Role of Chest Imaging in Viral Lung Diseases

Abstract

The infection caused by novel beta-coronavirus (SARS-CoV-2) was officially declared a pandemic by the World Health Organization in March 2020. However, in the last 20 years, this has not been the only viral infection to cause respiratory tract infections leading to hundreds of thousands of deaths worldwide, referring in particular to severe acute respiratory syndrome (SARS), influenza H1N1 and Middle East respiratory syndrome (MERS). Although in this pandemic period SARS-CoV-2 infection should be the first diagnosis to exclude, many other viruses can cause pulmonary manifestations and have to be recognized. Through the description of the main radiological patterns, radiologists can suggest the diagnosis of viral pneumonia, also combining information from clinical and laboratory data.

Imaging Severity COVID-19 Assessment in Vaccinated and Unvaccinated Patients: Comparison of the Different Variants in a High Volume Italian Reference Center

“…As to the “gravity assessment” of COVID-19 infection and evaluation of pulmonary parenchymal involvement, several scores have been proposed [ 62 , 63 ]. The main goal of these tools is to establish a well-defined strategy for evaluation of the airways and lungs of COVID-19 positive patients from Computed Tomography (CT) scans, including detected abnormalities [ 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 ]. Their identification and the volumetric quantification may allow an easier classification in terms of gravity, extent and progression of the disease.…”

Artificial Intelligence and COVID-19 Using Chest CT Scan and Chest X-ray Images: Machine Learning and Deep Learning Approaches for Diagnosis and Treatment

“…In the context of the COVID-19 outbreak, there is a painstaking need for ready-touse resources for data acquisition and artificial intelligence (AI) algorithms to accelerate the search for effective and safe treatments. The progressive integration of radiomics approaches and AI-based solutions in healthcare is already changing established paradigms in the entire healthcare ecosystem, leveraging the progressive digitalization of medical data [38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53]. Specifically, diagnostic and decision support systems developed for medical imaging are the first successful examples of innovation for health.…”

“…AI-based methods have led to diagnostic applications that accelerate image acquisition, preprocessing, annotation and interpretation, offering an "augmentation" of the radiologists, rather than their unrealistic substitution. In particular, the application of AI in medical imaging has improved the assessment, diagnosis and early detection of neurodegenerative diseases, heart diseases, with a specifically high impact on breast and lung cancer [38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53].…”

Primary Lymphoproliferative Lung Diseases: Imaging and Multidisciplinary Approach

“…This finding is not specific to LYG and can be found in up to one fifth of patients with cryptogenic organizing pneumonia (COP), in some fungal infections, in SARS-CoV-2 infection, tuberculosis, sarcoidosis, granulomatosis with polyangiitis (GPA), radiation pneumonitis and many others. In immunocompromised patients, fungal infection should be considered to be the first suspect, while whether is combined with nodules inside the halo or with centrilobular opacities, the most probable differential diagnosis is with active tuberculosis [ 55 , 56 , 57 , 58 ].…”