scholarly journals MosMedData: Chest CT Scans with COVID-19 Related Findings

2020 ◽  
Author(s):  
Sergey Morozov ◽  
Anna Andreychenko ◽  
Nikolay Pavlov ◽  
Anton Vladzymyrskyy ◽  
Natalya Ledikhova ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Human Lung ◽  
Chest Ct ◽  
Ct Scans ◽  
Ground Glass ◽  
Small Subset ◽  
Creative Commons

This dataset contains anonymised human lung computed tomography (CT) scans with COVID-19 related findings, as well as without such findings. A small subset of studies has been annotated with binary pixel masks depicting regions of interests (ground-glass opacifications and consolidations). CT scans were obtained between 1st of March, 2020 and 25th of April, 2020, and provided by municipal hospitals in Moscow, Russia. Permanent link: https://mosmed.ai/datasets/covid19_1110. This dataset is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) License.

scholarly journals The diagnostic value of chest X-ray in coronavirus disease 2019: A comparative study of X-ray and CT

2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110162
Author(s):  
Fengxia Zeng ◽  
Yong Cai ◽  
Yi Guo ◽  
Weiguo Chen ◽  
Min Lin ◽  
...  
Keyword(s):  
Clinical Symptoms ◽  
Diagnostic Value ◽  
Rapid Identification ◽  
Chest Ct ◽  
Ct Scans ◽  
Ground Glass ◽  
X Ray ◽  
Chest X Ray ◽  
Laboratory Examinations ◽  
Sensitivity Specificity

As the coronavirus disease 2019 (COVID-19) epidemic spreads around the world, the demand for imaging examinations increases accordingly. The value of conventional chest radiography (CCR) remains unclear. In this study, we aimed to investigate the diagnostic value of CCR in the detection of COVID-19 through a comparative analysis of CCR and CT. This study included 49 patients with 52 CT images and chest radiographs of pathogen-confirmed COVID-19 cases and COVID-19-suspected cases that were found to be negative (non-COVID-19). The performance of CCR in detecting COVID-19 was compared to CT imaging. The major signatures that allowed for differentiation between COVID-19 and non-COVID-19 cases were also evaluated. Approximately 75% (39/52) of images had positive findings on the chest x-ray examinations, while 80.7% (42/52) had positive chest CT scans. The COVID-19 group accounted for 88.4% (23/26) of positive chest X-ray examinations and 96.1% (25/26) of positive chest CT scans. The sensitivity, specificity, and accuracy of CCR for abnormal shadows were 88%, 80%, and 87%, respectively, for all patients. For the COVID-19 group, the accuracy of CCR was 92%. The primary signature on CCR was flocculent shadows in both groups. The shadows were primarily in the bi-pulmonary, which was significantly different from non-COVID-19 patients ( p = 0.008). The major CT finding of COVID-19 patients was ground-glass opacities in both lungs, while in non-COVID-19 patients, consolidations combined with ground-glass opacities were more common in one lung than both lungs ( p = 0.0001). CCR showed excellent performance in detecting abnormal shadows in patients with confirmed COVID-19. However, it has limited value in differentiating COVID-19 patients from non-COVID-19 patients. Through the typical epidemiological history, laboratory examinations, and clinical symptoms, combined with the distributive characteristics of shadows, CCR may be useful to identify patients with possible COVID-19. This will allow for the rapid identification and quarantine of patients.

Advanced Chest Imaging Interpretation of Acute Pulmonary Disorders

2014 ◽  
Vol 25 (4) ◽  
pp. 365-374
Author(s):  
Debra Siela
Keyword(s):  
Computed Tomography ◽  
Advanced Practice Nurses ◽  
Chest Ct ◽  
Chest Radiographs ◽  
Ct Scans ◽  
Advanced Practice ◽  
Clinical Judgments ◽  
Chest Imaging ◽  
Practice Nurses ◽  
Lateral Chest

