Review of X-ray and computed tomography scan findings with a promising role of point of care ultrasound in COVID-19 pandemic

Role of Imaging in Diagnosis and Management of COVID-19: Evidence-Based Approaches

Imaging has been demonstrated to play a crucial role in both the diagnosis and management of COVID-19. Depending on resources, pre-test probability, and risk factors for severe disease progression, real-time polymerase chain reaction (RT-PCR) testing may be followed by chest radiography (CXR) or chest computed tomography (CT) to further aid in diagnosis or excluding COVID-19 disease. SARS-CoV-2 has been shown not only to pathologically impact the pulmonary system, but also the cardiovascular, gastrointestinal, and neurological systems to name a few. Imaging has again proven useful in further investigating and managing extrapulmonary disease, with the use of echocardiogram, CT angiography of the cardiovascular and cerebrovascular structures, MRI of the brain, as well as ultrasound of the abdomen and CT of the abdomen and pelvis proving particularly useful. Research in artificial intelligence and its application in the diagnosis of COVID-19 and disease severity prediction is underway, and point-of-care ultrasound is an emerging bedside technique that may allow for more efficient and timely diagnosis of COVID-19.

COVID-19 Detection in CT/X-ray Imagery Using Vision Transformers

The steady spread of the 2019 Coronavirus disease has brought about human and economic losses, imposing a new lifestyle across the world. On this point, medical imaging tests such as computed tomography (CT) and X-ray have demonstrated a sound screening potential. Deep learning methodologies have evidenced superior image analysis capabilities with respect to prior handcrafted counterparts. In this paper, we propose a novel deep learning framework for Coronavirus detection using CT and X-ray images. In particular, a Vision Transformer architecture is adopted as a backbone in the proposed network, in which a Siamese encoder is utilized. The latter is composed of two branches: one for processing the original image and another for processing an augmented view of the original image. The input images are divided into patches and fed through the encoder. The proposed framework is evaluated on public CT and X-ray datasets. The proposed system confirms its superiority over state-of-the-art methods on CT and X-ray data in terms of accuracy, precision, recall, specificity, and F1 score. Furthermore, the proposed system also exhibits good robustness when a small portion of training data is allocated.

The role of chest imaging in the diagnosis, management, and monitoring of coronavirus disease 2019 (COVID-19)

Coronavirus disease 2019 (COVID-19) pandemic has posed a major public health crisis all over the world. The role of chest imaging, especially computed tomography (CT), has evolved during the pandemic paralleling the accumulation of scientific evidence. In the early stage of the pandemic, the performance of chest imaging for COVID-19 has widely been debated especially in the context of comparison to real-time reverse transcription polymerase chain reaction. Current evidence is against the use of chest imaging for routine screening of COVID-19 contrary to the initial expectations. It still has an integral role to play, however, in its work up and staging, especially when assessing complications or disease progression. Chest CT is gold standard imaging modality for COVID-19 pneumonia; in some situations, chest X-ray or ultrasound may be an effective alternative. The most important role of radiologists in this context is to be able to identify those patients at greatest risk of imminent clinical decompensation by learning to stratify cases of COVID-19 on the basis of radiologic imaging in the most efficient and timely fashion possible. The present availability of multiple and more refined CT grading systems and classification is now making this task easier and thereby contributing to the recent improvements achieved in COVID-19 treatment and outcomes. In this article, evidence of chest imaging regarding diagnosis, management and monitoring of COVID-19 will be chronologically reviewed.

Spontaneous Pneumomediastinum in Patients Diagnosed with COVID-19: A Case Series with Review of Literature

Background

Spontaneous pneumomediastinum (SPM) is a rare condition defined by the presence of air in the mediastinum in the absence of traumatic or iatrogenic injury. Although the imaging findings and complications of SARS-CoV-2 infection have been reported many times, there are few reports of the prevalence and outcomes of patients with SPM.

