Chest computed tomography findings of COVID-19 pneumonia: pictorial essay with literature review.
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ABSTRACT:
SUBMITTER: Cellina M
PROVIDER: S-EPMC7315402 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
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Chest computed tomography findings of COVID-19 pneumonia: pictorial essay with literature review.
Cellina Michaela M Orsi Marcello M Valenti Pittino Carlo C Toluian Tahereh T Oliva Giancarlo G
Japanese journal of radiology 20200625 11
Available information on chest Computed Tomography (CT) findings of the 2019 novel coronavirus disease (COVID-19) is constantly evolving. Ground glass opacities and consolidation with bilateral and peripheral distribution were reported as the most common CT findings, but also less typical features could be identified. All radiologists should be aware of the imaging spectrum of the COVID-19 pneumonia and imaging changes in the course of the disease. Our aim is to display the chest CT findings at ...[more]
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Project description:PurposeThe purpose of our study was to determine the usability of lung ultrasonography (LUS) in the diagnosis of COVID-19, and to match the morphological features of lesions detected on computed tomography (CT) with the findings observed on LUS.MethodsSixty patients with COVID-19 were included in this prospective study. Patients were examined by radiology and anesthesia clinic specialists for a visual CT score. A LUS 12-zone ultrasonography protocol was applied by the investigator blinded to the CT and PCR test results. The characteristics of abnormal findings and the relationship of lesions to the pleura and the distance to the pleura were investigated.ResultsForty-five males and 25 females evaluated within the scope of the study had an average age of 61.2?±?15.3 years. The total CT score was calculated as 14.3?±?5.3, and the LUS score was found to be 19.9?±?7.6. There was a statistically significant positive correlation between the measured LUS and CT scores (r?=?0.857, p?<?0.001). The mean distance of these lesions to the pleura was 5.2?±?1.76 cm. LUS findings in 51 areas corresponded to non-pleural lesions on CT. There was a negative correlation between the measured distance to the pleura and the LUS scores (p?<?0.001, r?=?-?0.708).ConclusionThe results of this study showed that the correlation between CT and LUS findings may be used in the diagnosis of COVID-19 pneumonia, although there are some limitations. ClinicalTrials.gov identifier: NCT04719234.
| S-EPMC7908963 | biostudies-literature
Project description:Objective:The COVID-19 pandemic and annual influenza epidemic are responsible for thousands of deaths globally. With a similarity in clinical as well as laboratory findings, there is a need to differentiate these two conditions on chest CT scan. This paper attempts to use existing literature to draw out differences in chest CT findings in COVID-19 and influenza. Methods:A search was conducted using PubMed. 17 original studies on chest CT findings in COVID-19 and influenza were identified for full-text review and data analysis. Findings. COVID-19 and influenza share similar chest CT findings. The differences found show that COVID-19 ground-glass opacities are usually peripherally located with the lower lobes being commonly involved, while influenza has a central, peripheral, or random distribution usually affecting the five lobes. Vascular engorgement, pleural thickening, and subpleural lines were reported in COVID-19 patients. In contrast, pneumomediastinum and pneumothorax were reported only in studies on influenza. Conclusion and Relevance. COVID-19 and influenza have overlapping chest CT features with few differences which can assist in telling apart the two pathologies. Additional studies are needed to further define the differences and degree between COVID-19 and influenza.
| S-EPMC7275219 | biostudies-literature
Project description:The goals of this pictorial essay are: (1) to set out a multislice computed tomography (MSCT) imaging protocol to assess infective endocarditis (IE); (2) to give an MSCT overview of valvular and peri-valvular involvement during IE; (3) to give a CT overview of septic embolism and infectious pseudoaneurysms during IE.MSCT acquisition protocols to assess IE are performed in two different phases: the first acquisition, under electrocardiography (ECG) gating, covers the cardiac structures during first-pass iodine injection; the second acquisition covers the thorax, abdomen, pelvic and cerebral regions.Valvular and peri-valvular lesions during IE are: vegetation-a hypodense, homogeneous, irregular mass on a valve or endocardial structure; perforation-a defect in the leaflet; valvular aneurysm-loss of the homogenous curvature of the leaflet; valvular thickening; peri-valvular abscess; pseudoaneurysm; fistula and disinsertion of a prosthetic valve. Extra-cardiac location could involve all organs.MSCT can be considered as a useful complement in visualising the cardiac lesions of IE if echocardiography is inconclusive. MSCT is the only imaging modality that provides assessment of valvular and peri-valvular involvement, extra-cardiac lesions, and non-invasive evaluation of the coronary artery anatomy, simultaneously.• MSCT provides assessment of coronary anatomy, cardiac and extra-cardiac lesions. • MSCT represents an alternative to echocardiography during IE. • Surgical valve replacement is usually required if vegetation is >10 mm. • Peri-valvular extension (abscesses, pseudoaneurysm and fistulae) required surgical treatment.
