Chest Computed Tomography Is an Efficient Method for Initial Diagnosis of COVID-19: An Observational Study.

Pitfalls in chest CT findings of COVID-19 patients infected during hospitalisation

To the Editor Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a recently pandemic beta-coronavirus, for which infection symptoms may vary from fever, dry cough, fatigue, and lymphopenia to viral pneumonia with acute respiratory distress syndrome (ARDS).1 Several studies have proven the greater sensitivity of chest computerized tomography (CT) compared to real-time reverse transcription polymerase chain reaction (RT-PCR) in identifying coronavirus disease 2019 (COVID-19) pneumonia; moreover, lung abnormalities may precede clinical manifestations, suggesting chest CT as a better screening test.2,3 Chest CT, however, has several limitations: it is invasive and expensive and requires patient transport to a health care facility; these characteristics could lead to a diagnostic delay, when clinical conditions may already be critical. Furthermore, the risk in transporting unstable hypoxemic patients, and associated nosocomial transmission, further limits chest CT utilization. The COVID-19 outbreak moves fast, and we need to organize and allocate resources while optimizing costs and time: identification of patients with pneumonia should be rapid and economic. Lung ultrasound (US) has already proven to be a reliable tool in diagnosing lung inflammatory processes4: the results are immediate and the examination is safe, repeatable, and cheap. Lung parenchymal alterations can be observed at the onset, and a disposable probe cover can ensure a clean procedure. Most notably, as opposed to CT imaging, US examinations are easily performed at the point of care, which can be the patient’s bedside or even outside the hospital. All these qualities make it a precious tool in clinical practice, optimal to assist clinicians even in initial patient triage. Early literature suggests that patients with confirmed COVID-19 pneumonia demonstrate typical lung imaging features, including pleural line irregularities, B lines, and multifocal consolidations.5 Early use of lung US could be valuable in COVID-19 patients, leading to early correct diagnoses and appropriate management. One particularly promising setting for this could be triage: in Italy, tents have been mounted outside the hospital as “field hospitals” to avoid contact between infected patients and noninfected ones. Providing every tent with an US scanner could permit early diagnosis outside the hospital, effectively implementing a “US triage.” A US-guided triage algorithm should be developed: one such proposal is shown in the Figure.Figure.: The ultrasound-guided triage algorithm. COVID-19 indicates coronavirus disease 2019; RT-PCR, reverse transcription polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; Spo 2, peripheral oxygen saturation; US, ultrasound.Limitations for the implementation of US triage are the lack of specific protocols and operator experience, which influences the validity of test results. Although the US triage has not yet been validated by prospective studies, it is a concept that needs prompt definition and investigation to improve our ability to decide which patients need hospitalization immediately when resources are limited and need to be conserved. Chiara Piliego, MDAlessandro Strumia, MDUnit of Anaesthesia, Intensive Care and Pain ManagementDepartment of MedicineUniversità Campus Bio-Medico di RomaRome, Italy[email protected] Michael Benjamin Stone, MDDepartment of Emergency MedicineLegacy Emanuel Medical CenterPortland, Oregon Giuseppe Pascarella, MDUnit of Anaesthesia, Intensive Care and Pain ManagementDepartment of MedicineUniversità Campus Bio-Medico di RomaRome, Italy

Systematic Screening of COVID-19 Disease Based on Chest CT and RT-PCR for Cancer Patients Undergoing Radiation Therapy in a Coronavirus French Hotspot

ObjectivesTo compare the performance of chest computed tomography (CT) scan versus reverse transcription polymerase chain reaction (RT-PCR) as the reference standard in the initial diagnostic assessment of coronavirus disease 2019 (COVID-19) patients.DesignA systematic review and meta-analysis were performed as per the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. A search of electronic information was conducted using the following databases: MEDLINE, EMBASE, EMCARE, CINAHL and the Cochrane Central Register of Controlled Trials.SettingStudies that compared the diagnostic performance within the same patient cohort of chest CT scan versus RT-PCR in COVID-19 suspected patients.ParticipantsThirteen non-randomised studies enrolling 4092 patients were identified.Main outcome measuresSensitivity, specificity and accuracy were primary outcome measures. Secondary outcomes included other test performance characteristics and discrepant findings between both investigations.ResultsChest CT had a median sensitivity, specificity and accuracy of 0.91 (range 0.82–0.98), 0.775 (0.25–1.00) and 0.87 (0.68–0.99), respectively, with RT-PCR as the reference. Importantly, early small, China-based studies tended to favour chest CT versus later larger, non-China studies.ConclusionsA relatively high false positive rate can be expected with chest CT. It is possible it may still be useful to provide circumstantial evidence, however, in some patients with a suspicious clinical presentation of COVID-19 and negative initial Severe Acute Respiratory Syndrome Coronavirus 2 RT-PCR tests, but more evidence is required in this context. In acute cardiorespiratory presentations, negative CT scan and RT-PCR tests is likely to be reassuring.