Purpose

In this paper, we aimed to illustrate the different manifestations, management, and outcome of three cases of SPM in COVID-19 patients and provide an extensive review available literature.

Materials and Methods

Detailed report of patients' demographics, clinical presentation, management, and outcome of three cases of COVID-19 induced SPM seen in our institution was provided. Additionally, literature search was employed through March 2021 using Pubmed and Google scholar databases where a total of 22 articles consisting of 35 patients were included.

Results

Statistical analysis of the reviewed articles showed that SPM in COVID-19 occurs in patients with a mean age of 55.6 ± 16.7 years. Furthermore, 80% of the 35 patients are males and almost 60% have comorbidities. Intriguingly, SPM in COVID-19 is associated with a 28.5% mortality rate. These findings are consistent with our case series and are different from previous reports of SPM in non-COVID-19 cases where it most commonly occurs in younger individuals and has a self-limiting course with a good outcome.

Conclusion

Therefore, SPM in COVID-19 patients occurs in older patients and is potentially associated with a higher mortality rate. Further studies are necessary to assess its role as a prognostic marker of poor outcome.

COVID-19 pneumonia: A review of typical radiological characteristics

Coronavirus disease 2019 (COVID-19) was first discovered after unusual cases of severe pneumonia emerged by the end of 2019 in Wuhan (China) and was declared a global public health emergency by the World Health Organization in January 2020. The new pathogen responsible for the infection, genetically similar to the beta-coronavirus family, is known as severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), and the current gold standard diagnostic tool for its detection in respiratory samples is the reverse transcription-polymerase chain reaction test. Imaging findings on COVID-19 have been widely described in studies published throughout last year, 2020. In general, ground-glass opacities and consolidations, with a bilateral and peripheral distribution, are the most typical patterns found in COVID-19 pneumonia. Even though much of the literature focuses on chest computed tomography (CT) and X-ray imaging and their findings, other imaging modalities have also been useful in the assessment of COVID-19 patients. Lung ultrasonography is an emerging technique with a high sensitivity, and thus useful in the initial evaluation of SARS-CoV-2 infection. In addition, combined positron emission tomography-CT enables the identification of affected areas and follow-up treatment responses. This review intends to clarify the role of the imaging modalities available and identify the most common radiological manifestations of COVID-19.

Long-term chest CT follow-up in COVID-19 Survivors: 102-361 days after onset

Background

The aim of this study was to evaluate long-term longitudinal changes in chest computed tomography (CT) findings in coronavirus disease 2019 (COVID-19) survivors and their correlations with dyspnea after discharge.

Methods

A total of 337 COVID-19 survivors who underwent CT scan during hospitalization and between 102 and 361 days after onset were retrospectively included. Subjective CT findings, lesion volume, therapeutic measures and laboratory parameters were collected. The severity of the survivors' dyspnea was determined by follow-up questionnaire. The evolution of the CT findings from the peak period to discharge and throughout follow-up and the abilities of CT findings and clinical parameters to predict survival with and without dyspnea were analyzed.

Results

Ninety-one COVID-19 survivors still had dyspnea at follow-up. The age, comorbidity score, duration of hospital stays, receipt of hormone administration, receipt of immunoglobulin injections, intensive care unit (ICU) admission, receipt of mechanical ventilation, laboratory parameters, clinical classifications and parameters associated with lesion volume of the survivors with dyspnea were significantly different from those of survivors without dyspnea. Among the clinical parameters and CT parameters used to identify dyspnea, parameters associated with lesion volume showed the largest area under the curve (AUC) values, with lesion volume at discharge showing the largest AUC (0.820). Lesion volume decreased gradually from the peak period to discharge and through follow-up, with a notable decrease observed after discharge. Absorption of lesions continued 6 months after discharge.

Conclusions

Among the clinical parameters and subjective CT findings, CT findings associated with lesion volume were the best predictors of post-discharge dyspnea in COVID-19 survivors.

