When pneumonia is not COVID-19

Pneumonia in the Pandemic: Not Always COVID-19

The coronavirus disease 2019 (COVID-19) pandemic has changed the way we manage patients, especially those with respiratory illnesses. Clinical manifestations, chest imaging, and reverse-transcription polymerase chain reaction (RT-PCR) play major roles in diagnosing respiratory infections during a pandemic. However, several infections can mimic COVID-19 regarding its clinical signs, symptoms, and imaging appearance. Diagnosing pneumonia other than COVID-19 is a big challenge in developing countries, given the limited resources available. We presented a case of a 25-year-old female with clinical symptoms and radiological characteristics typical of COVID-19 but a repeated negative RT-PCR test. Further workups found lung tuberculosis as her primary diagnosis. Our patient continued treatment with an antituberculosis agent and a short course of steroids, with a remission of symptoms.

Detection of Lung Opacity and Treatment Planning with Three-Channel Fusion CNN Model

Lung opacities are extremely important for physicians to monitor and can have irreversible consequences for patients if misdiagnosed or confused with other findings. Therefore, long-term monitoring of the regions of lung opacity is recommended by physicians. Tracking the regional dimensions of images and classifying differences from other lung cases can provide significant ease to physicians. Deep learning methods can be easily used for the detection, classification, and segmentation of lung opacity. In this study, a three-channel fusion CNN model is applied to effectively detect lung opacity on a balanced dataset compiled from public datasets. The MobileNetV2 architecture is used in the first channel, the InceptionV3 model in the second channel, and the VGG19 architecture in the third channel. The ResNet architecture is used for feature transfer from the previous layer to the current layer. In addition to being easy to implement, the proposed approach can also provide significant cost and time advantages to physicians. Our accuracy values for two, three, four, and five classes on the newly compiled dataset for lung opacity classifications are found to be 92.52%, 92.44%, 87.12%, and 91.71%, respectively.

Schematic approach to the diagnosis of multifocal lung opacities in the emergency department

Radiologists in the emergency department must be prepared to deal with any type of disease in any organ at any time. Many entities involving the chest can result in patients' presenting at the emergency department. This chapter deals with entities that manifest with multifocal lung opacities and that can be mistaken for pneumonia. To facilitate their identification, this chapter approaches these entities by considering their most characteristic distribution on chest X-rays, the main diagnostic modality used for thoracic problems in the emergency department. Our schematic approach includes the key findings in patients' personal histories, clinical examination, laboratory tests, and imaging studies that can be available during the initial workup.

Epidemiology of Systemic Mycoses in the COVID-19 Pandemic

The physiopathologic characteristics of COVID-19 (high levels of inflammatory cytokines and T-cell reduction) promote fungal colonization and infection, which can go unnoticed because the symptoms in both diseases are very similar. The objective of this work was to study the current epidemiology of systemic mycosis in COVID-19 times. A literature search on the subject (January 2020–February 2021) was performed in PubMed, Embase, Cochrane Library, and LILACS without language restrictions. Demographic data, etiological agent, risk factors, diagnostic methods, antifungal treatment, and fatality rate were considered. Eighty nine publications were found on co-infection by COVID-19 and pneumocystosis, candidiasis, aspergillosis, mucormycosis, coccidioidomycosis, or histoplasmosis. In general, the co-infections occurred in males over the age of 40 with immunosuppression caused by various conditions. Several species were identified in candidiasis and aspergillosis co-infections. For diagnosis, diverse methods were used, from microbiological to molecular. Most patients received antifungals; however, the fatality rates were 11–100%. The latter may result because the clinical picture is usually attributed exclusively to SARS-CoV-2, preventing a clinical suspicion for mycosis. Diagnostic tests also have limitations beginning with sampling. Therefore, in the remainder of the pandemic, these diagnostic limitations must be overcome to achieve a better patient prognosis.