Background Detection of the viral nucleic acid is the cornerstone to diagnose the novel coronavirus disease 2019 (COVID-19). Due to the limited resources, the clinical and laboratory biomarkers will help in the early and differential diagnosis of severe acute respiratory syndrome coronavirus 2 infection and predict the prognosis of the disease. These findings in patients with pneumonia include fatigue, dry cough, low-grade fever, along with normal white blood cell count, decreased lymphocyte count, and high C-reactive protein (CRP) and D-dimer levels. Chest computed tomography (CT) severity score relies on the opacification of lungs as a proof for disease extension. Several studies have settled the importance of CT chest in the diagnosis and follow up of COVID-19 patients. Otherwise, many scientific societies have disclaimed the routine CT screening of these patients. Hence, it is important to correlate the CT severity score in positive PCR COVID-19 patients to their laboratory findings to minimize the need of frequent CT chest as a tool of follow-up. Patients and methods The study included 198 positive PCR for COVID-19 health-care workers including physicians, nurses, employees, and workers of Ain Shams University Hospitals, who sought medical advice at the Chest OPC or the ER triage or through teleconsultations. Patients underwent history taking, laboratory workup including complete blood count with differential, serum ferritin, CRP, D-dimer levels, and high-resolution CT chest. Results The study included 198 health-care workers including physicians, nurses, employees, and workers of Ain Shams University Hospitals with 106 of them being females and 92 males. The age range of the included patients is from 21 years up to 85 years. The cases were classified according to their CT severity score into normal CT chest with 47.5% of cases, mild CT findings representing 21.2%, 34 patients with moderate findings in CT, and those with severe score were 28 patients. A significant relation was found between the age and CT severity score with P value less than 0.001. The severity score was higher in cases with lower total leukocyte count and lymphocytes with significant relation and the P value was less than 0.001. The median CRP and ferritin level show a highly significant relation with the CT severity score. A highly significant relationship was found between severity score and D-dimer level of patients with a P value of less than 0.001. Conclusion This work sets a semiquantitative framework to assess and follow up the severity of COVID-19 disease. This score could be possibly used to facilitate the clinical triage of COVID-19 moderate to severe patients, requiring admission in hospitals in relation to laboratory findings. Also, it could be used to evaluate the severity of lung involvement in patients objectively and quickly. However, it was proposed that the use of laboratory results is of value in the follow up of the cases to limit the exposure to radiations.

The aim of this study was to study interreader agreement of the RSNA-STR-ACR (Radiological Society of North America/Society of Thoracic Radiology/American College of Radiology) consensus statement on reporting chest computed tomography (CT) findings related to COVID-19 on a sample of consecutive patients confirmed with reverse transcriptase-polymerase chain reaction (RT-PCR) for severe acute respiratory syndrome coronavirus 2. This institutional review board-approved retrospective study included 240 cases with a mean age of 47.6 ± 15.9 years, ranging from 20 to 90 years, who had a chest CT and RT-PCR performed. Computed tomography images were independently analyzed by 2 thoracic radiologists to identify patterns defined by the RSNA-STR-ACR consensus statement, and concordance was determined with weighted κ tests. Also, CT findings and CT severity scores were tabulated and compared. Of the 240 cases, 118 had findings on CT. The most frequent on the RT-PCR-positive group were areas of ground-glass opacities (80.5%), crazy-paving pattern (32.2%), and rounded pseudonodular ground-glass opacities (22.9%). Regarding the CT patterns, the most frequent in the RT-PCR-positive group was typical in 75.9%, followed by negative in 17.1%. The interreader agreement was 0.90 (95% confidence interval, 0.80-0.96) in this group. The CT severity score had a mean difference of -0.07 (95% confidence interval, -0.48 to 0.34) among the readers, showing no significant differences regarding visual estimation. The RSNA-STR-ACR consensus statement on reporting chest CT patterns for COVID-19 presents a high interreader agreement, with the typical pattern being more frequently associated with RT-PCR-positive examinations.

