Imaging algorithm for COVID-19: A practical approach

Comparison of Computed Tomography Findings between Adult and Pediatric COVID-19 Patients

PURPOSE

This study aims to compare chest computed tomography (CT) findings between adult and pediatric patients with coronavirus disease-19 (COVID-19) pneumonia.

MATERIALS AND METHODS

This study included 30 pediatric patients aged 1 to 17 years and 30 adult patients over 18 years of age with COVID-19 pneumonia confirmed by reverse transcriptase-polymerase chain reaction (RT-PCR) who have findings related to COVID-19 on Chest Computed Tomography. The CT findings of adult and pediatric patients were compared with a z-test.

RESULTS

Bilateral involvement (p:0.00056), involvement in all five lobes (p<0.00001), and central and peripheral involvement (p:0.01928) were significantly higher in the adult group compared to the pediatric group. In the pediatric group, the frequency of unilateral involvement (p:0.00056), involvement of solitary lobe (p:0.00132), and peripheral involvement (p: 0.01928) were significantly higher than in the adult group. The most common parenchymal finding in adults and pediatric patients was ground-glass opacities (100% and 83%, respectively). Among the parenchymal findings in adults, ground-glass opacities with consolidation (63%) were the second most common finding, followed by air bronchogram (60%) in adults, while in pediatric patients, halo sign (27%) and nodule (27%) were the second most common, followed by the ground-glass opacities with consolidation (23%).

CONCLUSION

The CT findings of pediatric COVID-19 patients must be well-known as the course of the disease is usually less severe, and the radiological findings are uncertain when compared with adults.

Investigation of the diagnostic importance and accuracy of CT in the chest compared to the RT-PCR test for suspected COVID-19 patients in Jordan

This article aims to synthesize the existing literature on the implementation of public policies to incentivize the development of treatments for rare diseases, (diseases with very low prevalence and therefore with low commercial interest) otherwise known as orphan drugs. The implementation of these incentives in the United States (US), Japan, and in the European Union (EU) seems to be related to a substantial increase in treatments for these diseases, and has influenced the way the pharmaceutical research & development (R&D) system operates beyond this policy area. Despite the success of the Orphan Drug model, the academic literature also highlights the negative implications that these public policies have on affordability and access to orphan drugs, as well as on the prioritization of certain disease rare areas over others. The synthesis focuses mostly on the United States' Orphan Drug Act (ODA) as a model for subsequent policies in other regions and countries. It starts with a historical overview of the creation of the term "rare diseases", continues with a summary of the evidence available on the US ODA's positive and negative impacts, and provides a summary of the different proposals to reform these incentives in light of the negative outcomes described. Finally, it describes some key aspects of the Japanese and European policies, as well as some of the challenges captured in the literature related to their impact in Low- and Middle-Income Countries (LMICs).

Role of Imaging in the Management of Patients with SARS-CoV-2 Lung Involvement Admitted to the Emergency Department: A Systematic Review

During the waves of the coronavirus disease (COVID-19) pandemic, emergency departments were overflowing with patients suffering with suspected medical or surgical issues. In these settings, healthcare staff should be able to deal with different medical and surgical scenarios while protecting themselves against the risk of contamination. Various strategies were used to overcome the most critical issues and guarantee quick and efficient diagnostic and therapeutic charts. The use of saliva and nasopharyngeal swab Nucleic Acid Amplification Tests (NAAT) in the diagnosis of COVID-19 was one of the most adopted worldwide. However, NAAT results were slow to report and could sometimes create significant delays in patient management, especially during pandemic peaks. On these bases, radiology has played and continues to play an essential role in detecting COVID-19 patients and solving differential diagnosis between different medical conditions. This systematic review aims to summarize the role of radiology in the management of COVID-19 patients admitted to emergency departments by using chest X-rays (CXR), computed tomography (CT), lung ultrasounds (LUS), and artificial intelligence (AI).

