Background: At present, the diagnosis of COVID-19 depends on real-time reverse transcriptase polymerase chain reaction (RT-PCT). On imaging, computed tomography (CT) manifestations resemble those seen in viral pneumonias, with multifocal ground-glass opacities and consolidation in a peripheral distribution being the most common findings. Although these findings lack specificity for COVID-19 diagnosis on imaging grounds, CT could be used to provide objective assessment about the extension of the lung opacities, which could be used as an imaging surrogate for disease burden. Chest CT scan may be helpful in early diagnosing of COVID-19. Objective: The current study investigated the diagnostic accuracy and false-positive rate of chest CT in detecting COVID-19 pneumoniain a population with clinical suspicion using RT-PCR testing as reference standard. Materials and Methods: In this prospective single centerstudy performed on 612 cases with clinical suspicion of COVID-19, all adult symptomatic ED patients had both a CT scan and a PCR upon arrival at the hospital. CT results were compared with PCR test (s) and diagnostic accuracy was calculated. Results: Between February 15, 2020 to July 15, 2020, 612 symptomatic ED patients were included. In total, 78.5% of patients had a positive PCR and 82.8% a positive CT, resulting in a sensitivity of 94.2%, specificity 76.4%, likelihood ratio (LR) + 2.94 and (LR) - 0.18.The PPV was 76.7% and NPV 94.1%. The sensitivity of the CT tended to be higher (100.0%) in those with severe risk pneumonia than in patients with low/medium risk pneumonia (90.3%, P = 0.42). In patients with sepsis, sensitivity was significantly higher than in those without sepsis (99.5 vs. 63.5%, P < 0.001). The diagnostic ability of chest CT was found to be rather high with 92.1%, concordance rate between findings of CT and PCR. In 48 (7.8%) patients discordant findings between CT and PCR were observed. The positive predictive values (PPV) and accuracy of chest CT in diagnosing COVID-19 were higher in patients ≥60 years than that in patients <60 years (P = 0.001 and 0.004, respectively). The specificity and NPV of chest CT in diagnosing COVID-19 were greater for women than that for men (P = 0.007 and 0.03, respectively); and no difference existed for sensitivity, PPV and accuracy (P = 0.43, 0.69 and 0.31, respectively). In most cases, the CT scan was considered suspicious for COVID-19, while the PCR was negative (37/48, 70.8%). In the majority of these, the diagnosis at discharge was pulmonary infection (n = 26; 74.3%). The current study included repeated PCRs and explored discordant test results, which showed that in about 45.9% of patients with false-positive CT scans, other viral pathogens were detected. The false-positive rate of CT findings in the diagnosis of COVID-19 pneumonia was 7.2%.Conclusion: High diagnostic accuracy of chest CT findings with typical and relatively atypical CT manifestations of COVID-19 leads to a low rate of missed diagnosis. Normal chest CT can be found in RT-PCR positive COVID-19 cases, and typical CT manifestations can be found in RT-PCR negative cases. Therefore, a combination of both CT and RT-PCR for future follow-up, management and medical surveillance is recommended considering the false-positive results of chest CT in the diagnosis of COVID-19 pneumonia.

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Aim: To describe the distribution of lung patterns determined by High Resolution Computed Tomography (HRCT) in COVID patients with mild and moderate lung involvement and outcomes after early identification and management with steroids and anticoagulants. Material and Methods: A cross sectional study of COVID-19 patients with mild and moderate lung involvement presenting at 5 healthcare centres in Trichy district of South TamilNadu in India. Patients underwent HRCT to assess patterns and severity of lung involvement, Inflammatory markers (LDH/Ferritin) and D-Dimer assay and clinical correlation with signs and symptoms. Patients were assessed for oxygen, steroid and anticoagulant therapy, clinical recovery or progression on follow up and details on mortality were collected. The RSNA, Fleischer Society guidelines and CORADS score was used for radiological reporting. New potential classification of patterns of percentage of lung parenchyma involvement in Covid patients is being suggested. Results: The study included 7,340 patients with suspected COVID and 3,963 (53.9%) patients had lung involvement based on HRCT. RT PCR was positive in 74.1% of the CT Positive cases. Crazy Pavement pattern was predominant (n = 2022, 51.0%) and Ground Glass Opacity (GGO) was found in 1,941 (49.0%) patients in the study. Severe lung involvement was more common in the Crazy Pavement pattern. Patients with GGO in moderate lung involvement were significantly more likely to recover faster compared to Crazy Pavement pattern (P value <0.001). Conclusion: HRCT chest and assessment of lung patterns can help triage patients to home quarantine and hospital admission. Early initiation of steroids and anticoagulants based on lung patterns can prevent progression to more severe stages and aid early recovery. HRCT can play a major role to triage and guide management especially as RT PCR testing and results are delayed for the benefit of patients and in a social cause to decrease the spread of the virus