The value of early chest computed tomography (CT) was evaluated among severe community-acquired pneumonia (SCAP) patients. The study population consisted of 65 of 457 SCAP patients with concomitant chest CT and radiograph performed within 48 h of ICU admission. Each image pair was re-evaluated by two radiologists. The type of pneumonia, the presence of pleural fluid and atelectasis were assessed. Therapeutic and diagnostic procedures induced by CT results were analysed together with clinical, microbiological and outcome data. Alveolar pneumonia was observed in 72.3% of patients by radiograph and in 75.4% of patients by CT. Pleural fluid was detected via chest radiograph and CT in 17 (26.2%) and 41 cases (63.1%), (P < 0.001) and atelectasis in 10 (15.4%) and 22 cases (33.8%), (P = 0.002), respectively. In 34 patients (52.3%), the CT revealed 38 new findings (58.5%) not shown in plain chest radiograph. Out of these 34 patients, therapeutic interventions or procedures were performed in 26 (76.5%). The number of infected lobes correlated negatively with the lowest PaO2 /FiO2 ratio (ρ = -0.326, P = 0.008) for chest CT scans. Compared with chest radiograph, chest CT generated new findings in nearly 60% of SCAP patients, leading to new procedures or changes in medical treatment in nearly 75% of those patients. Chest CT better describes the pulmonary involvement and severity of oxygenation disorder compared to a plain chest radiograph.

Chest computed tomography (CT) can be used to monitor the course of the disease or response to therapy. Therefore, our study was designed to identify chest CT manifestations that can predict the outcome of patients on short term follow-up. This was a retrospective study wherein we reviewed chest CT scans of 112 real-time reverse transcription polymerase chain reaction positive patients admitted to our hospital. All 112 patients underwent follow-up chest CT at a time interval of 4 to 42 days. Our study included 83 male and 29 female who were positive for COVID 19 infection and admitted to the hospital with positive chest CT findings. All patients underwent follow-up chest CT, and the outcomes were categorized as resolution, regression, residual fibrosis, progression, or death. These proportions were 5.4%, 48.2%, 24.1%, 14.3%, and 8%, respectively. The only significant factor in determining the complete resolution of chest CT was oligo-segmental affection (P = .0001). The main CT feature that significantly affected the regression of chest CT manifestations was diffuse nodular shadows (P = .039). The CT features noted in patients with residual fibrosis were interstitial thickening, with a P value of .017. The mono-segmental process significantly affected progression (P = .044). The significant factors for fatality were diffuse crazy paving, pleural effusion, and extra-thoracic complications (P = .033, .029, and .007, respectively). The prognostic value of the first admission CT can help assess disease outcomes in the earliest phases of onset. This can improve resource distribution.

BackgroundIn patients with tracheobronchial involvement, the differential diagnosis between granulomatosis with polyangiitis (GPA) and relapsing polychondritis (RP) can be challenging. The aim of this study was to describe the characteristics of airway abnormalities on chest computed tomography (CT) in patients with GPA or RP and to determine whether specific imaging criteria could be used to differentiate them.MethodsGPA and RP patients with tracheobronchial involvement referred to a national referral center from 2008 to 2020 were evaluated. Their chest CT images were reviewed by two radiologists who were blinded to the final diagnosis in order to analyze the characteristics of airway involvement. The association between imaging features and a diagnosis of GPA rather than RP was analyzed using a generalized linear regression model.ResultsChest CTs from 26 GPA and 19 RP patients were analyzed. Involvement of the subglottic trachea (odds ratio for GPA=28.56 [95% CI: 3.17; 847.63]; P=0.001) and extensive airway involvement (odds ratio for GPA=0.02 [95% CI: 0.00; 0.43]; P=0.008) were the two independent CT features that differentiated GPA from RP in multivariate analysis. Tracheal thickening sparing the posterior membrane was significantly associated to RP (odds ratio for GPA=0.09 [95% CI: 0.02; 0.39]; P=0.003) but only in the univariate analysis and suffered from only moderate interobserver agreement (kappa=0.55). Tracheal calcifications were also associated with RP only in the univariate analysis (odds ratio for GPA=0.21 [95% CI: 0.05; 0.78]; P=0.045).ConclusionThe presence of subglottic involvement and diffuse airway involvement are the two most relevant criteria in differentiating between GPA and RP on chest CT. Although generally considered to be a highly suggestive sign of RP, posterior tracheal membrane sparing is a nonspecific and an overly subjective sign.