Bedside and advanced practice nurses in acute and critical care often view chest radiologic images of their patients. Correlation of findings on chest radiologic images with results of physical and other diagnostic assessments can provide information for making appropriate clinical judgments. Radiologic images of the chest available for acutely ill patients now include frontal/lateral chest radiographs and computed tomography (CT) scans. The purpose of this article is for the reader to review basic skills for interpreting chest radiographs, gain skill in reviewing CT scans of the chest, and be able to apply more advanced interpretation skills for both chest radiographs and chest CT scans. Several chest images are included for review.

scholarly journals Tracheal Tube Obstruction in Mechanically Ventilated Patients Assessed by High-resolution Computed Tomography

2014 ◽  
Vol 121 (6) ◽  
pp. 1226-1235 ◽  
Author(s):  
Cristina Mietto ◽  
Riccardo Pinciroli ◽  
Annop Piriyapatsom ◽  
John G. Thomas ◽  
Lynn Bry ◽  
...  
Keyword(s):  
Computed Tomography ◽  
High Resolution ◽  
Tracheal Tube ◽  
Chest Ct ◽  
Ct Scans ◽  
Common Finding ◽  
High Resolution Computed Tomography ◽  
Airflow Resistance ◽  
High Resolution Ct ◽  
Ventilated Patients

Abstract Background: Tracheal intubation compromises mucus clearance and secretions accumulate inside the tracheal tube (TT). The aim of this study was to evaluate with a novel methodology TT luminal obstruction in critically ill patients. Methods: This was a three-phase study: (1) the authors collected 20 TTs at extubation. High-resolution computed tomography (CT) was performed to determine cross-sectional area (CSA) and mucus distribution within the TT; (2) five TTs partially filled with silicone were used to correlate high-resolution CT results and increased airflow resistance; and (3) 20 chest CT scans of intubated patients were reviewed for detection of secretions in ventilated patients’ TT. Results: Postextubation TTs showed a maximum CSA reduction of (mean ± SD) 24.9 ± 3.9% (range 3.3 to 71.2%) after a median intubation of 4.5 (interquartile range 2.5 to 6.5) days. CSA progressively decreased from oral to lung end of used TTs. The luminal volume of air was different between used and new TTs for all internal diameters (P < 0.01 for new vs. used TTs for all studied internal diameters). The relationship between pressure drop and increasing airflow rates was nonlinear and depended on minimum CSA available to ventilation. Weak correlation was found between TT occlusion and days of intubation (R2 = 0.352, P = 0.006). With standard clinical chest CT scans, 6 of 20 TTs showed measurable secretions with a CSA reduction of 24.0 ± 3.9%. Conclusions: TT luminal narrowing is a common finding and correlates with increased airflow resistance. The authors propose high-resolution CT as a novel technique to visualize and quantify secretions collected within the TT lumen.

Chest Computed Tomography Findings in a Case Series of Coronavirus Disease 2019 (COVID-19) Patients at Siriraj Hospital

2021 ◽  
Vol 104 (5) ◽  
pp. 866-871
Keyword(s):  
Computed Tomography ◽  
Medical Records ◽  
Case Series ◽  
Ground Glass Opacity ◽  
Chest Ct ◽  
Ground Glass ◽  
Chest Computed Tomography ◽  
Ct Findings ◽  
Siriraj Hospital ◽  
Chest Ct Scan

Background: Recent evidence has demonstrated the high sensitivity of chest computed tomography (CT) in coronavirus disease 2019 (COVID-19) case detection. However, considering the cost and infection control issues, the experience of chest CT for COVID-19 diagnosis in Thailand is still limited. Objective: To present the characteristics of chest CT findings in COVID-19 patients at Siriraj Hospital and compare them with other reports. Materials and Methods: The authors retrospectively reviewed the COVID-19 patients’ medical records between April and May 2020. All cases with the presence of chest CT performed during admission were recruited. Clinical data were retrieved from the patients’ medical records. All chest imaging results were reported by consensus between the authors. Results: From 103 cases, four cases with a chest CT scan during the admission were recruited. Consistent with previous reports, the common chest CT findings included a ground-glass opacity and consolidation with bilateral involvement. A round-shaped ground-glass opacity or consolidation was evidenced in half of the cases. The only case with the presence of chest CT scan, which was done 77 days after the onset of COVID-19 symptoms, revealed resolution of the abnormal findings. Conclusion: Chest CT findings in four COVID-19 cases at Siriraj Hospital are consistent with previous reports. Common findings include bilateral ground-glass opacity and consolidation. Keywords: COVID-19, SARS-CoV-2, Computed tomography, Case series

scholarly journals Unusual Radiographic Presentation of Pneumocystis Pneumonia in a Patient with AIDS