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While the COVID-19 pandemics seem to be crippling the global health care system, it has caused enormous uncertainty and panic in the lives of the health care professionals with a significant impact on their productivity. A significant proportion of these affected health care individuals comprise of the working staff belonging to the Radiology department. Although the main focus of all health care individuals has constantly been to reduce the number of new cases by minimal transmission, save lives of the infected patients by findings effective cure and carry out meticulous research to develop preventive vaccine, we have been unknowingly giving very little consideration to critical issues relating to the psychological well-being of the front liners. It is of utmost necessity that the psychological impact of this pandemic needs to be recognized and dealt with, in a timely fashion. While planning interventions to fight the pandemic, mental health issues must not be sidelined instead considered pragmatically. The radiology departments must come up with a mitigation plan to combat the subsequent short-term and long-term adverse effects of COVID-19 on mental well-being of their staff members. This article discusses the psychological impact of COVID-19 on the radiology department.

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The COVID-19 pandemic has necessitated rapid testing and diagnosis to manage its spread. While reverse transcriptase polymerase chain reaction (RT-PCR) is being used as the gold standard method to diagnose COVID-19, many scientists and doctors have pointed out some challenges related to the variability, accuracy, and affordability of this technique. At the same time, radiological methods, which were being used to diagnose COVID-19 in the early phase of the pandemic in China, were sidelined by many primarily due to their low specificity and the difficulty in conducting a differential diagnosis. However, the utility of radiological methods cannot be neglected. Indeed, over the past few months, healthcare consultants and radiologists in India have been using or advising the use of high-resolution computed tomography (HRCT) of the chest for early diagnosis and tracking of COVID-19, particularly in preoperative and asymptomatic patients. At the same time, scientists have been trying to improve upon the radiological method of COVID-19 diagnosis and monitoring by using artificial intelligence (AI)-based interpretation models. This review is an effort to compile and compare such efforts. To this end, the latest scientific literature on the use of radiology and AI-assisted radiology for the diagnosis and monitoring of COVID-19 has been reviewed and presented, highlighting the strengths and limitations of such techniques.

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Aim: In this study, we aim to evaluate the perception and practice of IPC measures by Radiologists during pre-COVID and present COVID times, while conducting a thorough review of current concepts and literature, to provide a standard operating procedure (SOP) for radiology operations. Methods: This study was conducted by Department of Radiodiagnosis and Imaging, Kasturba Medical College, MAHE, Mangalore. After obtaining approval from the institutional ethics committee, and other required permissions, the Google form questionnaire was sent to 350 Radiologists via email and text during the period of May 2020. Data was collected by time-based sampling in the period of fifteen days during the end of the total lockdown time. Results: 54% (n = 152) reported never attending a training session on (Infection Prevention & Control) IPC prior to the COVID-19 outbreak. The perception regarding IPC were found to be good among radiologists as majority of the respondents were correctly able to answer questions regarding IPC. 86% (n = 152) of the respondents believed that their knowledge on IPC has improved during the COVID-19 pandemic. However, it was revealed that majority of the respondents only started to practice appropriate contact and droplet / procedural precautions only after the COVID-19 outbreak. Conclusion: The present COVID-19 scenario coupled with the lack of knowledge and training regarding IPC amongst radiologists evident from the results of our survey, highlights the need for proper training and establishing standard operating procedures and best practices in IPC pertinent to modern radiology practice

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Background: Whether the sensitivity of Deep Learning (DL) models to screen chest radiographs (CXR) for CoVID-19 can approximate that of radiologists, so that they can be adopted and used if real-time review of CXRs by radiologists is not possible, has not been explored before. Objective: To evaluate the diagnostic performance of a doctor-trained DL model (Svita_DL8) to screen for COVID-19 on CXR, and to compare the performance of the DL model with that of expert radiologists. Materials and Methods: We used a pre-trained convolutional neural network to develop a publicly available online DL model to evaluate CXR examinations saved in .jpeg or .png format. The initial model was subsequently curated and trained by an internist and a radiologist using 1062 chest radiographs to classify a submitted CXR as either normal, COVID-19, or a non-COVID-19 abnormal. For validation, we collected a separate set of 430 CXR examinations from numerous publicly available datasets from 10 different countries, case presentations, and two hospital repositories. These examinations were assessed for COVID-19 by the DL model and by two independent radiologists. Diagnostic performance was compared between the model and the radiologists and the correlation coefficient calculated. Results: For detecting COVID-19 on CXR, our DL model demonstrated sensitivity of 91.5%, specificity of 55.3%, PPV 60.9%, NPV 77.9%, accuracy 70.1%, and AUC 0.73 (95% CI: 0.86, 0.95). There was a significant correlation (r = 0.617, P = 0.000) between the results of the DL model and the radiologists' interpretations. The sensitivity of the radiologists is 96% and their overall diagnostic accuracy is 90% in this study. Conclusions: The DL model demonstrated high sensitivity for detecting COVID-19 on CXR. Clinical Impact: The doctor trained DL tool Svita_DL8 can be used in resource-constrained settings to quickly triage patients with suspected COVID-19 for further in-depth review and testing.