| S-EPMC4195843 | biostudies-other
Project description:ObjectiveThe aim of our study was to assess the effect of a short-term treatment with low-moderate corticosteroid (CS) doses by both a quantitative and qualitative assessment of chest HRCT of COVID-19 pneumonia.MethodsCORTICOVID is a single-center, cross-sectional, retrospective study involving severe/critical COVID-19 patients with mild/moderate ARDS. Lung total severity score was obtained according to Chung and colleagues. Moreover, the relative percentages of lung total severity score by ground glass opacities, consolidations, crazy paving, and linear bands were computed. Chest HRCT scores, P/F ratio, and laboratory parameters were evaluated before (pre-CS) and 7-10 days after (post-CS) methylprednisolone of 0.5-0.8 mg/kg/day.FindingsA total of 34 severe/critical COVID-19 patients were included in the study, of which 17 received Standard of Care (SoC) and 17 CS therapy in add-on. CS treatment disclosed a significant decrease in HRCT total severity score [median = 6 (IQR: 5-7.5) versus 10 (IQR: 9-13) in SoC, p < 0.001], as well in single consolidations [median = 0.33 (IQR: 0-0.92) versus 6.73 (IQR: 2.49-8.03) in SoC, p < 0.001] and crazy paving scores [mean = 0.19 (SD = 0.53) versus 1.79 (SD = 2.71) in SoC, p = 0.010], along with a significant increase in linear bands [mean = 2.56 (SD = 1.65) versus 0.97 (SD = 1.30) in SoC, p = 0.006]. GGO score instead did not significantly differ at the end of treatment between the two groups. Most post-CS GGO, however, derived from previous consolidations and crazy paving [median = 1.5 (0.35-3.81) versus 2 (1.25-3.8) pre-CS; p = 0.579], while pre-CS GGO significantly decreased after methylprednisolone therapy [median = 0.66 (0.05-1.33) versus 1.5 (0.35-3.81) pre-CS; p = 0.004]. CS therapy further determined a significant improvement in P/F levels [median P/F = 310 (IQR: 235.5-370) versus 136 (IQR: 98.5-211.75) in SoC; p < 0.001], and a significant increase in white blood cells, lymphocytes, and neutrophils absolute values.ConclusionThe improvement of all chest HRCT findings further supports the role of CS adjunctive therapy in severe/critical COVID-19 pneumonia.
| S-EPMC8477677 | biostudies-literature
Project description:BackgroundThe aim of this systematic review is to evaluate the chest computed tomography (CT) findings in infants with confirmed COVID-19 infection by providing a comprehensive review of the existing literature.Data sourcesA systematic search was conducted on PubMed and Embase from the onset of the COVID-19 outbreak to October 20, 2020, for studies that discussed the chest CT findings in infants younger than 1 year with COVID-19 infection.ResultsA total of 35 studies comprising 70 COVID-19 (58.5% boys) confirmed infants were included. The mean age of the included patients was 4.1 months with a range of 1 day to 12 months. Chest CT scans showed bilateral abnormalities in 34 patients, and unilateral lung involvement in 25 patients. Ground-glass opacities (GGO) (71.43%) were found to be the most prevalent chest CT manifestation, followed by peribronchial thickening (60%), linear or band-shaped opacities (32.8%), consolidation (28.57%), nodule (18.57%), effusion (7.14%) and focal lucency (7.14%).ConclusionsGGO and peribronchial thickening were the most prevalent findings in the infants' chest CT scans. Linear or band-shaped opacities, consolidation, and pulmonary nodules are more common in infants than in adults. These findings suggest that the disease is more likely to be presented as an atypical pneumonia (peribronchial thickening and linear or band-shaped opacities) in this age group. Other chest CT scan manifestations can be classified as typical COVID-19 infection (peripheral GGO), lobar pneumonia (consolidation) and opportunistic infections (pulmonary nodules).
