Diagnosis Of COVID-19 Pneumonia Research Articles

Association between Acute Pancreatitis and COVID-19: Could Pancreatitis Be the Missing Piece of the Puzzle about Increased Mortality Rates?

Background The COVID-19 pandemic caused by SARS-CoV-2 commenced in Wuhan China in 2019 and soon spread worldwide. SARS-CoV-2 enters the cell by binding to the ACE II receptor and begins viral replication. The effects and clinical findings of SARS-CoV-2 on the liver, kidney, heart, gastrointestinal (GI) system and especially lungs have been widely discussed. However, the effects on the pancreas—another organ that also expresses ACE II—have not been studied. Methods This work prospectively evaluated data from 316 patients who were admitted with a diagnosis of COVID-19 pneumonia. The patients were categorized into three according to the severity of pneumonia (mild, severe, critical). Demographic data, rate of pancreatitis, biochemical parameters, and radiological images from each group were analyzed. The patients were divided into two groups and outcomes were compared: COVID-19 patients with acute pancreatitis (Group P) and without acute pancreatitis (Group C). Results The median age was 54 (18–87), and the median age for patients with acute pancreatitis was 55 (26–84). As an expected finding, we found a positive correlation between advanced age and mortality (p = 0.0003). 12.6% of the patients had acute pancreatitis. While pancreatitis was not seen in patients on mild status, the rate of pancreatitis was 32.5% in critical patients. Hospitalization and mortality rates were higher in patients with COVID-19 accompanied by acute pancreatitis (p = 0.0038 and p < 0.0001, respectively). C-Reactive Protein (CRP) and ferritin were significantly higher in those who had pancreatitis (p < 0.0001). D-Dimer and procalcitonin levels had only a small difference (p = 0.1127 and p = 0.3403, respectively) Conclusion Acute pancreatitis alone is a clinical condition that can lead to mortality and may be one of the reasons for the exaggerated immune response developing in the progression of COVID-19. Our results point out that the presence of pancreatic damage triggered by SARS-CoV-2 can deteriorate the clinical condition of patients and the mortality rate may increase in these patients.

Clinical usefulness of tomographic standards for COVID-19 pneumonia diagnosis: Experience from a Brazilian reference center

BackgroundCOVID-19 is a new disease and the most common complication is pneumonia. The Radiological Society of North America (RSNA) proposed an expert consensus for imaging classification for COVID-19 pneumonia. ObjectiveTo evaluate sensitivity, specificity, accuracy, and reproducibility of chest CT standards in the beginning of the Brazilian COVID-19 outbreak. MethodsCross-sectional study performed from March 1st to April 14th, 2020. Patients with suspected COVID-19 pneumonia submitted to RT-PCR test and chest computed tomography (CT) were included. Two thoracic radiologists blinded for RT-PCR and clinical and laboratory results classified every patient scan according to the RSNA expert consensus. A third thoracic radiologist also evaluated in case of discordance, and consensus was reached among the three radiologists. A typical appearance was considered a positive chest CT for COVID-19 pneumonia. Sensitivity, specificity, positive and negative predictive values were calculated. Cohen’s kappa coefficient was used to evaluate intra- and inter-rater agreements. ResultsA total of 159 patients were included (mean age 57.9 ± 18.0 years; 88 [55.3%] males): 86 (54.1%) COVID-19 and 73 (45.9%) non-COVID-19 patients. Eighty (50.3%) patients had a positive CT for COVID-19 pneumonia. Sensitivity and specificity of typical appearance were 88.3% (95%CI, 79.9–93.5) and 94.5% (95%CI, 86.7–97.8), respectively. Intra- and inter-rater agreement were assessed (Cohen’s kappa = 0.924, P = 0.06; Cohen’s kappa=0.772, P = 0.05, respectively). ConclusionChest CT categorical classification of COVID-19 findings is reproducible and demonstrates high level of agreement with clinical and RT-PCR diagnosis of COVID-19. In RT-PCR scarcity scenarios or in equivocal cases, it may be useful for attending physicians in the evaluation of suspected COVID-19 pneumonia patients attended at the emergency unit.