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Corona virus disease 2019 (COVID-19) is caused by severe acute respiratory coronavirus 2 (SARS-CoV-2) and has been declared as pandemic. Its transmission is mainly by droplets and touching infected surfaces. Health care workers including personnel working at diagnostic centers are more prone to contact the disease through infected patients and hence various precautionary measures have to be implemented which has been discussed in this article. This manuscript shall brief about the preparedness by the diagnostic center in terms of the modification in the work flow, the precautions and protections to be taken by the personnel and patients, disinfection of the equipment and surfaces, and new norms of social distancing. This article will be addressing mainly to the diagnostic centers and the changes to be made as per their convenience.

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Background: With COVID-19 cases rising, despite CT chest being of value in diagnosis and prognostication in COVID-19, its role in mild or asymptomatic suspected COVID-19, before RT-PCR test is lacking. Method: This is a retrospective observational study involving asymptomatic or mildly symptomatic clinically suspected COVID-19 infection in a high endemicity area. Of 2532 HRCT chest database, 376 eligible cases were analyzed for clinico-radiological correlation for CT findings based CORADS and CT severity score between positive vs negative group. Results: Of 376, 186 (48.46%) had COVID-19 features on HRCT in mild and asymptomatic suspected patients. 98 (26.06%) had CO-RARDS - 5, 88 (23.40%) had CO-RADS - 4. 48 (12.76%), 128 (34.04%), 14 (3.72%) had CO-RADS score of 3,2,1, respectively. Positive CT findings were more likely beyond 3 days of symptoms compared to those presenting earlier {days: (Mean) 4.2 vs 2.76} Positive CT was significantly associated with patients with anosmia and dyspnea. The common presenting symptoms were Fever 196 (52.12%) and followed by sore throat in 173 (46.01%). The common HRCT findings were Ground glass opacity (GGO) (74.60%), followed by Lymphadenopathy (LN) (27.92%). LN which was more prevalent in symptomatic patients {99/343 (28.86%) vs {6/33 (18.18%)} asymptomatics (P: 0.04)}. Consolidation was significantly more in asymptomatics with COPD (P: 0.004). 6 (3.22%) patients had CT score >17/25. Conclusion: Chest HRCT picked 48.46% positive cases in mildly symptomatic and asymptomatic patients of which 3.22% had severe involvement (>17). Being a noninvasive, rapid, sensitive, low risk of cross infection with high reproducibility, chest CT is worth evaluating as screening modality even in asymptomatic and mildly symptomatic clinically suspected COVID-19.

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The COVID-19 pandemic has affected every sector of healthcare. Interventional Radiology in many instances continues to provide frontline care during this pandemic. The purpose of this article is to assist Interventional Radiologists in their preparation to face the challenges, by summarizing global experiences and guidelines. We provide a basic framework that can be used to prepare institue specific guidelines in coordination with multidisciplinary teams and hospital administration.

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Background: Early detection is the key to contain the ongoing pandemic. The current gold standard to detect SARS CoV2 is RT-PCR. However, it has a high false negative rate and long turnaround time. Purpose: In view of the high sensitivity of CT in detection of lower respiratory tract pathologies, a study of 2581 patients comparing RT-PCR status with CT findings was undertaken to see if it augments the diagnostic performance. Materials and Methods: A multi centre prospective study of consecutive cases was conducted. All CT studies suggestive of COVID 19 pneumonia were collated and evaluated independently by three Radiologists to confirm the imaging diagnosis of COVID-19 pneumonia. The RT-PCR values were retrospectively obtained, based on the RT-PCR values, CT studies were categorised into three subgroups, positive, negative and unknown. CT features from all three groups were compared to evaluate any communality or discordance. Results: Out of the 2581 patients with positive CT findings for COVID pneumonia, 825 were females and 1,756 were males in a wide age group of 28-90 years. Predominant CT features observed in all the subgroups were Ground glass densities 94.8%, in mixed distribution (peripheral and central) (59.12%), posterior segments in 92% and multilobar involvement in 70.9%. The CT features across the three subgroups were statistically significant with a P value <0.001. Conclusion: There was a communality of CT findings regardless of RT-PCR status. In a pandemic setting ground glass densities in a subpleural, posterior and basal distribution are indicative of COVID 19. Thus CT chest in conjunction to RT PCR augments the diagnosis of COVID 19 pneumonia; utilization of CT chest may just be the missing link in closing this pandemic.