Understanding the significance of adipose tissue in the inflammatory response to COVID-19

OBJECTIVE:To investigate the relationship between lung lesion burden (LLB) found on chest computed tomography (CT) and 30-day mortality in hospitalized patients with high clinical suspicion of coronavirus disease 2019 (COVID-19), accounting for tomographic dynamic changes.METHODS:Patients hospitalized with high clinical suspicion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in a dedicated and reference hospital for COVID-19, having undergone at least one RT-PCR test, regardless of the result, and with one CT compatible with COVID-19, were retrospectively studied. Clinical and laboratory data upon admission were assessed, and LLB found on CT was semi-quantitatively evaluated through visual analysis. The primary outcome was 30-day mortality after admission. Secondary outcomes, including the intensive care unit (ICU) admission, mechanical ventilation used, and length of stay (LOS), were assessed.RESULTS:A total of 457 patients with a mean age of 57±15 years were included. Among these, 58% presented with positive RT-PCR result for COVID-19. The median time from symptom onset to RT-PCR was 8 days [interquartile range 6-11 days]. An initial LLB of ≥50% using CT was found in 201 patients (44%), which was associated with an increased crude at 30-day mortality (31% vs. 15% in patients with LLB of <50%, p<0.001). An LLB of ≥50% was also associated with an increase in the ICU admission, the need for mechanical ventilation, and a prolonged LOS after adjusting for baseline covariates and accounting for the CT findings as a time-varying covariate; hence, patients with an LLB of ≥50% remained at a higher risk at 30-day mortality (adjusted hazard ratio 2.17, 95% confidence interval 1.47-3.18, p<0.001).CONCLUSION:Even after accounting for dynamic CT changes in patients with both clinical and imaging findings consistent with COVID-19, an LLB of ≥50% might be associated with a higher risk of mortality.

Background: High resolution chest computed tomography (HRCT) is an established imaging modality that accurately assesses disease processes that are non-specific on conventional chest radiography. Chest Computed Tomography (CT) has proven invaluable in the evaluation of various diseases of the chest providing precise diagnosis that have great impact on the course of management. In this study, our aim is to evaluate the spectrum of radiological findings in all patients that had chest CTs at a tertiary health Institution in a developing Country. Method: This is a 6-year retrospective study of all patients that had Chest CT from 2009 till 2015. All patient data were retrieved and their Chest CT images reviewed and radiological findings and diagnosis documented. Results: Age range of patients was 1 - 84 years with a mean of 52.36 ± 22.9 years. Ten patients were children (12%). There were more males 53 (63.1%) than females 31 (36.9%) in the study. Referral for imaging was predominantly from internal medicine 33 (47.1%) and Surgery 27 (38.6%) departments. Most of the patients, 53 (63.1%) did not have previous chest radiographs. Consolidative changes were the most common parenchymal finding (77.4%). Few mediastinal masses were found in the study population. CT angiography constituted only 10.7% of all chest CTs done in adults. Conclusion: Few chest CT evaluations are performed compared to CTs of other parts of the body done in the same period. Chest CT is generally under-utilized even in a tertiary institution. There is a need to educate chest physicians on the role and advantages of CT use for the management of their patients.