Lung ultrasound is a reliable diagnostic technique to predict abnormal CT chest scan and to detect oxygen requirements in COVID-19 pneumonia.

COVID-19 pneumonia can be severe, with an unpredictable evolution and high mortality prevalence in older patients. The diagnosis is usually performed by RT-PCR or CT chest scan. Lung ultrasonography (LUS) has been proposed as an alternative method to monitor patients with COVID-19 pneumonia.To assess the diagnostic performance of LUS, we performed LUS using a portable device and adapting a protocol already used in Acute Respiratory Syndrome. We used the score obtained with the index we created to assess for LUS diagnostic performance as compared to lung CT chest scan and to predict for oxygen requirements.Daily bedside LUS was easy to perform and microbiologically safe. LUS was 89% sensitive and 100% specific in predicting CT chest scan abnormalities, and 95% sensitive and 67% specific in detecting oxygen requirements.This is the first report on the diagnostic performance of LUS as compared to CT chest scan for the diagnosis of COVID-19 pneumonia and assessments of oxygen requirements by LUS. LUS could help in the orientation of dyspneic patients to intensive care. It could also be proposed when there is limited access to CT scan in the context of a pandemic crisis, or to implement clinical lung examinations for outpatient follow-up.

Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures

PurposeHigh-dimensional image features that underlie COVID-19 pneumonia remain opaque. We aim to compare feature engineering and deep learning methods to gain insights into the image features that drive CT-based for COVID-19 pneumonia prediction, and uncover CT image features significant for COVID-19 pneumonia from deep learning and radiomics framework.MethodsA total of 266 patients with COVID-19 and other viral pneumonia with clinical symptoms and CT signs similar to that of COVID-19 during the outbreak were retrospectively collected from three hospitals in China and the USA. All the pneumonia lesions on CT images were manually delineated by four radiologists. One hundred eighty-four patients (n = 93 COVID-19 positive; n = 91 COVID-19 negative; 24,216 pneumonia lesions from 12,001 CT image slices) from two hospitals from China served as discovery cohort for model development. Thirty-two patients (17 COVID-19 positive, 15 COVID-19 negative; 7883 pneumonia lesions from 3799 CT image slices) from a US hospital served as external validation cohort. A bi-directional adversarial network-based framework and PyRadiomics package were used to extract deep learning and radiomics features, respectively. Linear and Lasso classifiers were used to develop models predictive of COVID-19 versus non-COVID-19 viral pneumonia.Results120-dimensional deep learning image features and 120-dimensional radiomics features were extracted. Linear and Lasso classifiers identified 32 high-dimensional deep learning image features and 4 radiomics features associated with COVID-19 pneumonia diagnosis (P < 0.0001). Both models achieved sensitivity > 73% and specificity > 75% on external validation cohort with slight superior performance for radiomics Lasso classifier. Human expert diagnostic performance improved (increase by 16.5% and 11.6% in sensitivity and specificity, respectively) when using a combined deep learning-radiomics model.ConclusionsWe uncover specific deep learning and radiomics features to add insight into interpretability of machine learning algorithms and compare deep learning and radiomics models for COVID-19 pneumonia that might serve to augment human diagnostic performance.

Predictive value of initial CT scan for various adverse outcomes in patients with COVID-19 pneumonia

BackgroundChest computed tomography (CT) scan is frequently used in the diagnosis of COVID-19 pneumonia. ObjectivesThis study investigates the predictive value of CT severity score (CSS) for length-of-stay (LOS) in hospital, initial disease severity, ICU admission, intubation, and mortality. MethodsIn this retrospective study, initial CT scans of consecutively admitted patients with COVID-19 pneumonia were reviewed in a tertiary hospital. The association of CSS with the severity of disease upon admission and the final adverse outcomes was assessed using Pearson's correlation test and logistic regression, respectively. ResultsTotal of 121 patients (60±16 years), including 54 women and 67 men, with positive RT-PCR tests were enrolled. We found a significant but weak correlation between CSS and qSOFA, as a measure of disease severity (r: 0.261, p = 0.003). No significant association was demonstrated between CSS and LOS. Patients with CSS>8 had at least three-fold higher risk of ICU admission, intubation, and mortality. ConclusionsCSS in baseline CT scan of patients with COVID-19 pneumonia can predict adverse outcomes and is weakly correlated with initial disease severity.