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Context: Since its outbreak, the COVID-19 pneumonia pandemic is rapidly spreading across India; although computed tomography of chest (CT chest) is not recommended as a screening tool, there is a rapid surge in the CT chest performed in suspected cases. We should be aware of the imaging features among the Indian population. Aim: To analyze the CT chest features in Indian COVID-19 patients. Settings and Design: Retrospective study. Subjects and Methods: CT chest of 31 polymerase chain reaction (PCR) verified patients of COVID-19 was assessed for ground-glass opacities (GGO), consolidations, bronchiectasis, pleural effusions, vascular enlargement, crazy paving, and reverse halo sign. Statistical Analysis Used: The data was analyzed in Microsoft Excel 2019. Results: Only one patient showed a normal scan. Multilobar involvements with parenchymal abnormalities were seen in all the patients with bilateral involvement in 74.1%. 42.5% of the lung parenchymal abnormalities were pure GGOs, while 41.6% had GGOs mixed with consolidation. Peripheral and posterior lung field involvement was seen in 70.5% and 65.5%, respectively; 56.8% had well-defined margins. Pure GGOs were seen in all six patients, who underwent CT in the first 2 days of onset of symptoms. Seventeen patients scanned between 3 and 6 days of the illness showed GGOs mixed with consolidation and pure consolidations 76%. Vascular enlargement, crazy paving, and reverse halo sign were seen in 70%, 53%, and 35% of the patients, respectively. Patients scanned after 1 week of symptoms showed traction bronchiectasis along with GGOs and or consolidations. Conclusions: COVID-19 pneumonia showed multifocal predominantly subpleural basal posteriorly located GGOs and/or consolidations which were predominantly well defined. “Crazy paving” was prevailing in the intermediate stage while early traction bronchiectasis among the patients presented later in the course of illness.

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Coronavirus disease 2019 (COVID-19) is caused due to infection by severe acute respiratory syndrome virus coronavirus 2 (SARS-CoV-2). It is highly infective virus resulting in recent on-going pandemic and causing multisystem involvement predominantly affecting respiratory system. The most common presenting symptoms are fever, dry cough and breathlessness. The role of Computerized tomography (CT) is crucial especially in those patient having negative (rRT-PCR) but with high clinical suspicion, for prognosis and follow up. CT imaging findings mainly consists of multiple patchy bilateral ground-glass opacity (GGO) with or without consolidation and interlobular septal thickening with a peripheral or posterior distribution, mainly involving the lower lobes, depending upon the stage of disease. We present two case report of high CT severity score COVID-19 infection on non-invasive ventilation (NIV) having rare complication of pneumomediastinum and subcutaneous emphysema apart from typical COVID pattern lung findings during their course of admission in the hospital.

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Context: CT scan is a quick and effective method to triage patients in the Covid-19 pandemic to prevent the heathcare facilities from getting overwhelmed. Aims: To find whether an initial HRCT chest can help triage patient by determining their oxygen requirement, place of treatment, laboratory parameters and risk of mortality and to compare 3 CT scoring systems (0-20, 0-25 and percentage of involved lung models) to find if one is a better predictor of prognosis than the other. Settings and Design: This was a prospective observational study conducted at a Tertiary care hospital in Mumbai, Patients undergoing CT scan were included by complete enumeration method. Methods and Material: Data collected included demographics, days from swab positivity to CT scan, comorbidities, place of treatment, laboratory parameters, oxygen requirement and mortality. We divided the patients into mild, moderate and severe based on 3 criteria - 20 point CT score (OS1), 25 point CT score (OS2) and opacity percentage (OP). CT scans were analysed using CT pneumonia analysis prototype software (Siemens Healthcare version 2.5.2, Erlangen, Germany). Statistical Analysis: ROC curve and Youden's index were used to determine cut off points. Multinomial logistic regression used to study the relations with oxygen requirement and place of admission. Hosmer-Lemeshow test was done to test the goodness of fit of our models. Results: A total of 740 patients were included in our study. All the 3 scoring systems showed a significant positive correlation with oxygen requirement, place of admission and death. Based on ROC analysis a score of 4 for OS1, 9 for OS2 and 12.7% for OP was determined as the cut off for oxygen requirement. Conclusions: CT severity scoring using an automated deep learning software programme is a boon for determining oxygen requirement and triage. As the score increases, the chances of requirement of higher oxygen and intubation increase. All the three scoring systems are predictive of oxygen requirement.

