 out of 29 (27.6%) moderate PC patients presented signs of lung fibrosis, associated to lower levels of IFN-β, but higher IL-1α and TGF-β. Conclusions: We found that higher IL-1α and TGF-β and lower plasma levels of IFN-β could predict an increased relative risk (RR = 2.8) of lung fibrosis-like changes in PC patients.


Author(s):  
Carmine Guarino ◽  
Cristiano Cesaro ◽  
Giuseppe La Cerra ◽  
Raffaella Lucci ◽  
Flavio Cesaro ◽  
...  

Pulmonary hamartomas represent the most frequent family of benign lung tumors that typically involve the lung parenchyma and only rarely grow as endobronchial tumors. The elective treatment of endobronchial hamartoma is the bronchoscopic resection, and in those cases in which tumor extension and localization makes it not possible, surgical treatment must be evaluated. Patients with symptomatic COVID-19, hospitalized, frequently undergo a chest CT scan and in some cases, occasional findings may emerge, requiring diagnostic investigations such as bronchoscopy and interventional pulmonology procedures. Therefore, in such a delicate pathological condition, such as COVID-19, the need to perform bronchoscopy and interventional pulmonology procedures, minimizing the risk of viral transmission and ensuring necessary assistance, represents a great challenge for pulmonologists. In this article authors describe, for the first time in literature, a rare case of endobronchial hamartoma, radically resected using a single use bronchoscope, in a young female patient hospitalized for symptomatic COVID-19.


2021 ◽  
Vol 24 (12) ◽  
pp. 916-918
Author(s):  
Barış Çil ◽  
Mehmet Kabak

Primary tracheal tumors are very rare and 10%–20% are benign tumors. Tracheal lipoma is extremely rare and only a few cases have been reported in the literature. A 69-year-old male patient presented to the emergency department with complaints of shortness of breath, respiratory distress, chest pain and cough. Chest CT scan showed a round mass in the topography of the trachea that almost caused airway obstruction. The lesion was resected endoscopically and the pedicle base was cauterized. Tracheal lipoma is a rare condition that should lie in the differential diagnosis of treatment-resistant asthma.


2021 ◽  
Vol 10 (23) ◽  
pp. 5500
Author(s):  
Max Scheffler ◽  
Laurence Genton ◽  
Christophe E. Graf ◽  
Jorge Remuinan ◽  
Gabriel Gold ◽  
...  

Background: We investigated the prognostic significance of visceral and subcutaneous adiposity in octogenarians with COVID-19. Methods: This paper presents a monocentric retrospective study that was conducted in acute geriatric wards with 64 hospitalized patients aged 80+ who had a diagnosis of COVID-19 and who underwent a chest CT scan. A quantification of the subcutaneous, visceral, and total fat areas was performed after segmentations on the first abdominal slice caudal to the deepest pleural recess on a soft-tissue window setting. Logistic regression models were applied to investigate the association with in-hospital mortality and the extent of COVID-19 pneumonia. Results: The patients had a mean age of 86.4 ± 6.0 years, and 46.9% were male, with a mean BMI of 24.1 ± 4.4Kg/m2 and mortality rate of 32.8%. A higher subcutaneous fat area had a protective effect against mortality (OR 0.416; 0.183–0.944 95% CI; p = 0.036), which remained significant after adjustments for age, sex, and BMI (OR 0.231; 0.071–0.751 95% CI; p = 0.015). Inversely, higher abdominal circumference, total fat area, subcutaneous fat area, and visceral fat were associated with worse COVID-19 pneumonia, with the latter presenting the strongest association after adjustments for age, sex, and BMI (OR 2.862; 1.523–5.379 95% CI; p = 0.001). Conclusion: Subcutaneous and visceral fat areas measured on chest CT scans were associated with prognosis in octogenarians with COVID-19.


2021 ◽  
Vol 16 (4) ◽  
Author(s):  
Mohammad Ali Kazemi ◽  
Nasrin Nikravangolsefid ◽  
Hamidreza Abtahi ◽  
Shahideh Amini ◽  
Hossein Ghanaati ◽  
...  

Introduction: Organ transplant recipients might be more likely to develop COVID-19, as they receive long-term immunosuppressives and have comorbidities. Case Presentation: Herein, we reported the case of a 32-year-old man with unilateral lung transplantation due to unclassifiable lung fibrosis on pathologic evaluation who presented with cough, fever, and headache. After evaluation with RT-PCR test and chest CT scan, COVID-19 in the previously transplanted lung was diagnosed. However, the other non-transplanted fibrotic lung was not involved. Conclusions: Lack of COVID-19 involvement in the fibrotic lung tissue in our case without any other risk factors might be related to the fact that the lung with underlying diseases was less susceptible to COVID-19 as unhealthy lungs have lower ACE2 receptors, or it might be related to genetic differences between the donor and recipient.


2021 ◽  
Vol 8 ◽  
Author(s):  
Hamid Reza Marateb ◽  
Farzad Ziaie Nezhad ◽  
Mohammad Reza Mohebian ◽  
Ramin Sami ◽  
Shaghayegh Haghjooy Javanmard ◽  
...  

