Chest CT findings of coronavirus disease 2019 (COVID-19): A comprehensive meta-analysis of 9907 confirmed patients

ObjectivesWe performed a systematic review and meta-analysis of the prevalence of chest CT findings in patients with confirmed COVID-19 infection.MethodsSystematic review of the literature was performed using PubMed, Scopus, Embase, and Google Scholar to retrieve original studies on chest CT findings of patients with confirmed COVID-19, available up to 10 May 2020. Data on frequency and distribution of chest CT findings were extracted from eligible studies, pooled and meta-analyzed using random-effects model to calculate the prevalence of chest CT findings.ResultsOverall, 103 studies (pooled population: 9907 confirmed COVID-19 patients) were meta-analyzed. The most common CT findings were ground-glass opacities (GGOs) (77.18%, 95%CI = 72.23–81.47), reticulations (46.24%, 95%CI = 38.51–54.14), and air bronchogram (41.61%, 95%CI = 32.78–51.01). Pleural thickening (33.35%, 95%CI = 21.89–47.18) and bronchial wall thickening (15.48%, 95%CI = 8.54–26.43) were major atypical and airway findings. Lesions were predominantly distributed bilaterally (75.72%, 95%CI = 70.79–80.06) and peripherally (65.64%, 95%CI = 58.21–72.36), while 8.20% (95%CI = 6.30–10.61) of patients had no abnormal findings and pre-existing lung diseases were present in 6.01% (95%CI = 4.37–8.23).ConclusionsThe most common CT findings in COVID-19 are GGOs with/without consolidation, reticulations, and air bronchogram, which often involve both lungs with peripheral distribution. However, COVID-19 might present with atypical manifestations or no abnormal findings in chest CT, which deserve clinicians' notice.     

防控新型冠状病毒肺炎的主要做法和体会

根据上级针对新型冠状病毒肺炎疫情防控的统一部署,中国人民解放军总医院第六医学中心党委及全体工作人员能够做到“牢记使命、闻令而动、勇挑重担、敢打硬仗”,通过成立领导小组组织谋划中心防控工作以及通过成立专家组指导临床一线筛查工作;制定中心诊疗方案、门诊和住院收容管理规定、密切接触者管理方案、返京工作人员管理规定、医务人员个人防护要求等方案预案,从制度上约束防控工作;采取“守住前头、看住中心、管住后院”的工作方法,确保防控工作落地见效。疫情防控期间,接诊患者和医务人员“零感染”,发热门诊排查的病历无漏诊情况发生。     

The indispensable role of chest CT in the detection of coronavirus disease 2019 (COVID-19)

European Journal of Nuclear Medicine and Molecular Imaging -     

Novel coronavirus disease 2019 (COVID-19): relationship between chest CT scores and laboratory parameters

European Journal of Nuclear Medicine and Molecular Imaging - To quantify the severity of 2019 novel coronavirus disease (COVID-19) on chest CT and to determine its relationship with laboratory...     

Early prediction of severity in coronavirus disease (COVID-19) using quantitative CT imaging

PurposeTo evaluate whether the extent of COVID-19 pneumonia on CT scans using quantitative CT imaging obtained early in the illness can predict its future severity.MethodsWe conducted a retrospective single-center study on confirmed COVID-19 patients between January 18, 2020 and March 5, 2020. A quantitative AI algorithm was used to evaluate each patient's CT scan to determine the proportion of the lungs with pneumonia (VR) and the rate of change (RAR) in VR from scan to scan. Patients were classified as being in the severe or non-severe group based on their final symptoms. Penalized B-splines regression modeling was used to examine the relationship between mean VR and days from onset of symptoms in the two groups, with 95% and 99% confidence intervals.ResultsMedian VR max was 18.6% (IQR 9.1–32.7%) in 21 patients in the severe group, significantly higher (P < 0.0001) than in the 53 patients in non-severe group (1.8% (IQR 0.4–5.7%)). RAR was increasing with a median RAR of 2.1% (IQR 0.4–5.5%) in severe and 0.4% (IQR 0.1–0.9%) in non-severe group, which was significantly different (P < 0.0001). Penalized B-spline analyses showed positive relationships between VR and days from onset of symptom. The 95% confidence limits of the predicted means for the two groups diverged 5 days after the onset of initial symptoms with a threshold of 11.9%.ConclusionFive days after the initial onset of symptoms, CT could predict the patients who later developed severe symptoms with 95% confidence.     