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In December 2019, an unprecedented outbreak of pneumonia of unknown etiology emerged called COVID-19. A vast number of people affected by this disease are asymptomatic and yet contagious with up to 79% of COVID-19 infections reportedly caused by undocumented infections. Surprisingly, these asymptomatic subjects are also known to quietly harbor pneumonia changes on CT scans. RT-PCR, the definitive test for COVID-19, maybe false negative in patients with COVID-19 pneumonia on CT. Incidental findings highly suspicious of COVID-19 pneumonia on CT chest of asymptomatic patients may increase as the community transmission of the virus rises and isolation restrictions are released. It is advisable to be aware of its appearances and the challenges associated with it.

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Background: Chest radiography (CXR) is a widely available baseline radiological modality in evaluating symptomatic patients with suspected or confirmed Covid-19 disease. Serial changes can help in monitoring the patients in conjunction with the clinical status of these patients in a hospital setting. Purpose: The purpose of this study was to analyse the patterns of radiological findings on chest radiograph (CXR) for suspected and confirmed COVID-19 patients on initial presentation to the emergency medical services (EMS) on admission and to assess the progression and resolution. Materials and Methods: In this study, patients who presented to EMS of a multispeciality hospital as suspected or confirmed Covid-19 on consecutive reverse transcriptase polymerase chain reaction (RT-PCR). CXR was examined for findings of haziness, patterns and distribution of opacities. Progression and regression of findings in serial CXR were studied and evaluated with the clinical and laboratory parameters. High resolution CT (HRCT) chest was performed initially for some patients. Results: 756 RT-PCR confirmed COVID-19 patients were included in our study who had initial CXR. 510 (67.46%) of our patients with positive initial RT-PCR showed abnormal baseline CXR. The abnormal findings were described as haziness akin to ground glass opacities (GGO) on CT, peripheral opacities, patchy parenchymal opacities and consolidation. Peripheral opacities and lower zone distribution were the commonest pattern of CXR abnormalities with bilateral involvement. The severity of findings on serial CXR and radiographic regression was studied along with follow-up to assess response to treatment. Forty-six patients showed features of acute lung injury (ALI). Complications and new CXR findings were reported for patients who were given ventilator support. Conclusion: CXR is a valuable baseline radiological investigation on hospital admission in symptomatic patients with suspected or confirmed Covid-19 presenting to the EMS as it helps to monitor the progress and regression of the disease in conjunction with clinical findings.

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Coronavirus disease (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is an enveloped single-stranded RNA virus belonging to the family of betacoronaviruses. Chest computed tomography (CT) has helped us in understanding this new disease. Typical CT features of COVID-19 pneumonia are ground-glass opacities (GGO), crazy paving pattern and GGO with superimposed consolidation with a basal, posterior and peripheral lung predilection. Less commonly bronchial wall thickening, bronchial dilatation and pleural thickening are seen. Presence of pleural effusion, pericardial effusion and mediastinal lymphadenopathy is seen in severe cases. Reticulations, fibrous stripes, reverse halo sign and perilobular opacities are seen late (>2 weeks) in the course of illness. We aim to present a pictorial review of CT imaging findings in COVID-19 to illustrate the typical and atypical manifestations of this disease in a bid to familiarize radiologists with the myriad imaging manifestations of this disease.

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Context: As the burden of COVID-19 enhances, the need of a fast and reliable screening method is imperative. Chest radiographs plays a pivotal role in rapidly triaging the patients. Unfortunately, in low-resource settings, there is a scarcity of trained radiologists. Aim: This study evaluates and compares the performance of an artificial intelligence (AI) system with a radiologist in detecting chest radiograph findings due to COVID-19. Subjects and Methods: The test set consisted of 457 CXR images of patients with suspected COVID-19 pneumonia over a period of three months. The radiographs were evaluated by a radiologist with experience of more than 13 years and by the AI system (NeuraCovid, a web application that pairs with the AI model COVID-NET). Performance of AI system and the radiologist were compared by calculating the sensitivity, specificity and generating a receiver operating characteristic curve. RT-PCR test results were used as the gold standard. Results: The radiologist obtained a sensitivity and specificity of 44.1% and 92.5%, respectively, whereas the AI had a sensitivity and specificity of 41.6% and 60%, respectively. The area under curve for correctly classifying CXR images as COVID-19 pneumonia was 0.48 for the AI system and 0.68 for the radiologist. The radiologist's prediction was found to be superior to that of the AI with a P VALUE of 0.005. Conclusion: The specificity and sensitivity of detecting lung involvement in COVID-19, by the radiologist, was found to be superior to that by the AI system.