High serum IL-6 values increase the risk of mortality and the severity of pneumonia in patients diagnosed with COVID-19

The clinical presentation of COVID-19 is very heterogeneous, ranging from asymptomatic to severe, which could lead to the need for mechanical ventilation or even death.We analyzed the serum levels of IL-6 in patients with COVID-19 diagnosis and its relationship with the severity of the disease, the need for mechanical ventilation and with patient mortality. We assessed IL-6 in a cohort of 50 patients diagnosed with COVID-19 pneumonia with different degrees of disease severity, and compared it with clinical and laboratory findings.We found higher levels of IL-6 in patients with more severe pneumonia according to CURB-65 scale (p = 0.001), with ICU mechanical ventilation requirements (p = 0.02), and who subsequently died (p = 0.003). Of the clinical and analytical parameters analyzed in the current study, the serum levels of IL-6 was the most effective predictor of disease severity. From the data obtained in ROC curve analysis, we defined a cut-off point for serum IL-6 levels of 35 pg/mL above which both the risk of mortality (OR = 20.00, 95 % CI 4.214-94-912, p = 0.0001) and ICU admission (OR = 12.750, 95 % CI 2,159-75,3,3, p = 0.005) were increased. Starting from blood IL-6 levels 27 out of 50 patients, with high levels and more severe symptoms, were treated with the IL-6 receptor antagonist Tocilizumab.IL-6 serum levels appear to be a useful prognostic biomarker in patients with a diagnosis of COVID-19 pneumonia. A cut-off point of 35 pg/mL could clearly differentiate patients a with more severe disease.

Successful Treatment of a COVID-19 Case with Pneumonia and Renal Injury Using Tocilizumab

A 49-year-old male Japanese patient was admitted to our hospital under the diagnosis of COVID-19 pneumonia. For 5 days before admission, he had experienced various symptoms, including high fever, watery diarrhea, dyspnea, and cough, and he tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid. The patient is a smoker who was on medication for hypertension. A chest computed tomography scan showed bilateral multiple patchy ground-glass opacities. Despite being treated with several therapeutic agents, he still exhibited dyspnea (oxygen saturation [SpO2] in ambient air: 88%), a high fever (axillary temperature: 39 °C), and high blood pressure (148/98 mmHg). Because laboratory data revealed high levels of C-reactive protein (CRP; 2.10 mg/dL) and urinary β2-microglobulin (B2M; 33,683 µg/mL), the anti-interleukin-6 receptor antibody tocilizumab (TCZ; 400 mg) was administered intravenously. One day after injection, he was afebrile. Four days after the TCZ injection, his CRP level dropped to 0.27 mg/dL, B2M level decreased to 3817 µg/mL, and viral load became low. No adverse drug reaction due to TCZ was observed. The patient was discharged 15 days after admission. The early administration of TCZ in this patient prevented the pneumonia and kidney injury caused by COVID-19 from progressing to hyperinflammation syndrome.

Ultrasound in Suspected Pneumonic COVID-19: Our Experience

Coronavirus disease-19 [COVID-19] is a pandemic spreading all over the world. The novel corona virus has a specific tropism for the low respiratory airways causing viral pneumonia. Early diagnosis of suspicious COVID-19 pneumonia represents a pillar for immediate management. Computed tomography [CT] scan is considered the gold-standard screening tool, but it has several limitations. A chest ultrasound could play a role in COVID-19

Comparison of admission chest computed tomography and lung ultrasound performance for diagnosis of COVID-19 pneumonia in populations with different disease prevalence