| S-EPMC8104919 | biostudies-literature
Project description:Background and objectivePatients with coronavirus disease 2019 (COVID-19) pneumonia present with typical findings on chest computed tomography (CT), but the underlying histopathological patterns are unknown. Through direct regional correlation of imaging findings to histopathological patterns, this study aimed to explain typical COVID-19 CT patterns at tissue level.MethodsEight autopsy cases were prospectively selected of patients with PCR-proven COVID-19 pneumonia with varying clinical manifestations and causes of death. All had been subjected to chest CT imaging 24-72 h prior to death. Twenty-seven lung areas with typical COVID-19 patterns and two radiologically unaffected pulmonary areas were correlated to histopathological findings in the same lung regions.ResultsTwo dominant radiological patterns were observed: ground-glass opacity (GGO) (n = 11) and consolidation (n = 16). In seven of 11 sampled areas of GGO, diffuse alveolar damage (DAD) was observed. In four areas of GGO, the histological pattern was vascular damage and thrombosis, with (n = 2) or without DAD (n = 2). DAD was also observed in five of 16 samples derived from areas of radiological consolidation. Seven areas of consolidation were based on a combination of DAD, vascular damage and thrombosis. In four areas of consolidation, bronchopneumonia was found. Unexpectedly, in samples from radiologically unaffected lung parenchyma, evidence was found of vascular damage and thrombosis.ConclusionIn COVID-19, radiological findings of GGO and consolidation are mostly explained by DAD or a combination of DAD and vascular damage plus thrombosis. However, the different typical CT patterns in COVID-19 are not related to specific histopathological patterns. Microvascular damage and thrombosis are even encountered in the radiologically normal lung.
| S-EPMC8447040 | biostudies-literature
Project description:AimsSeveral studies have unveiled the great heterogeneity of COVID-19 pneumonia. Identification of the "vascular phenotype" (involving both pulmonary parenchyma and its circulation) has prognostic significance. Our aim was to explore the combined role of chest computed tomography (CT) scan and electrocardiogram (ECG) at hospital admission in predicting short-term prognosis and to draw pathophysiological insights.Methods and resultsWe analyzed the chest CT scan and ECG performed at admission in 151 consecutive COVID-19 patients admitted between 20 March and 4 April 2020. All-cause mortality within 30 days was the primary endpoint. Median age was 71 years (IQR: 62-76). Severe pneumonia was present in 25 (17%) patients, and 121 (80%) had abnormal ECG. During a median follow-up of 7 days (IQR: 4-13), 54 (36%) patients died. Deceased patients had more severe pneumonia than survivors did (80% vs. 64%, p = 0.044). ECG in deceased patients showed more frequently atrial fibrillation/flutter (17% vs. 6%, p = 0.039) and acute right ventricular (RV) strain (35% vs. 10%, p < 0.001), suggesting the "vascular phenotype". ECG signs of acute RV strain (HR 2.46, 95% CIs 1.36-4.45, p = 0.0028) were independently associated with all-cause mortality in multivariable analysis, and in the likelihood ratio test, showed incremental prognostic value over chest CT scan, age, and C-reactive protein.ConclusionsCombining chest CT scan and ECG data improves risk stratification in COVID-19 pneumonia by identifying a distinctive phenotype with both parenchymal and vascular damage of the lung. Patients with severe pneumonia at chest CT scan plus ECG signs of acute RV strain have an extremely poor short-term prognosis.
| S-EPMC8303750 | biostudies-literature
Project description:Introduction: Computed Tomography is an essential diagnostic tool in the management of COVID-19. Considering the large amount of examinations in high case-load scenarios, an automated tool could facilitate and save critical time in the diagnosis and risk stratification of the disease.Methods: A novel deep learning derived machine learning (ML) classifier was developed using a simplified programming approach and an open source dataset consisting of 6868 chest CT images from 418 patients which was split into training and validation subsets. The diagnostic performance was then evaluated and compared to experienced radiologists on an independent testing dataset. Diagnostic performance metrics were calculated using Receiver Operating Characteristics (ROC) analysis. Operating points with high positive (>10) and low negative (<0.01) likelihood ratios to stratify the risk of COVID-19 being present were identified and validated.Results: The model achieved an overall accuracy of 0.956 (AUC) on an independent testing dataset of 90 patients. Both rule-in and rule out thresholds were identified and tested. At the rule-in operating point, sensitivity and specificity were 84.4 % and 93.3 % and did not differ from both radiologists (p?>?0.05). At the rule-out threshold, sensitivity (100 %) and specificity (60 %) differed significantly from the radiologists (p?<?0.05). Likelihood ratios and a Fagan nomogram provide prevalence independent test performance estimates.Conclusion: Accurate diagnosis of COVID-19 using a basic deep learning approach is feasible using open-source CT image data. In addition, the machine learning classifier provided validated rule-in and rule-out criteria could be used to stratify the risk of COVID-19 being present.