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Context: Corona virus disease (COVID-19) has spread in a rampant manner all over the World causing severe acute respiratory illness. Prompt recognition of disease is invaluable to ensure timely treatment, and rapid patient isolation is crucial for containment of this communicable disease. Aims: To evaluate the performance of high resolution CT (HRCT) in the diagnosis of COVID-19. To establish the role of HRCT in prognosis of affected patients and to assess severity of disease based on HRCT findings. Settings and Design: This retrospective study included 216 patients admitted to our institute with a diagnosis of COVID-19 infection confirmed by nucleic acid RT-PCR testing. Subjects and Methods: Patients underwent non contrast HRCT chest examination and images were reconstructed in thin 1.25 mm lung window. Images were evaluated for presence of lung lesions & CT severity score was assigned to each patient based on number of lung lobes involved. Results: Ground-glass opacities (GGOs) with or without consolidation, interlobular septal thickening, the “reversed halo” sign (Atoll sign) and GGO's with rounded nodular pattern are common CT features of COVID-19 Conclusions: Typical peripheral subpleural distributions of GGO's with bilateral asymmetrical lung involvement are characteristic features of COVID19 pneumonia. Chest HRCT can be a very useful and standard imaging method to assess the severity and progression of the disease and thereby optimizing the management of patients. With increasing case load all over the world HRCT can be used as a one stop radiological investigation for the diagnosis and prognosis of corona virus disease.

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Objective: To analyze radiological changes in portable chest radiographs in coronavirus disease-19(COVID-19) patients to optimize the management of hospitalized patients. Methods: We retrospectively reviewed 638 portable radiographs of 422 hospitalized COVID-19 patients with RT-PCR confirmed COVID-19 infection. All the radiographs were reported in a structured format by two experienced radiologists. A severity score was assigned to every Chest Xray (CXR) and correlation was done with the CT scans whenever available. Results: Out of 422 baseline portable radiographs assessed, ^the ratio of male: female patients was 337:85 that is 79.8% were males and 20.14% were females.The mean age was 50.5 years and the range was 17–84 years.Of these 422 patients, 187 patients (44.3%) had abnormal baseline CXR. 161 out of 187 (86%) had either typical or indeterminate findings for COVID-19 pneumonia, rest 26 (13.9%) patients had CXR findings not consistent with COVID-19, like pleural effusion, hydropneumothorax, or lung cavity.Most commonly observed CXR findings in COVID 19 pneumonia were bilateral, multifocal air space opacities (consolidation and ground-glass opacities) predominantly involving lower zones and peripheral lung fields. X-ray identifiable lung changes of COVID-19 were mostly seen at 9-11 days after symptom onset. Conclusion: The presence of multifocal air-space opacities with bilateral, peripheral distribution on chest radiograph is highly suggestive of COVID-19 pneumonia in this pandemic setting.Portable chest radiography is a widely available and quicktool for estimating the evolution and assessing the severity of lung involvement of COVID-19 pneumonia in hospitalized symptomatic patients.

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The COVID-19 pandemic will have serious financial effects on the healthcare sector business. There will be significant short-term and long-term effects of this on Radiology services throughout the country. Various social distancing measures undertaken by the government will bring larger economic hurdles with them. An attempt to achieve COVID-19 preparedness by hospitals has led to a significant decline in patient footfall and in turn imaging volumes. Despite relief measures provided by the government like providing a moratorium on EMIs of all outstanding loans for a specified period and allocating funds toward reinforcing healthcare infrastructure, the effects of this pandemic will leave the radiology business in a crippled state, in the foreseeable future. Radiology practices have seen a significant impact on business to the extent of almost 60%–70% reduction in imaging volumes and this will be the case for the next few months to come. Administrators and radiologists should proactively take measures to device strategies and plans to tide over this crisis. Eventually, this pandemic will end, and life will have a “New Normal.” Medical aid that is being deferred today will be sought out later. Alternate means of reporting like teleradiology and artificial intelligence should be strongly pursued and providing education regarding these to their staff and the younger generation of radiologists should be of prime concern.