PurposeChest computed tomography (CT) is considered a reliable imaging tool for COVID-19 pneumonia diagnosis, while lung ultrasound (LUS) has emerged as a potential alternative to characterize lung involvement. The aim of the study was to compare diagnostic performance of admission chest CT and LUS for the diagnosis of COVID-19. MethodsWe included patients admitted to emergency department between February 21-March 6, 2020 (high prevalence group, HP) and between March 30-April 13, 2020 (moderate prevalence group, MP) undergoing LUS and chest CT within 12 h. Chest CT was considered positive in case of “indeterminate”/“typical” pattern for COVID-19 by RSNA classification system. At LUS, thickened pleural line with ≥ three B-lines at least in one zone of the 12 explored was considered positive. Sensitivity, specificity, PPV, NPV, and AUC were calculated for CT and LUS against real-time reverse transcriptase polymerase chain reaction (RT-PCR) and serology as reference standard. ResultsThe study included 486 patients (males 61 %; median age, 70 years): 247 patients in HP (COVID-19 prevalence 94 %) and 239 patients in MP (COVID-19 prevalence 45 %).In HP and MP respectively, sensitivity, specificity, PPV, and NPV were 90–95 %, 43–69 %, 96−72 %, 20–95 % for CT and 94−93 %, 7–31 %, 94−52 %, 7–83 % for LUS. CT demonstrated better performance than LUS in diagnosis of COVID-19, both in HP (AUC 0.75 vs 0.51; P < 0.001) and MP (AUC 0.85 vs 0.62; P < 0.001). ConclusionsAdmission chest CT shows better performance than LUS for COVID-19 diagnosis, at varying disease prevalence. LUS is highly sensitive, but not specific for COVID-19.

Thromboembolic Events and Role of Point of Care Ultrasound in Hospitalized Covid-19 Patients Needing Intensive Care Unit Admission.

Background:Covid-19 associated coagulopathy (CAC) is associated with prothrombotic state and thromboembolism. However, true incidence of thromboembolic events is difficult to determine in the ICU setting. The aim of our study was to investigate the cumulative incidence of thromboembolic events in Covid-19 patients needing intensive care unit (ICU) admission and assessing the utility of point of care ultrasound (POCUS) to screen for and diagnose lower extremity deep venous thrombosis (DVT).Methods:We conducted a prospective observational study between April 22nd and May 26th, 2020 where all adult patients with the diagnosis of Covid-19 pneumonia admitted to 8 ICUs of Montefiore Medical Center were included. POCUS exam was performed on all patients at day 1 of ICU admission and at day 7 and 14 after the first exam.Results:The primary outcome was to study the cumulative incidence of thromboembolic events in Covid-19 patients needing ICU admission. A total of 107 patients were included. All patients got POCUS exam on day 1 in the ICU, 62% got day 7 and 41% got day 14 exam. POCUS diagnosed 17 lower extremity DVTs on day 1, 3 new on day 7 and 1 new on day 14. Forty patients developed 52 thromboembolic events, with the rate of 37.3%. We found a high 45-day cumulative incidence of thromboembolic events of 37% and a high 45-day cumulative incidence of lower and upper extremity DVT of 21% and 10% respectively. Twelve (30%) patients had failure of therapeutic anticoagulation. Occurrence of a thromboembolic event was not associated with a higher risk of mortality (HR 1.08, p value = .81).Conclusions:Covid-19 patients in ICU have a high cumulative incidence of thromboembolic events, but not associated with higher mortality. POCUS is an excellent tool to help screen and diagnose DVT during a pandemic.

COVID-19 pneumonia: high diagnostic accuracy of chest CT in patients with intermediate clinical probability.