Advanced Imaging Supports the Mechanistic Role of Autoimmunity and Plaque Rupture in COVID-19 Heart Involvement

The cardiovascular system is frequently affected by coronavirus disease-19 (COVID-19), particularly in hospitalized cases, and these manifestations are associated with a worse prognosis. Most commonly, heart involvement is represented by myocarditis, myocardial infarction, and pulmonary embolism, while arrhythmias, heart valve damage, and pericarditis are less frequent. While the clinical suspicion is necessary for a prompt disease recognition, imaging allows the early detection of cardiovascular complications in patients with COVID-19. The combination of cardiothoracic approaches has been proposed for advanced imaging techniques, i.e., CT scan and MRI, for a simultaneous evaluation of cardiovascular structures, pulmonary arteries, and lung parenchyma. Several mechanisms have been proposed to explain the cardiovascular injury, and among these, it is established that the host immune system is responsible for the aberrant response characterizing severe COVID-19 and inducing organ-specific injury. We illustrate novel evidence to support the hypothesis that molecular mimicry may be the immunological mechanism for myocarditis in COVID-19. The present article provides a comprehensive review of the available evidence of the immune mechanisms of the COVID-19 cardiovascular injury and the imaging tools to be used in the diagnostic workup. As some of these techniques cannot be implemented for general screening of all cases, we critically discuss the need to maximize the sustainability and the specificity of the proposed tests while illustrating the findings of some paradigmatic cases.

Understanding COVID-19 Situation in Nepal and Implications for SARS-CoV-2 Transmission and Management

BACKGROUND

The pandemic of Coronavirus Disease 2019 (COVID-19), one of the most infectious diseases in the modern history, is caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) and has had a profound health and economic toll, globally. This paper identifies the overall health status associated with COVID-19 pandemic in all 7 provinces of Nepal, a developing country in South Asia, analyzing data from January 2020 to February 2022. It focuses on the SARS-CoV-2 prevalence, transmission through wastewater and other routes, diagnostics, treatment options, and alternative medicines, thereby offering key perspectives for its management.

MATERIALS AND METHODS

Studies regarding coronavirus spanning the 2017 to 2022 period were searched on the web, Nepalese database, and Web of Science. Refined criteria included SARS-CoV-2 in wastewater of Nepal or worldwide. Demographic data (sex, age-group, and geographic location) were also obtained from websites and relevant reports of the Ministry of Health and Population (MOHP) of Nepal, ranging from January 2020 to February 2022. Moreover, trends concerning lockdown, business, and border activities in Nepal between February 2020 and October 2020 were evaluated. The viral dissemination pathways, diagnosis, and available treatment options, including the Ayurvedic medicine, were also examined.

RESULTS

Aerosols generated during the hospital, industrial, recreational, and household activities were found to contribute to the propagation of SARS-CoV-2 into environmental wastewater, thereby putting the surrounding communities at risk of infection. When lockdown ended and businesses opened in October 2020, the number of active cases of COVID-19 increased exponentially. Bagmati Province had the highest number of cases (53.84%), while the remaining 6 provinces tallied 46.16%. Kathmandu district had the highest number of COVID-19 cases (138, 319 cases), while Manang district had the smallest number of infections (81 cases). The male population was found to be predominantly infected (58.7%). The most affected age groups were the 31 to 40 years old males (25.92%) and the 21 to 30 years old females (26.85%).

CONCLUSION

The pandemic impacted the public health and economic growth in our study duration. SARS-CoV-2 was prevalent in the wastewater of Nepal. The Terai districts and the megacities were mostly affected by SARS-CoV-2 infections. Working-age groups and males were identified as the highest risk groups. More investigations on the therapeutic and alternative cures are recommended. These findings may guide the researchers and professionals with handling the COVID-19 challenges in developing countries such as Nepal and better prepare for future pandemics.