A Comparison of Lung Ultrasound and Computed Tomography in the Diagnosis of Patients with COVID-19: A Systematic Review and Meta-Analysis

Background Lung ultrasound (LUS) and computed tomography (CT) can both be used for diagnosis of interstitial pneumonia caused by coronavirus disease 2019 (COVID-19), but the agreement between LUS and CT is unknown. Purpose to compare the agreement of LUS and CT in the diagnosis of interstitial pneumonia caused by COVID-19. Materials and Methods We searched PubMed, Cochrane library, Embase, Chinese Biomedicine Literature, and WHO COVID-19 databases to identify studies that compared LUS with CT in the diagnosis of interstitial pneumonia caused by COVID-19. We calculated the pooled overall, positive and negative percent agreements, diagnostic odds ratio (DOR) and the area under the standard receiver operating curve (SROC) for LUS in the diagnosis of COVID-19 compared with CT. Results We identified 1896 records, of which nine studies involving 531 patients were finally included. The pooled overall, positive and negative percentage agreements of LUS for the diagnosis of interstitial pneumonia caused by COVID-19 compared with CT were 81% (95% confidence interval [CI] 43–99%), 96% (95% CI, 80–99%, I² = 92.15%) and 80% (95%CI, 60–92%, I² = 92.85%), respectively. DOR was 37.41 (95% CI, 9.43–148.49, I² = 63.9%), and the area under the SROC curve was 0.94 (95% CI, 0.92–0.96). The quality of evidence for both specificity and sensitivity was low because of heterogeneity and risk of bias. Conclusion The level of diagnostic agreement between LUS and CT in the diagnosis of interstitial pneumonia caused by COVID-19 is high. LUS can be therefore considered as an equally accurate alternative for CT in situations where molecular tests are not available.

Imaging in the COVID-19 era: Lessons learned during a pandemic

The first year of the coronavirus disease 2019 (COVID-19) pandemic has been a year of unprecedented changes, scientific breakthroughs, and controversies. The radiology community has not been spared from the challenges imposed on global healthcare systems. Radiology has played a crucial part in tackling this pandemic, either by demonstrating the manifestations of the virus and guiding patient management, or by safely handling the patients and mitigating transmission within the hospital. Major modifications involving all aspects of daily radiology practice have occurred as a result of the pandemic, including workflow alterations, volume reductions, and strict infection control strategies. Despite the ongoing challenges, considerable knowledge has been gained that will guide future innovations. The aim of this review is to provide the latest evidence on the role of imaging in the diagnosis of the multifaceted manifestations of COVID-19, and to discuss the implications of the pandemic on radiology departments globally, including infection control strategies and delays in cancer screening. Lastly, the promising contribution of artificial intelligence in the COVID-19 pandemic is explored.

COVID-19 imaging: Diagnostic approaches, challenges, and evolving advances

The role of radiology and the radiologist have evolved throughout the coronavirus disease-2019 (COVID-19) pandemic. Early on, chest computed tomography was used for screening and diagnosis of COVID-19; however, it is now indicated for high-risk patients, those with severe disease, or in areas where polymerase chain reaction testing is sparsely available. Chest radiography is now utilized mainly for monitoring disease progression in hospitalized patients showing signs of worsening clinical status. Additionally, many challenges at the operational level have been overcome within the field of radiology throughout the COVID-19 pandemic. The use of teleradiology and virtual care clinics greatly enhanced our ability to socially distance and both are likely to remain important mediums for diagnostic imaging delivery and patient care. Opportunities to better utilize of imaging for detection of extrapulmonary manifestations and complications of COVID-19 disease will continue to arise as a more detailed understanding of the pathophysiology of the virus continues to be uncovered and identification of predisposing risk factors for complication development continue to be better understood. Furthermore, unidentified advancements in areas such as standardized imaging reporting, point-of-care ultrasound, and artificial intelligence offer exciting discovery pathways that will inevitably lead to improved care for patients with COVID-19.