ObjectivesTo assess inter-reader agreements and diagnostic accuracy of chest CT to identify COVID-19 pneumonia in patients with intermediate clinical probability during an acute disease outbreak.MethodsFrom March 20 to April 8, 319 patients (mean age 62.3 years old) consecutive patients with an intermediate clinical probability of COVID-19 pneumonia underwent a chest CT scan. Two independent chest radiologists blinded to clinical information and RT-PCR results retrospectively reviewed and classified images on a 1–5 confidence level scale for COVID-19 pneumonia. Agreements between radiologists were assessed with kappa statistics. Diagnostic accuracy of chest CT compared with RT-PCR assay and patient outcomes was measured using receiver operating characteristics (ROC). Positive predictive value (PPV) and negative predictive value (NPV) for COVID-19 pneumonia were calculated.ResultsInter-observer agreement for highly probable (kappa: 0.83 [p < .001]) and highly probable or probable (kappa: 0.82 [p < .001]) diagnosis of COVID-19 pneumonia was very good. RT-PCR tests performed in 307 patients were positive in 174 and negative in 133. The areas under the curve (AUC) were 0.94 and 0.92 respectively. With a disease prevalence of 61.2%, PPV were 95.9% and 94.3%, and NPV 84.4% and 77.1%.ConclusionDuring acute COVID-19 outbreak, chest CT scan may be used for triage of patients with intermediate clinical probability with very good inter-observer agreements and diagnostic accuracy.Key Points • Concordances between two chest radiologists to diagnose or exclude a COVID-19 pneumonia in 319 consecutive patients with intermediate clinical probability were very good (kappa: 0.82; p < .001). • When compared with RT-PCR results and patient outcomes, the diagnostic accuracy of CT to identify COVID-19 pneumonia was high for both radiologists (AUC: 0.94 and 0.92). • With a disease prevalence of 61.2% in the studied population, the positive predictive values of CT for diagnosing COVID-19 pneumonia were 95.9% and 94.3% with negative predictive values of 84.4% and 77.1%. Electronic supplementary materialThe online version of this article (10.1007/s00330-020-07346-y) contains supplementary material, which is available to authorized users.

The Role of Imaging in COVID-19 Pneumonia Diagnosis and Management: Main Positions of the Experts, Key Imaging Features and Open Answers.

Lung imaging is widely involved in facing the coronavirus disease (COVID-19) pandemic. In fact, the COVID-19 infection may lead to a rapidly evolving and potentially fatal pneumonia. Moreover, computed tomography (CT) can be more sensitive than the COVID-19 reverse transcriptase-polymerase chain reaction test, especially at the beginning of the disease. Only patients with mild features consistent with COVID-19 infection, negative COVID-19 test, or positive COVID-19 test but at low risk for disease progression should avoid imaging. However, imaging becomes mandatory if respiratory symptoms worsen. A CT pattern classification has been designed to help both radiologists and clinicians. The typical pattern of COVID-19 is depicted by multifocal, bilateral, and peripheral ground-glass opacities (with or without consolidations or crazy paving) or findings of organizing pneumonia. Moreover, CT has demonstrated a prognostic role in patients with a diagnosis of COVID-19 pneumonia. Lung ultrasounds (LUS) are an emergent tool in the diagnosis of the disease. The adoption of LUS combined to chest X-rays in COVID-19 in pneumonia diagnosis is an interesting prospect that needs to be confirmed.

285 Deployment of Artificial Intelligence for Radiographic Diagnosis of COVID-19 Pneumonia in the Emergency Department

The surge and long tail of patients in acute respiratory distress during the coronavirus-19 (CoVID19) pandemic has inspired new innovations in diagnosing, treating and dispositioning patients during high census conditions with constrained resources. During the first wave of the pandemic, we deployed an artificial intelligence (AI) algorithm for assisted interpretation of chest x-ray for use by radiologists and emergency department (ED) physicians. We report first experiences of physician interaction with this novel AI algorithm designed to enhance physician abilities to identify ground glass and consolidation on chest radiographs.

6 Lung Ultrasound versus Chest X-ray for the Diagnosis of COVID-19 Pneumonia

The viral illness severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), more commonly known as coronavirus 2019 (COVID-19), has become a global pandemic infecting over 2 million individuals worldwide. Symptoms are often vague and physical exam findings have proven unreliable as indicators of infection. Therefore, diagnosis typically relies on imaging or nasopharyngeal swabs. The objective of this study was to compare point-of-care lung ultrasound (LUS) with chest x-ray (CXR) to determine which is the more accurate diagnostic imaging modality for diagnosing COVID-19 pneumonia.

Accidental diagnosis of COVID-19 pneumonia after 18F FDG PET/CT: a case series.

PurposeThe aim of this case series is to illustrate possible [18F]-FDG uptake patterns associated to COVID-19.MethodsRetrospective assessment of all Fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) scans performed for any clinical / oncological reason from 1st April 2020 to 30th April 2020. Results of PCR testing for SARS-CoV-2 were retrieved for all patients with lung consolidations and/or peripheral ground glass opacities characterized by increased metabolism to evaluate any possible association with the viral infection.ResultsSeven (4%) out of 172 FDG-PET scans were included. Six out of seven patients (85%) had positive RT-PCR for SARS-CoV-2, while one patient (15%) had possible (not PCR confirmed) COVID-19 pneumonia.ConclusionSuspicious accidental COVID-19 findings in Nuclear Medicine Department need to be reported and appropriately evaluated to implement proper supportive treatment and infection control measures.