Industry 4.0 technologies and their applications in fighting COVID-19 pandemic using deep learning techniques

The disease known as COVID-19 has turned into a pandemic and spread all over the world. The fourth industrial revolution known as Industry 4.0 includes digitization, the Internet of Things, and artificial intelligence. Industry 4.0 has the potential to fulfil customized requirements during the COVID-19 emergency crises. The development of a prediction framework can help health authorities to react appropriately and rapidly. Clinical imaging like X-rays and computed tomography (CT) can play a significant part in the early diagnosis of COVID-19 patients that will help with appropriate treatment. The X-ray images could help in developing an automated system for the rapid identification of COVID-19 patients. This study makes use of a deep convolutional neural network (CNN) to extract significant features and discriminate X-ray images of infected patients from non-infected ones. Multiple image processing techniques are used to extract a region of interest (ROI) from the entire X-ray image. The ImageDataGenerator class is used to overcome the small dataset size and generate ten thousand augmented images. The performance of the proposed approach has been compared with state-of-the-art VGG16, AlexNet, and InceptionV3 models. Results demonstrate that the proposed CNN model outperforms other baseline models with high accuracy values: 97.68% for two classes, 89.85% for three classes, and 84.76% for four classes. This system allows COVID-19 patients to be processed by an automated screening system with minimal human contact.

Fungal infection mimicking COVID-19 infection - A case report

For the last 2 years, one of the most frequent causes of respiratory failure is coronavirus disease 2019 (COVID-19). The symptoms are not specific. Imaging diagnostics, especially high-resolution computed tomography, is a diagnostic method widely used in the diagnosis of this disease. It is important to emphasize that not only SARS-CoV-2 infection may manifest as interstitial pneumonia. Other diseases such as other viral, fungal, atypical bacterial pneumonia, autoimmune process, and even cancer can also manifest as ground-glass opacities or consolidations in the imaging of the lungs. In this case report, we described a patient who manifested many symptoms that seemed to be COVID-19. However, all performed antigen and polymerase chain reaction tests were negative. The diagnostics must have been extended. Microbiological and mycological blood cultures and sputum cultures were performed. Blood cultures were negative but in sputum, Candida albicans and Candida glabrata were identified. Targeted therapy with fluconazole was implemented with a satisfactory result. The patient was discharged from the hospital in a good general condition with no complaints.

Executing Lung Sonography to Assess Acute and Chronic Disease: Can These Techniques Be Used to Monitor Adults and Children Surviving COVID-19?

Lung ultrasonography (LUS) has been used as a clinical diagnostic tool for the location of pleural fluid and marking patients for a thoracentesis, for decades, but has not been deemed as appropriate for other diagnostic uses. In the context of the COVID-19 pandemic, the necessity of a portable, low-cost, and non-ionizing diagnostic choice is needed to assess patient lungs. LUS has become a strong candidate to fill this diagnostic gap. With the use of Lichtenstein’s bedside LUS in emergency (BLUE) protocol, LUS may have potential to diagnose lung disease and assist with treatment decisions. While evidence of LUS as a COVID-19 diagnostic tool is not conclusive, early diagnostic results are promising. Further research on the use of LUS and the clinical implementation of the technique have a true potential to improve patient outcomes.

Inter-Observer Agreement between Low-Dose and Standard-Dose CT with Soft and Sharp Convolution Kernels in COVID-19 Pneumonia

Computed tomography (CT) has been an essential diagnostic tool during the COVID-19 pandemic. The study aimed to develop an optimal CT protocol in terms of safety and reliability. For this, we assessed the inter-observer agreement between CT and low-dose CT (LDCT) with soft and sharp kernels using a semi-quantitative severity scale in a prospective study (Moscow, Russia). Two consecutive scans with CT and LDCT were performed in a single visit. Reading was performed by ten radiologists with 3–25 years’ experience. The study included 230 patients, and statistical analysis showed LDCT with a sharp kernel as the most reliable protocol (percentage agreement 74.35 ± 43.77%), but its advantage was marginal. There was no significant correlation between radiologists’ experience and average percentage agreement for all four evaluated protocols. Regarding the radiation exposure, CTDI_vol was 3.6 ± 0.64 times lower for LDCT. In conclusion, CT and LDCT with soft and sharp reconstructions are equally reliable for COVID-19 reporting using the “CT 0-4” scale. The LDCT protocol allows for a significant decrease in radiation exposure but may be restricted by body mass index.