| S-EPMC7641539 | biostudies-literature
Project description:PURPOSE:The relationship between lung ultrasound (LUS) and chest computed tomography (CT) scans in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia is not clearly defined. The primary objective of our study was to assess the performance of LUS in determining severity of SARS-CoV-2 pneumonia compared with chest CT scan. Secondary objectives were to test the association between LUS score and location of the patient, use of mechanical ventilation, and the pulse oximetry (SpO2)/fractional inspired oxygen (FiO2) ratio. METHODS:A multicentre observational study was performed between 15 March and 20 April 2020. Patients in the Emergency Department (ED) or Intensive Care Unit (ICU) with acute dyspnoea who were PCR positive for SARS-CoV-2, and who had LUS and chest CT performed within a 24-h period, were included. RESULTS:One hundred patients were included. LUS score was significantly associated with pneumonia severity assessed by chest CT and clinical features. The AUC of the ROC curve of the relationship of LUS versus chest CT for the assessment of severe SARS-CoV-2 pneumonia was 0.78 (CI 95% 0.68-0.87; p?<?0.0001). A high LUS score was associated with the use of mechanical ventilation, and with a SpO2/FiO2 ratio below 357. CONCLUSION:In known SARS-CoV-2 pneumonia patients, the LUS score was predictive of pneumonia severity as assessed by a chest CT scan and clinical features. Within the limitations inherent to our study design, LUS can be used to assess SARS-CoV-2 pneumonia severity.
| S-EPMC7388119 | biostudies-literature
Project description:ObjectivesGround-glass opacity and consolidation are recognized typical features of Coronavirus disease-19 (COVID-19) pneumonia on Chest CT, yet ancillary findings have not been fully described. We aimed to describe ancillary findings of COVID-19 pneumonia on CT, to define their prevalence, and investigate their association with clinical data.MethodsWe retrospectively reviewed our CT chest cases with coupled reverse transcriptase polymerase chain reaction (rt-PCR). Patients with negative rt-PCR or without admission chest CT were excluded. Ancillary findings included: vessel enlargement, subpleural curvilinear lines, dependent subpleural atelectasis, centrilobular solid nodules, pleural and/or pericardial effusions, enlarged mediastinal lymph nodes. Continuous data were expressed as median and 95% confidence interval (95% CI) and tested by Mann-Whitney U test.ResultsAncillary findings were represented by 106/252 (42.1%, 36.1 to 48.2) vessel enlargement, 50/252 (19.8%, 15.4 to 25.2) subpleural curvilinear lines, 26/252 (10.1%, 7.1 to 14.7) dependent subpleural atelectasis, 15/252 (5.9%, 3.6 to 9.6) pleural effusion, 15/252 (5.9%, 3.6 to 9.6) mediastinal lymph nodes enlargement, 13/252 (5.2%, 3 to 8.6) centrilobular solid nodules, and 6/252 (2.4%, 1.1 to 5.1) pericardial effusion. Air space disease was more extensive in patients with vessel enlargement or centrilobular solid nodules (p < 0.001). Vessel enlargement was associated with longer history of fever (p = 0.035) and lower admission oxygen saturation (p = 0.014); dependent subpleural atelectasis with lower oxygen saturation (p < 0.001) and higher respiratory rate (p < 0.001); mediastinal lymph nodes with shorter history of cough (p = 0.046); centrilobular solid nodules with lower prevalence of cough (p = 0.023), lower oxygen saturation (p < 0.001), and higher respiratory rate (p = 0.032), and pericardial effusion with shorter history of cough (p = 0.015). Ancillary findings associated with longer hospital stay were subpleural curvilinear lines (p = 0.02), whereas centrilobular solid nodules were associated with higher rate of intensive care unit admission (p = 0.01).ConclusionTypical high-resolution CT findings of COVID-19 pneumonia are frequently associated with ancillary findings that variably associate with disease extent, clinical parameters, and disease severity.Advances in knowledgeAncillary findings might reflect the broad range of heterogeneous mechanisms in severe acute respiratory syndrome from viral pneumonia, and potentially help disease phenotyping.
| S-EPMC7934290 | biostudies-literature