Ultrasound Elastography for Lung Disease Assessment.

Ultrasound elastography (US-E) is a noninvasive, safe, cost-effective and reliable technique to assess the mechanical properties of soft tissue and provide imaging biomarkers for pathological processes. Many lung diseases such as acute respiratory distress syndrome, chronic obstructive pulmonary disease, and interstitial lung disease are associated with dramatic changes in mechanical properties of lung tissues. Nevertheless, US-E is rarely used to image the lung because it is filled with air. The large difference in acoustic impedance between air and lung tissue results in the reflection of the ultrasound wave at the lung surface and, consequently, the loss of most ultrasound energy. In recent years, there has been an increasing interest in US-E applications in evaluating lung diseases. This article provides a comprehensive review of the technological advances of US-E research on lung disease diagnosis. We introduce the basic principles and major techniques of US-E and provide information on various applications in lung disease assessment. Finally, the potential applications of US-E to the diagnosis of COVID-19 pneumonia is discussed.

Accuracy of Bedside Lung Ultrasound as a Rapid Triage Tool for Suspected Covid-19 Cases.

The novel coronavirus disease 2019 (Covid-19) outbreak began in China. The characteristic of the disease is development of pneumonia. We aimed to investigate the accuracy of bedside lung ultrasound (BLUS) for diagnosing Covid-19 pneumonia, and its effectiveness for the correct triage of patients with suspected Covid-19 in the emergency department (ED). This study was a prospective, cross-sectional cohort study. During their shifts, 3 accredited and certificated emergency physicians performed BLUS using BLUE protocol at the triage area of the ED on patients with suspected Covid-19. All of the patients underwent chest computed tomography. The BLUS findings were statistically compared with formal radiology reports of computed tomographies as the criterion standard for the diagnosis of Covid-19 pneumonia. Kolmogorov-Smirnov analysis, Shapiro-Wilk test, and Q-Q plots were performed with 95% confidence intervals (CIs) for statistical analysis. A total of 72 patients were included in the study. The sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of BLUS were 96.9% (95% CI, 84.2%-99.9%), 92.3% (95% CI, 79.1%-98.3%), 84.3% (95% CI, 64.5%-94.1%), 98.6% (95% CI, 91.1%-99.8%), and 93.7% (95% CI, 85.3%-98.0%), respectively. The positive and negative predictive values were 84.3% (95% CI, 64.5%-94.1%) and 98.6% (95% CI, 91.1%-99.8%), respectively. The area under curve was found to be 0.946 (95% CI, 0.866-0.986; P < 0.0001). Bedside lung ultrasound can be used to detect the presence of pulmonary involvement in suspected cases of Covid-19 for the effective triage of patients in the ED.

Interpretation of CT Scan Findings During the COVID-19 Pandemic

Studies have documented criteria for the prevention, diagnosis, and treatment of COVID-19 pneumonia as more information has become available about its symptoms and complications. Similar to other coronavirus-induced cases of pneumonia, COVID-19 pneumonia causes acute respiratory problems. The chest CT scan, which is easily available in almost all areas, is a common imaging technique for diagnosing pneumonia. Its findings, which are accompanied by high speed, quality, and accuracy, allow the radiologist to easily identify affected areas of the lungs and to determine typical radiological features of patients with pneumonia caused by COVID-19. These features include ground-glass opacity, multifocal patchy consolidation, and interstitial changes with the peripheral distribution. The highest incidence occurs in the 4th and 5th lobes, where about 50% to 75% of the lesions observed. For infected patients, the CT scan protocol includes administration of HRCT technique in the inspiration phase with spiral 4-slice devices and higher. Scan parameters also include KV: 100 - 120, and mAs: 20 - 30, thickness = 1 - 2 mm, spiral, single breath-hold, and Pitch = 0.8 - 1.5, which are determined for all patients. Since there are restrictions on using ionizing radiation for pregnant women, it is recommended to initially conduct PCR tests. If necessary, typical radiography with an abdominal shield can be used for women in the first trimester of pregnancy, and the HRCT technique in low doses can be used for those in the second and third trimesters.