FDG PET/CT imaging features and clinical utility in COVID-19

Purpose

To determine the imaging findings and potential clinical utility of FDG PET/CT in patients with laboratory-confirmed COVID-19.

Methods

We performed a single institution retrospective review of patients diagnosed with COVID-19 using real time reverse transcription–polymerase chain reaction (RT-PCR) who underwent FDG PET/CT for routine cancer care between March 1, 2020 to April 30, 2020, during the height of the pandemic in New York City, New York, United States. PET/CT scans were retrospectively reviewed for imaging findings suspicious for COVID-19. For positive scans, PET and CT findings were recorded, including location, FDG avidity (SUV_max) and CT morphology. Patient demographics and COVID-19 specific clinical data were collected and analyzed with respect to PET/CT scan positivity, lung SUV_max, and time interval between PET/CT and RT-PCR.

Results

Thirty-one patients (21 males and 10 females, mean age 57 years ± 16) were evaluated. Thirteen of 31 patients had positive PET/CT scans, yielding a detection rate of 41.9%. Patients with positive scans had significantly higher rates of symptomatic COVID-19 infection (77% vs 28%, p = 0.01) and hospitalizations (46% vs. 0%, p = 0.002) compared to patients with negative scans. Eleven of 13 patients (84.6%) with positive scans had FDG-avid lung findings, with mean lung SUV_max of 5.36. Six of 13 patients (46.2%) had extrapulmonary findings of FDG-avid thoracic lymph nodes. The detection rate was significantly lower when the scan was performed before RT-PCR versus after RT-PCR (18.8% (n = 3/16) vs. 66.7% (n = 10/15), p = 0.009). Lung SUV_max was not associated with COVID-19 symptoms, severity, or disease course.

Conclusion

FDG PET/CT has limited sensitivity for detecting COVID-19 infection. However, a positive PET scan is associated with higher risk of symptomatic infection and hospitalizations, which may be helpful in predicting disease severity.

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.

M-BLUE protocol for coronavirus disease-19 (COVID-19) patients: interobserver variability and correlation with disease severity

AIM

To retrospectively evaluate the interobserver variability of intensive care unit (ICU) practitioners and radiologists who used the M-BLUE (modified bedside lung ultrasound in emergency) protocol to assess coronavirus disease-19 (COVID-19) patients, and to determine the correlation between total M-BLUE protocol score and three different scoring systems reflecting disease severity.

MATERIALS AND METHODS

Institutional review board approval was obtained and informed consent was not required. Ninety-six lung ultrasonography (LUS) examinations were performed using the M-BLUE protocol in 79 consecutive COVID-19 patients. Two ICU practitioners and three radiologists reviewed video clips of the LUS of eight different regions in each lung retrospectively. Each observer, who was blind to the patient information, described each clip with M-BLUE terminology and assigned a corresponding score. Interobserver variability was assessed using intraclass correlation coefficient. Spearman's correlation coefficient analysis (R-value) was used to assess the correlation between the total score of the eight video clips and disease severity.

RESULTS

For different LUS signs, fair to good agreement was obtained (ICC = 0.601, 0.339, 0.334, and 0.557 for 0-3 points respectively). The overall interobserver variability was good for both the five different readers and consensus opinions (ICC = 0.618 and 0.607, respectively). There were good correlations between total LUS score and scores from three systems reflecting disease severity (R=0.394-0.660, p<0.01).

CONCLUSION

In conclusion, interobserver agreement for different signs and total scores in LUS is good and justifies its use in patients with COVID-19. The total scores of LUS are useful to indicate disease severity.