Coronavirus disease-2019, also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was a disaster in 2020. Accurate and early diagnosis of coronavirus disease-2019 (COVID-19) is still essential for health policymaking. Reverse transcriptase-polymerase chain reaction (RT-PCR) has been performed as the operational gold standard for COVID-19 diagnosis. We aimed to design and implement a reliable COVID-19 diagnosis method to provide the risk of infection using demographics, symptoms and signs, blood markers, and family history of diseases to have excellent agreement with the results obtained by the RT-PCR and CT-scan. Our study primarily used sample data from a 1-year hospital-based prospective COVID-19 open-cohort, the Khorshid COVID Cohort (KCC) study. A sample of 634 patients with COVID-19 and 118 patients with pneumonia with similar characteristics whose RT-PCR and chest CT scan were negative (as the control group) (dataset 1) was used to design the system and for internal validation. Two other online datasets, namely, some symptoms (dataset 2) and blood tests (dataset 3), were also analyzed. A combination of one-hot encoding, stability feature selection, over-sampling, and an ensemble classifier was used. Ten-fold stratified cross-validation was performed. In addition to gender and symptom duration, signs and symptoms, blood biomarkers, and comorbidities were selected. Performance indices of the cross-validated confusion matrix for dataset 1 were as follows: sensitivity of 96% [confidence interval, CI, 95%: 94–98], specificity of 95% [90–99], positive predictive value (PPV) of 99% [98–100], negative predictive value (NPV) of 82% [76–89], diagnostic odds ratio (DOR) of 496 [198–1,245], area under the ROC (AUC) of 0.96 [0.94–0.97], Matthews Correlation Coefficient (MCC) of 0.87 [0.85–0.88], accuracy of 96% [94–98], and Cohen's Kappa of 0.86 [0.81–0.91]. The proposed algorithm showed excellent diagnosis accuracy and class-labeling agreement, and fair discriminant power. The AUC on the datasets 2 and 3 was 0.97 [0.96–0.98] and 0.92 [0.91–0.94], respectively. The most important feature was white blood cell count, shortness of breath, and C-reactive protein for datasets 1, 2, and 3, respectively. The proposed algorithm is, thus, a promising COVID-19 diagnosis method, which could be an amendment to simple blood tests and screening of symptoms. However, the RT-PCR and chest CT-scan, performed as the gold standard, are not 100% accurate.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Priyanka Yadlapalli ◽  
D. Bhavana ◽  
Suryanarayana Gunnam

PurposeComputed tomography (CT) scan can provide valuable information in the diagnosis of lung diseases. To detect the location of the cancerous lung nodules, this work uses novel deep learning methods. The majority of the early investigations used CT, magnetic resonance and mammography imaging. Using appropriate procedures, the professional doctor in this sector analyses these images to discover and diagnose the various degrees of lung cancer. All of the methods used to discover and detect cancer illnesses are time-consuming, expensive and stressful for the patients. To address all of these issues, appropriate deep learning approaches for analyzing these medical images, which included CT scan images, were utilized.Design/methodology/approachRadiologists currently employ chest CT scans to detect lung cancer at an early stage. In certain situations, radiologists' perception plays a critical role in identifying lung melanoma which is incorrectly detected. Deep learning is a new, capable and influential approach for predicting medical images. In this paper, the authors employed deep transfer learning algorithms for intelligent classification of lung nodules. Convolutional neural networks (VGG16, VGG19, MobileNet and DenseNet169) are used to constrain the input and output layers of a chest CT scan image dataset.FindingsThe collection includes normal chest CT scan pictures as well as images from two kinds of lung cancer, squamous and adenocarcinoma impacted chest CT scan images. According to the confusion matrix results, the VGG16 transfer learning technique has the highest accuracy in lung cancer classification with 91.28% accuracy, followed by VGG19 with 89.39%, MobileNet with 85.60% and DenseNet169 with 83.71% accuracy, which is analyzed using Google Collaborator.Originality/valueThe proposed approach using VGG16 maximizes the classification accuracy when compared to VGG19, MobileNet and DenseNet169. The results are validated by computing the confusion matrix for each network type.


Bionatura ◽  
2021 ◽  
Vol 6 (4) ◽  
pp. 2265-2269
Author(s):  
Hazim Ghazzay ◽  
Hamdi Saleh Al-Mutoriy ◽  
Mazin Saleh Al- Rudaini ◽  
Hamed Al Reesi

The SARS-CoV2 infection emerged in Iraq in February 2020. In this study, we describe the clinical characteristics and outcomes of the initial SARS-CoV2 patients. A total of 529 patients were included in this study from April to August 2020 in Anbar province. Patients were confirmed to be infected in nasal swabs by real-time RT-PCR or chest CT scan findings. The gathered data included the demographic variables (age, sex, residency), presence of comorbidity (hypertension, diabetes mellitus, respiratory illness, coronary heart disease, chronic kidney disease, obesity), and history of contact with a known case of SARS-CoV2. The results showed that 64% of the patients were males and 36% were female, 48% of the patients lied in the age category 40-59 years, 74% had exposure history, 95% did not have a history of smoking, 46% were overweight, 60% had no comorbidity, 78% presented with mild/moderate disease, 70% had typical chest CT scan finding (CO-RAD 5), and 76% of patients showed positive PCR. The fatality rate is 16%. Most of the patients had a history of exposure to a confirmed case of SARS-CoV2 before the illness. The severity and outcome were correlated with risk factors and comorbidity. Combining chest computed tomography images with the qPCR analysis of nasal swab samples can improve the accuracy of SARS-CoV2 diagnosis.


Author(s):  
Herveat RAMANANDAFY ◽  
Princy Parfait Andriamahenina ◽  
Harison Michel Tiaray ◽  
Anjara Mihaja Nandimbiniaina ◽  
Angela Zamelina Razafindrasoa ◽  
...  

Rendu Osler’s disease is a genetic disease characterized by mucocutaneous and visceral telangiectasias. Rendu Osler’s disease was discovered during hypoxemia during an outbreak of SARS-Cov2.This was a 36-year-old woman with exertional dyspnea and severe hypoxemia revealing pulmonary arteriovenous malformations on chest CT scan.


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