COVID-19 Pneumonia: A Review of Typical Ct Findings and Differential Diagnosis

Pneumonia that is caused by the 2019 novel coronavirus (SARS-CoV-2, which is also referred to as 2019-nCoV recently did break out in Wuhan China has been coined the terminology of COVID-19. With the spread of the disease, similar cases of COVID-19 had been confirmed in various regions of the world. Because COVID-19 is a relatively new global disease, clinicians, and patients across the globe would initially not be conversant with the clinical features and radiology imaging characteristics of SARS-CoV-2 pneumonia. The causes of pneumonia are protein, many secondary to an underlying cardiorespiratory abnormality while some are related systemic disease. Various imaging techniques generally diagnose cases of Pneumonia. In the current climate, COVID-19 Pneumonia has taken center stage; confirmation relies upon microbiological studies such as real-time polymerase chain reaction or sequencing. These investigations are not usually available in an emergency setting. Computed Tomography (CT) can be used as an essential complement for the diagnosis of COVID-19 Pneumonia in the current epidemic context. But the later may be misleading as other cases of Pneumonia, and interstitial lung disease can easily be confused with COVID-19 Pneumonia. Also, Covid19 Pneumonia may be missed if not considered. The attention of clinicians should be alerted to the possibility of COVID-19 to conduct the appropriate tests to confirm or negate the diagnosis of COVID-19. In asymptomatic as well as in symptomatic patients that have COVID1-9 pneumonia, the initial COVID-19 nuclei acid test results could be normal, which upon subsequent repeat testing would become normal. Still, radiology imaging using a CT scan of thorax would tend to demonstrate various non-specific features that affect a variable number of lobes of the lungs, and these features quickly increase in size when a repeat CT scan of the thorax is undertaken. These findings tend to predate positive COVID-19 test results in some cases of COVID-19. The non-specific changes tend to resolve when the patient resolves from COVID-19 pneumonia. A catalog of radiology images that demonstrate various types of cardio-pulmonary lesions which when encountered by clinicians should alert them to exclude the possibility of COVID-19 Pneumonia has been included in the paper as an aid to alerting clinicians to have a high index of suspicion of radiology images of the thorax which should help them to quickly undertake appropriate tests to confirm or negate the diagnosis of COVID-19 pulmonary infection.

Characteristics of Chest CT Images in Patients With COVID-19 Pneumonia in London, UK.

Background and objectiveNovel coronavirus 2019 (COVID-19) outbreak was first reported in Wuhan, Hubei Province in China in December 2019; it has then spread quickly and exponentially beyond the Chinese borders and is now regarded as a global pandemic. We aimed to evaluate the chest CT radiological characteristics and lesion distribution patterns in patients of COVID-19 pneumonia in London, UK.MethodsWe performed a retrospective study and reviewed data of patients with clinically suspected COVID-19 who underwent chest CT between February 1 and May 5, 2020. All patients underwent the reverse transcription-polymerase chain reaction (RT-PCR) test. Lung lesion characteristics and distribution patterns were evaluated by two radiologists. Fisher’s exact test was used for statistical analysis, and a p-value of <0.05 was considered statistically significant.ResultsA total of 18 patients (nine men and nine women) were analyzed. All of them had bilateral patchy lesions in the chest CT images. There was no correlation between the severity score and mortality (p=0.790). The distinctive CT features included ground-glass opacity (GGO) and consolidative patchy amorphous lesions, bilateral posterior and peripheral multi-lobar lung involvement, pleural effusions, subpleural fibrotic lines, subpleural sparing, vascular engorgement, occasional crazy paving, occasional mediastinal lymphadenopathy, pleural thickening, lack of cavitation, and absence of reverse halo (atoll) signs.ConclusionCT can facilitate the diagnosis of COVID-19 pneumonia. Our UK cohort showed slight variations compared with previously reported Asian and continental European cases with respect to chest CT images.