CT-based radiomics for predicting the rapid progression of coronavirus disease 2019 (COVID-19) pneumonia lesions

Objectives:To develop and validate a radiomic model to predict the rapid progression (defined as volume growth of pneumonia lesions > 50% within seven days) in patients with coronavirus disease 2019 (COVID-19).Methods:Patients with laboratory-confirmed COVID-19 who underwent longitudinal chest CT between January 01 and February 18, 2020 were included. A total of 1316 radiomic features were extracted from the lung parenchyma window for each CT. The least absolute shrinkage and selection operator (LASSO), Relief, Las Vegas Wrapper (LVW), L1-norm-Support Vector Machine (L1-norm-SVM), and recursive feature elimination (RFE) were applied to select the features that associated with rapid progression. Four machine learning classifiers were used for modeling, including Support Vector Machine (SVM), Random Forest (RF), Logistic Regression (LR), and Decision Tree (DT). Accordingly, 20 radiomic models were developed on the basis of 296 CT scans and validated in 74 CT scans. Model performance was determined by the receiver operating characteristic curve.Results:A total of 107 patients (median age, 49.0 years, interquartile range, 35–54) were evaluated. The patients underwent a total of 370 chest CT scans with a median interval of 4 days (interquartile range, 3–5 days). The combination methods of L1-norm SVM and SVM with 17 radiomic features yielded the highest performance in predicting the likelihood of rapid progression of pneumonia lesions on next CT scan, with an AUC of 0.857 (95% CI: 0.766–0.947), sensitivity of 87.5%, and specificity of 70.7%.Conclusions:Our radiomic model based on longitudinal chest CT data could predict the rapid progression of pneumonia lesions, which may facilitate the CT follow-up intervals and reduce the radiation.Advances in knowledge:Radiomic features extracted from the current chest CT have potential in predicting the likelihood of rapid progression of pneumonia lesions on the next chest CT, which would improve clinical decision-making regarding timely treatment.     

Key elements of preparedness for pandemic coronavirus disease 2019 (COVID-19) in nuclear medicine units

European Journal of Nuclear Medicine and Molecular Imaging -     

Impact of coronavirus disease 2019 (COVID-19) outbreak on radiology research: An Italian survey

PurposeTo understand how COVID-19 pandemic has changed radiology research in Italy.MethodsA questionnaire (n = 19 questions) was sent to all members of the Italian Society of Radiology two months after the first Italian national lockdown was lifted.ResultsA total of 327 Italian radiologists took part in the survey (mean age: 49 ± 12 years). After national lockdown, the working-flow came back to normal in the vast majority of cases (285/327, 87.2%). Participants reported that a total of 462 radiological trials were recruiting patients at their institutions prior to COVID-19 outbreak, of which 332 (71.9%) were stopped during the emergency. On the other hand, 252 radiological trials have been started during the pandemic, of which 156 were non-COVID-19 trials (61.9%) and 96 were focused on COVID-19 patients (38.2%). The majority of radiologists surveyed (61.5%) do not conduct research. Of the radiologists who carried on research activities, participants reported a significant increase of the number of hours per week spent for research purposes during national lockdown (mean 4.5 ± 8.9 h during lockdown vs. 3.3 ± 6.8 h before lockdown; p = .046), followed by a significant drop after the lockdown was lifted (3.2 ± 6.5 h per week, p = .035). During national lockdown, 15.6% of participants started new review articles and completed old papers, 14.1% completed old works, and 8.9% started new review articles. Ninety-six surveyed radiologists (29.3%) declared to have submitted at least one article during COVID-19 emergency.ConclusionThis study shows the need to support radiology research in challenging scenarios like COVID-19 emergency.     

A review of neuroradiological abnormalities in patients with coronavirus disease 2019 (COVID-19)

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to various neurological manifestations. There is an urgent need for a summary of neuroimaging findings to accelerate diagnosis and treatment plans. We reviewed prospective and retrospective studies to classify neurological abnormalities observed in patients with the SARS-CoV-2 infection.MethodsThe relevant studies published in Scopus, PubMed and Clarivate Analytics databases were analysed. The search was performed for full-text articles published from 23 January 2020 to 23 February 2021.ResultsIn 23 studies the number of patients with SARS-CoV-2 infection was 20,850 and the number of patients with neurological manifestations was 1996 (9.5%). The total number of patients with neuroradiological abnormalities was 602 (2.8%). SARS-CoV-2 has led to various neuroimaging abnormalities which can be categorised by neuroanatomical localisation of lesions and their main probable underlying pathogenesis. Cranial nerve and spinal root abnormalities were cranial neuritis and polyradiculitis. Parenchymal abnormalities fell into four groups of: (a) thrombosis disorders, namely ischaemic stroke and sinus venous thrombosis; (b) endothelial dysfunction and damage disorders manifested as various types of intracranial haemorrhage and posterior reversible encephalopathy syndrome; (c) hypoxia/hypoperfusion disorders of leukoencephalopathy and watershed infarction; and (d) inflammatory disorders encompassing demyelinating disorders, encephalitis, vasculitis-like disorders, vasculopathy and cytotoxic lesions of the corpus callosum. Leptomeninges disorders included meningitis. Ischaemic stroke was the most frequent abnormality in these studies.ConclusionThe review study suggests that an anatomical approach to the classification of heterogeneous neuroimaging findings in patients with SARS-CoV-2 and neurological manifestations would lend itself well for use by practitioners in diagnosis and treatment planning.     