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Brian L. Block ◽  
Tejas Mehta ◽  
Gabriel M. Ortiz ◽  
Sean P. Ferris ◽  
Thienkhai H. Vu ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Management Strategies ◽  
Pneumocystis Pneumonia ◽  
Chest Ct ◽  
Ground Glass ◽  
Combination Antiretroviral Therapy ◽  
Alveolar Process ◽  
Routine Prophylaxis ◽  
High Negative Predictive Value ◽  
Radiographic Presentation

Pneumocystis jirovecii pneumonia (PCP) typically presents as an interstitial and alveolar process with ground glass opacities on chest computed tomography (CT). The absence of ground glass opacities on chest CT is thought to have a high negative predictive value for PCP in individuals with AIDS. Here, we report a case of PCP in a man with AIDS who presented to our hospital with subacute shortness of breath and a nonproductive cough. While his chest CT revealed diffuse nodular rather than ground glass opacities, bronchoscopy with bronchoalveolar lavage and transbronchial biopsies confirmed the diagnosis of PCP and did not identify additional pathogens. PCP was not the expected diagnosis based on chest CT, but it otherwise fit well with the patient’s clinical and laboratory presentation. In the era of combination antiretroviral therapy, routine prophylaxis for PCP, and increased use of computed tomography, it may be that PCP will increasingly present with nonclassical chest radiographic patterns. Clinicians should be aware of this presentation when selecting diagnostic and management strategies.

scholarly journals The incidence and outcome of incidental breast lesions detected by computed tomography

2010 ◽  
Vol 92 (2) ◽  
pp. 124-126 ◽  
Author(s):  
A Hussain ◽  
A Gordon-Dixon ◽  
H Almusawy ◽  
P Sinha ◽  
A Desai
Keyword(s):  
Breast Cancer ◽  
Computed Tomography ◽  
Breast Lesion ◽  
Chest Ct ◽  
Ct Scans ◽  
Breast Lesions ◽  
Breast Cancers ◽  
The Mean ◽  
The Uk ◽  
Symptomatic Breast

INTRODUCTION In the UK, the majority of breast cancers are diagnosed through symptomatic breast clinics and the breast screening programmes. With increased use of computed tomography (CT) to assess various pathologies, breast lesions are picked up incidentally. The aim of this study was to investigate the incidence and outcomes of breast lesions detected incidentally on CT scans. PATIENTS AND METHODS A retrospective study was conducted to assess the incidence and outcome of incidentally found breast lesions, which were detected on chest CT scans that were conducted for other pathologies during the period from February 2007 to October 2008. RESULTS A total of 432 chest CT scans were performed over 18 months. Thirty-three (7.63%) patients were found to have an incidental breast lesion. The mean age was 73 years (range, 50–86 years). Of these, 17 (52%) were benign, eight (24%) were primary breast cancer and the remaining eight (24%) had no definite pathology. The detection rate of breast cancer was 1.85%. CONCLUSIONS CT is emerging as an important contributor to the detection of occult breast lesions. Radiological awareness of incidental breast lesions is important so that appropriate referral to a specialised breast unit is made.

scholarly journals The Spectrum of Chest CT-Scans in the Hospitalized Patients with the Coronavirus Disease