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Context: As a response to the CoronaVirus Disease 2019 (COVID-19) pandemic, India announced a nation-wide lockdown effective from March 25, 2020. Recent media reports and published studies from Western countries indicate a decrease in patients presenting to hospitals with stroke, acute coronary syndromes, and other emergencies. Aims: The purpose of this study was to assess the impact of the lockdown on the number of patients undergoing Computed Tomography (CT) in a public tertiary care hospital in India, and thus indirectly assess the effect of the lockdown on medical conditions other than COVID-19. Settings and Design: Retrospective observational study. Materials and Methods: Analysis of the CT reports from the hospital's PACS for the first three months of lockdown was performed and compared with those of the month prior to the imposition of the lockdown. Statistical Analysis Used: Frequency tables and percentages were calculated. Results: There was a 70% decrease in the number of total CTs in the first three months of lockdown compared to the month prior to lockdown. There was a decrease in CTs performed for various conditions such as tuberculosis follow up (decreased by 98%), brain infarcts, nontraumatic intracranial hemorrhage (decreased by 40%), and baseline CTs for neoplasms (decreased by 73%). CTs for trauma also decreased by 64% with a decrease in patients involved in road traffic accidents undergoing CT. Conclusion: Our study highlights the impact of the lockdown on medical conditions other than COVID-19 in India, with a substantial decrease in the number of patients undergoing CTs for a variety of conditions.

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Background: Due to the relative early lockdown in India, relative greater availability of reverse transcription polymerase chain reaction (RT-PCR) testing, and mandate to admit all positive corona virus disease 2019 (COVID-19) patients, the protocol in our hospital is to perform a baseline chest X-ray (CXR) at the time of admission and for follow up. There are currently limited publications demonstrating the radiographic findings and the role of CXR of COVID-19 patients at presentation. Aims: Evaluatethe radiographic findings on CXR in COVID-19 patients at presentation. Recommend a guideline for its judicious use. Settings and Design: Retroprospective study performed on RT-PCR confirmed COVID-19 patients admitted in our hospital between March 31,2020 to May 25, 2020. The study included symptomatic and asymptomatic patients. CXR was performed for218 patients. Materials and Methods: Portable bedside CXR was performed. The CXRs were evaluated by three radiologists to record the findings and grade the disease. All variables were expressed as mean, ranges, counts, and percentages. Results: 157 patients (72%) were symptomatic and 61 (28%) were asymptomatic. 104 CXRs (48%) were abnormal (97 in symptomatic (62%) and fourin asymptomatic (6%)). 74 patients (47%) in the symptomatic group had known comorbidities and of these, 62 (84%) had abnormal CXR. 97 CXRs (93%) had bilateral findings and 87 CXRs (84%) had peripherally predominant abnormalities. The lower zone was the most common area of involvement (73%). Ground glass opacity (GGO) was the most common finding (94%–98 CXRs). Mild disease was seen in 56 (54%).Conclusion: CXR can be used to assess symptomatic COVID-19 patients at presentation and to grade the severity of disease. It may be avoided in asymptomatic patients.

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Severe acute respiratory syndrome coronavirus-2 (SAR-CoV-2) is a highly contagious infectious disease and spreads through aerosols and fomites. Health care personnel who are at the forefront of the fight against coronavirus disease-19 (COVID-19) pandemic are also at greater risk of contracting the infection. Mixing of uninfected people with infected people is potentially hazardous, especially in a radiology department. Implementation of meticulous operational changes, curtailment of nonurgent radiological work, rationalization of staff, equipment disinfection, use of personal protection equipment, and psychological support are needed to combat COVID-19 or any such infectious disease outbreak. This technical note will familiarize radiology workers with infectious disease outbreak-response to be adopted to ensure the safety of staff and patients.

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A total of 1,499 patients who underwent High Resolution Computed tomography (HRCT) chest in the duration of 2 months for suspected COVID-19 pneumonia were included. Subjects included were those who had tested positive for the virus on RT-PCR, those with symptoms suspicious for COVID-19 infection awaiting results for the RT-PCR test or with negative result but strong clinical suspicion as well as those with exposure to proven patients based on contact tracing. Thus, both symptomatic as well as asymptomatic patients were included. The positive predictive value of HRCT was 85%, sensitivity was 73% for all patients. Overall, accuracy was 68%. There was no significant difference in these values for symptomatic and asymptomatic individuals. These results were also independent of the time of scan from the onset of symptoms or contact. Thus, we propose that HRCT is an excellent adjunct for initial diagnosis of COVID-19 pneumonia in both symptomatic and asymptomatic individuals in addition to the role of prognostic indicator for COVID-19 pneumonia.

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With the sudden outbreak of Coronavirus disease-19 (COVID-19) in China, and its rapid spread across the continents over a short period of time, healthcare workers are posed with the challenge of managing these patients as well protecting themselves from getting infected. Since interventional radiology deals with both elective and emergency services, wherein close patient contact is a norm, there is a substantial risk of acquiring and transmitting infection. Given the circumstances, it is imperative to develop broadly applicable guidelines to utilize the available resources in an optimal fashion and limit transmission of disease. This brief review deals with infection control measures within the Interventional Radiology department or section and possible recommendations that can be adopted at the institutional level.