Chest CT imaging features and clinical outcome of coronavirus disease 2019 (COVID-19): A single-center case study in Ningbo,China

ObjectiveThe purpose of this study was to investigate the chest CT imaging features and clinical outcome of coronavirus disease 2019 (COVID-19) in Ningbo, China.MethodsIn this retrospective study, twenty-eight confirmed and seven highly suspected cases of COVID-19 were enrolled in Ningbo first hospital from January 26, 2020 to March 5, 2020. Cases were confirmed by real-time polymerase chain reaction (RT-PCR). The initial and follow-up chest CT imaging features, epidemiological history, and outcome were analyzed.ResultsThe average age of the patients was 57.3 ± 15.3 years (range: 27–96 years), including 25 females and 10 males. On CT images, 89.3% (25/28) confirmed and 100% (7/7) suspected patients had ground-glass opacities (GGOs), and GGOs with mixed consolidations were observed in 35.7% (10/28) confirmed and 42.9% (3/7) suspected cases, most of these lesions were distributed under the peripheral of both lungs. 17 confirmed and 4 suspected cases had a history of participating in Ningbo Tian-tong Temple rituals and all had GGOs in their lungs during the initial CT scan. As of March 25, 2020, the lung lesions of our cases were significantly resolved and all patients have been discharged from the hospital.ConclusionThe most common chest CT features are multiple bilateral and peripheral GGOs with mixed consolidations or not in the lungs of patients with COVID-19. Chest CT plays an important role in the diagnosis and monitoring treatment response of this disease. There was no reported death in our cases.     

Magnetic resonance imaging features of coronavirus disease 2019 (COVID-19) pneumonia: The first preliminary case series

Rationale and objectivesThere is a rising onus on understanding the common features of COVID-19 pneumonia on different imaging modalities. In this study, we aimed to review and depict the common MRI features of COVID-19 pneumonia in our laboratory confirmed case series, the first comprehensive reported cohort in the literature.Materials and methodsUpon IRB approval, eight laboratory confirmed COVID-19 patients who presented to our outpatient imaging clinic underwent chest CT and, once various features of COVID-19 pneumonia were identified, a dedicated multisequence chest MRI was performed on the same day with an institutional protocol. Demographic data and the morphology, laterality and location of the lesions were recorded for each case.ResultsFive males and three females with the mean age of 40.63 ± 12.64 years old were present in this case series. Five cases had typical CT features with ground glass opacities and consolidations, readily visible on different MRI sequences. Three cases had indeterminate or atypical features which were also easily seen on MRI. The comprehensive review of MRI features for each case and representative images have been illustrated.ConclusionBecoming familiar with typical findings of COVID-19 pneumonia in MRI is crucial for every radiologist. Although MRI is not the modality of choice for evaluation of pulmonary opacities, it has similar capabilities in detection of COVID-19 pneumonia when compared to chest CT.     

介入医务工作者应对新型冠状病毒感染防控专家共识

2019年12月以来,我国爆发新型冠状病毒肺炎(COVID-19)疫情。疫情期间大量患者需要介入手术治疗,存在院内感染隐患,也给疫情防控带来挑战。如何在开展介入手术的同时做好防控工作,对预防院内感染至关重要。为了进一步规范介入医务工作者的医疗行为,做好患者救治和疫情防控工作,中国医师协会介入医师分会组织人员起草了本专家共识。本共识在"疫情防控为重,严防院内感染"的前提下,结合属地突发公共卫生事件等级,对患者进行分类管理,指导介入医务工作者在COVID-19疫情期间安全地开展各类介入手术,同时针对COVID-19疫情期间手术室、门诊和会诊的防控管理,以及教学和科研等方面提出了建议。希望指导介入医务工作者在抗击COVID-19疫情的同时,做好自身的防护,更好地服务患者。     

新型冠状病毒肺炎胸部CT表现特征

目的 探讨新冠状病毒肺炎胸部CT表现特征.方法 对54例新型冠状病毒确诊患者进行胸部CT扫描,观察胸部CT影像表现,并进行统计学分析处理.结果 病灶呈磨玻璃样密度影38例(70.37％),网格状阴影16例(29.63％),实变10例(18.52％),纤维索条灶15例(27.78％),支气管壁增厚伴支扩11例(20.37...