2020 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Maria Shirvani ◽  
Alireza Janbakhsh ◽  
Feizollah Mansouri ◽  
Babak Sayad ◽  
Siavash Vaziri ◽  
...  
Keyword(s):  
Ct Scan ◽  
Clinical Symptoms ◽  
Large Family ◽  
Chest Ct ◽  
Hospitalized Patients ◽  
Ct Scans ◽  
Ground Glass ◽  
Sample Population ◽  
Ground Glass Opacification ◽  
Chest Ct Scan

Background: Coronaviruses are a large family of RNA viruses, which range from the common cold virus to the causative agent of more severe diseases. Coronavirus was declared a pandemic in December 2019 in Wuhan, China. Iran has been an endemic zone for the spread of the coronavirus since the outset of this global epidemic and has remained among the countries largely affected by high rates of the disease. Objectives: The present study aimed to investigate the range of the chest computed tomography (CT) scan findings among the hospitalized patients with COVID-19 in Kermanshah, Iran during March-April 2020 to contribute to the accurate diagnosis of the infected patients. Methods: The sample population consisted of 286 hospitalized patients diagnosed with or suspected of the coronavirus disease. Chest CT-scan images and clinical data were reviewed, and their correlation was analyzed. Results: In total, 176 patients (61.53%) were male, and 110 (38.47%) were female. The mean age of the patients was 56 years. Polymerase chain reaction (PCR) results showed that 35.31% of the cases had coronavirus, while the results were negative in 64.69% of the cases. In addition, the CT-scan findings indicated 77.27% abnormal and 22.73% normal chest CT-scans. Among the patients, 75.87% recovered completely, and 18.53% died. The major CT abnormalities were diffuse ground-glass opacification (35.66%), peripheral ground-glass opacification (bilateral; 21.33%), and a combination of diffuse and peripheral ground-glass lesions (18.88%). The consolidation lesion of one lobe was detected in 16 patients, and the consolidation lesion of more than one lobe was observed in 40 patients. Conclusions: According to the results, the most common chest CT-scan findings in COVID-19 include diffuse ground-glass opacification, peripheral ground-glass opacification (bilateral), central ground-glass opacification (bilateral), a combination of diffuse and peripheral ground-glass opacification, a combination of central and peripheral ground-glass opacification, the consolidation lesion of one lobe, and the consolidation lesion of more than one lobe. Furthermore, significant correlations were observed between the CT-scans and the main clinical symptoms, while no significant correlations were denoted between the chest CT-scan and PCR results.

scholarly journals A novel deep learning-based quantification of serial chest computed tomography in Coronavirus Disease 2019 (COVID-19)

2020 ◽  
Author(s):  
Feng Pan ◽  
Lin Li ◽  
Bo Liu ◽  
Tianhe Ye ◽  
Lingli Li ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Deep Learning ◽  
Quantitative Computed Tomography ◽  
Pulmonary Involvement ◽  
Chest Ct ◽  
Estimation Methods ◽  
Ct Scans ◽  
Severe Group ◽  
Conventional Ct ◽  
Spearman’S Correlation

Abstract Objectives: This study aims to explore and compare a novel deep learning-based quantification with the conventional semi-quantitative computed tomography (CT) scoring for the serial chest CT scans of COVID-19. Materials and Methods: 95 patients with confirmed COVID-19 and a total of 465 serial chest CT scans were involved, including 61 moderate patients (moderate group, 319 chest CT scans) and 34 severe patients (severe group, 146 chest CT scans). Conventional CT scoring and deep learning-based quantification were performed for all chest CT scans for two study goals: 1. Correlation between these two estimations; 2. Exploring the dynamic patterns using these two estimations between moderate and severe groups.Results: The Spearman’s correlation coefficient between these two estimation methods was 0.920 (p<0.001). predicted pulmonary involvement (CT score and percent of pulmonary lesions calculated using deep learning-based quantification) increased more rapidly and reached a higher peak on 23rd days from symptom onset in severe group, which reached a peak on 18th days in moderate group with faster absorption of the lesions. Conclusions: The deep learning-based quantification for COVID-19 showed a good correlation with the conventional CT scoring and demonstrated a potential benefit in the estimation of disease severities of COVID-19.

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