Highlighting COVID-19: What the imaging exams show about the disease

Coronavirus disease 2019 (COVID-19), a global emergency, is caused by severe acute respiratory syndrome coronavirus 2. The gold standard for its diagnosis is the reverse transcription polymerase chain reaction, but considering the high number of infected people, the low availability of this diagnostic tool in some contexts, and the limitations of the test, other tools that aid in the identification of the disease are necessary. In this scenario, imaging exams such as chest X-ray (CXR) and computed tomography (CT) have played important roles. CXR is useful for assessing disease progression because it allows the detection of extensive consolidations, besides being a fast and cheap method. On the other hand, CT is more sensitive for detecting lung changes in the early stages of the disease and is also useful for assessing disease progression. Of note, ground-glass opacities are the main COVID-19-related CT findings. Positron emission tomography combined with CT can be used to evaluate chronic and substantial damage to the lungs and other organs; however, it is an expensive test. Lung ultrasound (LUS) has been shown to be a promising technique in that context as well, being useful in the screening and monitoring of patients, disease classification, and management related to mechanical ventilation. Moreover, LUS is an inexpensive alternative available at the bedside. Finally, magnetic resonance imaging, although not usually requested, allows the detection of pulmonary, cardiovascular, and neurological abnormalities associated with COVID-19. Furthermore, it is important to consider the challenges faced in the radiology field in the adoption of control measures to prevent infection and in the follow-up of post-COVID-19 patients.

Discrepancies in the clinical and radiological profiles of COVID-19: A case-based discussion and review of literature

The current gold standard for the diagnosis of coronavirus disease-19 (COVID-19) is a positive reverse transcriptase polymerase chain reaction (RT-PCR) test, on the background of clinical suspicion. However, RT-PCR has its limitations; this includes issues of low sensitivity, sampling errors and appropriate timing of specimen collection. As pulmonary involvement is the most common manifestation of severe COVID-19, early and appropriate lung imaging is important to aid diagnosis. However, gross discrepancies can occur between the clinical and imaging findings in patients with COVID-19, which can mislead clinicians in their decision making. Although chest X-ray (CXR) has a low sensitivity for the diagnosis of COVID-19 associated lung disease, especially in the earlier stages, a positive CXR increases the pre-test probability of COVID-19. CXR scoring systems have shown to be useful, such as the COVID-19 opacification rating score which helps to predict the need of tracheal intubation. Furthermore, artificial intelligence-based algorithms have also shown promise in differentiating COVID-19 pneumonia on CXR from other lung diseases. Although costlier than CXR, unenhanced computed tomographic (CT) chest scans have a higher sensitivity, but lesser specificity compared to RT-PCR for the diagnosis of COVID-19 pneumonia. A semi-quantitative CT scoring system has been shown to predict short-term mortality. The routine use of CT pulmonary angiography as a first-line imaging modality in patients with suspected COVID-19 is not justifiable due to the risk of contrast nephropathy. Scoring systems similar to those pioneered in CXR and CT can be used to effectively plan and manage hospital resources such as ventilators. Lung ultrasound is useful in the assessment of critically ill COVID-19 patients in the hands of an experienced operator. Moreover, it is a convenient tool to monitor disease progression, as it is cheap, non-invasive, easily accessible and easy to sterilise. Newer lung imaging modalities such as magnetic resonance imaging (MRI) for safe imaging among children, adolescents and pregnant women are rapidly evolving. Imaging modalities are also essential for evaluating the extra-pulmonary manifestations of COVID-19: these include cranial imaging with CT or MRI; cardiac imaging with ultrasonography (US), CT and MRI; and abdominal imaging with US or CT. This review critically analyses the utility of each imaging modality to empower clinicians to use them appropriately in the management of patients with COVID-19 infection.