.Purpose: Coronavirus disease 2019 (COVID-19) is a new infection that has spread worldwide and with no automatic model to reliably detect its presence from images. We aim to investigate the potential of deep transfer learning to predict COVID-19 infection using chest computed tomography (CT) and x-ray images.Approach: Regions of interest (ROI) corresponding to ground-glass opacities (GGO), consolidations, and pleural effusions were labeled in 100 axial lung CT images from 60 COVID-19-infected subjects. These segmented regions were then employed as an additional input to six deep convolutional neural network (CNN) architectures (AlexNet, DenseNet, GoogleNet, NASNet-Mobile, ResNet18, and DarkNet), pretrained on natural images, to differentiate between COVID-19 and normal CT images. We also explored the model’s ability to classify x-ray images as COVID-19, non-COVID-19 pneumonia, or normal. Performance on test images was measured with global accuracy and area under the receiver operating characteristic curve (AUC).Results: When using raw CT images as input to the tested models, the highest accuracy of 82% and AUC of 88.16% is achieved. Incorporating the three ROIs as an additional model inputs further boosts performance to an accuracy of 82.30% and an AUC of 90.10% (DarkNet). For x-ray images, we obtained an outstanding AUC of 97% for classifying COVID-19 versus normal versus other. Combing chest CT and x-ray images, DarkNet architecture achieves the highest accuracy of 99.09% and AUC of 99.89% in classifying COVID-19 from non-COVID-19. Our results confirm the ability of deep CNNs with transfer learning to predict COVID-19 in both chest CT and x-ray images.Conclusions: The proposed method could help radiologists increase the accuracy of their diagnosis and increase efficiency in COVID-19 management.

This study aimed to explore the diagnostic value of chest computed tomography (CT) based on adaptive statistical iterative reconstruction (ASiR) in the optimal weight range for children with community-acquired pneumonia (CAP) and find the differences between chest CT and ultrasound in the diagnosis of CAP. 106 children who were diagnosed as CAP were selected as the research objects. All objects underwent CT and ultrasound scans to measure the noise of CT images after iterative reconstruction and the contrast-to-noise ratio (CNR) of the thoracic aorta and the back muscles. The correlation between ASiR weight, noise, and CNR was analyzed and compared further. In addition, the differences in imaging manifestations of lung consolidation, abnormal pleural line, alveolar interstitial syndrome, and pleural effusion were observed under the ultrasound and CT scans of the patients. The sensitivity, specificity, positive predicted value (PV), and negative PV of the CT scan and ultrasound were analyzed further for the diagnosis of CAP in children. The results showed that ASiR weight and image noise were extremely and negatively correlated ( P &lt; 0.001 ) and that CNR and ASiR weight were extremely and positively correlated ( P &lt; 0.001 ). 40–60% of ASiR image noise was in the middle position, and the muscle space and subcutaneous fat in CT images were clearer when ASiR was at 40% and 60%. 60.38% of children were diagnosed as CAP. The proportions of children with lung consolidation, interstitial changes, pleural effusion, and atelectasis after ultrasound and CT examination were not greatly different ( P &gt; 0.05 ). After ASiR, the sensitivity of CT in detecting the abnormal pleural line + B-line/consolidation feature was the highest, 93.75%. The results of ultrasound diagnosis were consistent with those of chest CT diagnosis ( P &lt; 0.01 ). This indicated that the sensitivity, specificity, positive PV, and negative PV of ASiR-based chest CT in the diagnosis of CAP were close to those of ultrasound.

The early diagnosis of coronary artery disease (CAD) enables early intervention for the modifiable risk factors of the disease. Coronary artery calcification (CAC) detected incidentally on standard noncontrast chest computed tomography (CT) provides an opportunity for the early diagnosis of CAD. The purpose of this study was to demonstrate that CAC should be routinely reported when evaluating thoracic CT examinations. Routine reporting of CAC will contribute to the early diagnosis of CAD. The present study included 279 patients who underwent conventional coronary angiography (CAG) and CT within one month before undergoing CAG. The CAG and CT images of the patients were evaluated retrospectively. The levels of coronary artery stenosis were determined in reference to the CAG images. The CAC scores of the patients were calculated using the Weston method based on their chest CT images. The mean age of the patients was 63.2 ± 11.5 (range, 41-93) years, and 172 (61.6%) of them were men. The Weston score (WS) was 0 in 18.9% of the patients with obstructive CAD (OCAD), whereas it was ≥ 7 in 27.9% of patients. All patients with a WS of ≥ 7 had OCAD. All patients without luminal stenosis or < 50% stenosis had a WS of < 7. The CAC score is useful for the diagnosis of CAD and OCAD. If CAC is identified on standard noncontrast chest CT, it should be scored and reported accordingly. The WS can be used for CAC scoring.