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This article focuses on a marked drop in volumes in the lockdown period during the COVID-19 pandemic across all modalities X-ray, sonography, CT scan and MRI scans and compares the volumes of data between a private and public hospital in Mumbai. This trend has been witnessed globally also. Even with easing of lockdown this has not reflected in an increase in numbers. Imaging volumes of a 1900-bed public hospital and a 220-bed private hospital in Mumbai were collated for all modalities, i.e., X-ray, sonography, CT and MRI for the months January, February 2020- Prelockdown, March 2020 Peri-lockdown, April, May 2020- Lockdown, June Unlock 1.0, July Unlock 2.0. The imaging volumes during lockdown, Unlock, were compared with prelockdown values. It was initially felt that this was due to a fear of visiting hospitals that are considered hotbeds of SARS-CoV-2. However, the same status has persisted over the 2 months of lockdown and the 2 months of unlocking. What is the cause of this huge drop in imaging volumes?

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The COVID-19 pandemic began in late December in 2019 and has now reached to 216 countries with 1,08,42,028 confirmed cases and 5,21,277 deaths according to the WHO reports and 6,49,666 confirmed cases in india alone with 18,679 deaths (as on 04^th july 2020) . RT-PCR has been considered the standard test for diagnosis of COVID 19. However, there has been reported a high false negative rate. This high false negative rate increases the risk of further transmission as well as delays the timely management of suspected cases. We have conducted HRCT chest of various (200 patient case study) proven and suspected cases of COVID-19 infection in the months of April, May and June 2020. Out of 200 scanned patients with clinical complains and suspicion, positive HRCT chest findings were seen in 196 patients, showing clinical-radiological correlation and an accuracy of 98%. The sensitivity of chest CT in suggesting COVID-19 was 98.6% (146/148patients) based on positive RT-PCR results. In patients with negative RT-PCR results and high clinical suspicion, 90% (18/20) had positive chest CT findings. HRCT chest is very sensitive and accurate in picking up lung parenchymal abnormalities in laboratory negative RT-PCR cases with high clinical suspicion of COVID-19 infection and also in all symptomatic patients where RT-PCR was not done. HRCT can also be very sensitive, cost effective and time effective in screening patients with high clinical suspicion. HRCT scores over RT-PCR in giving immediate results, assessing severity of disease and prediction of prognosis. We suggest HRCT chest for detection of early parenchymal abnormalities, assessing severity of disease in all patients with clinical symptoms and suspicion of COVID infection irrespective of laboratory RT-PCR status.

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Context: Paucity of literature of portable CXR findings in COVID-19. Aims: Evaluate radiographic findings in COVID-19 patients and calculate sensitivity of radiographs with RT-PCR as gold standard. Subjects and Methods: Total 116 COVID-19 patients underwent portable CXR between April-June, 2020. Two radiologists reviewed radiographs with respect to laterality, craniocaudal, mediolateral distribution, shape, density, unifocality/multifocality and number of lung zones. Sensitivity of radiography was calculated with RT-PCR as gold standard. Statistical Analysis Used: IBM SPSS Statistics Subscription software (IBM, New York, USA). Results: Many patients 67.2% (78/116) were asymptomatic. Cough (21.5%, 25/116) and fever (17.6%, 20/116) were the most frequent symptoms. 36.2% (42/116) patients revealed COVID-19 pneumonia-like abnormalities on CXR. Sensitivity of CXR with RT-PCR as gold standard was 36.2% (CI: Confidence interval = 27.46% - 44.95%). More patients in symptomatic group (68.4%, 26/38) had abnormal CXR compared to asymptomatic group (20.5%, 16/78) [P < 0.0001]. Radiographs revealed both unilateral (57.1%, 24/42), bilateral (42.8%, 18/42), GGO (80.9%, 34/42), or consolidation (11/42, 26.1%) in a middle (57.1%, 24/42), lower zone (83.3%, 35/42) and peripheral distribution (78.5%, 33/42). Lesions were commonly patchy (88%, 37/42) and multifocal (59.5%, 25/42). Majority had single (40.4%, 17/42) or two zone (35.7%, 15/42) involvement. Conclusions: Significant number of COVID-19 patients were asymptomatic. Over 1/3^rd of patients showed radiographic abnormalities. Symptomatic patients were more likely to show radiographic findings than asymptomatic patients. If radiographs identify pneumonia in appropriate clinical setting, CT can be avoided. Common radiographic abnormalities among COVID 19 patients were bilateral/unilateral, patchy, multifocal, ground glass opacity or consolidation in peripheral and middle/lower zone distribution.

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