Bone and soft-tissue primary malignant tumors or sarcomas are a large, diverse group of mesenchymal-derived malignancies. They represent a model for intra- and intertumoral heterogeneities, making them particularly suitable for radiomics analyses. Radiomic features offer information on cancer phenotype as well as the tumor microenvironment which, combined with other pertinent data such as genomics and proteomics and correlated with outcomes data, can produce accurate, robust, evidence-based, clinical-decision support systems. Our purpose in this narrative review is to offer an overview of radiomics studies dealing with Magnetic Resonance Imaging (MRI)-based radiomics models of bone and soft-tissue sarcomas that could help distinguish different histotypes, low-grade from high-grade sarcomas, predict response to multimodality therapy, and thus better tailor patients’ treatments and finally improve their survivals. Although showing promising results, interobserver segmentation variability, feature reproducibility, and model validation are three main challenges of radiomics that need to be addressed in order to translate radiomics studies to clinical applications. These efforts, together with a better knowledge and application of the “Radiomics Quality Score” and Image Biomarker Standardization Initiative reporting guidelines, could improve the quality of sarcoma radiomics studies and facilitate radiomics towards clinical translation.

Coronavirus disease 2019 (COVID-19) emerged in early December 2019 in China, as an acute lower respiratory tract infection and spread rapidly worldwide being declared a pandemic in March 2020. Chest-computed tomography (CT) has been utilized in different clinical settings of COVID-19 patients; however, COVID-19 imaging appearance is highly variable and nonspecific. Indeed, many pulmonary infections and non-infectious diseases can show similar CT findings and mimic COVID-19 pneumonia. In this review, we discuss clinical conditions that share a similar imaging appearance with COVID-19 pneumonia, in order to identify imaging and clinical characteristics useful in the differential diagnosis.

The aim of the study was to evaluate the temporal evolution of fibrotic-like pulmonary interstitial abnormalities secondary to Sars-CoV-2 virus (COVID-19) pneumonia detected on chest-CTs of patients hospitalized for COVID-19 infection. We retrospectively reviewed chest-CTs obtained up to 9 months after disease onset in a group of patients with COVID-19 pneumonia and CT features suggestive of lung fibrosis at the first follow-up after hospital discharge. We observed a complete and unexpected resolution of all interstitial abnormalities, including reticulations and bronchial dilatation, in a period of about 6-9 months after discharge. Interstitial fibrotic-like changes detectable in the first months after COVID-19 pneumonia could be slowly or very slowly resolving but still completely reversible and probably secondary to an organizing pneumonia reaction. KeywordsCOVID-19 • Diffuse lung disease • Organizing pneumonia • Pulmonary fibrosis • HRCT This article is part of the Topical Collection on COVID-19

Purpose: To identify differences in chest computed tomography (CT) of the symptomatic coronavirus disease 2019 (COVID-19) population according to the patients' severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination status (non-vaccinated, vaccinated with incomplete or complete vaccination cycle). Material and methods:CT examinations performed in the Emergency Department (ED) in May-November 2021 for suspected COVID-19 pneumonia with a positive SARS-CoV-2 test were retrospectively included. Personal data were compared for vaccination status. One 13-year experienced radiologist and two 4th-year radiology residents independently evaluated chest CT scans according to CO-RADS and ACR COVID classifications. In possible COVID-19 pneumonia cases, defined as CO-RADS 3 to 5 (ACR indeterminate and typical) by each reader, high involvement CT score (≥ 25%) and CT patterns (presence of ground glass opacities, consolidations, crazy paving areas) were compared for vaccination status.Results: 184 patients with known vaccination status were included in the analysis: 111 non-vaccinated (60%) for SARS-CoV-2 infection, 21 (11%) with an incomplete vaccination cycle, and 52 (28%) with a complete vaccination cycle (6 different vaccine types). Multivariate logistic regression showed that the only factor predicting the absence of pneumonia (CO-RADS 1 and ACR negative cases) for the 3 readers was a complete vaccination cycle (OR = 12.8-13.1 compared to non-vaccinated patients, p ≤ 0.032). Neither CT score nor CT patterns of possible COVID-19 pneumonia showed any statistically significant correlation with vaccination status for the 3 readers.Conclusions: Symptomatic SARS-CoV-2-infected patients with a complete vaccination cycle had much higher odds of showing a negative CT chest examination in ED compared to non-vaccinated patients. Neither CT involvement nor CT patterns of interstitial pneumonia showed differences across different vaccination status.

Following the introduction of new effective antifibrotic drugs, interest in fibrosing interstitial lung diseases (FILD) has been renewed. In this context, radiological evaluation of FILD plays a cardinal role. Radiological diagnosis is possible in about 50% of the cases, which allows the initiation of effective therapy, thereby avoiding invasive procedures such as surgical lung biopsy. Usual interstitial pneumonia (UIP) pattern may be diagnosed based on clinical, radiological, and pathological data. High-resolution computed tomography features of UIP have been widely described in literature; however, interpreting them remains challenging, even with specific expertise on the subject. Diagnostic difficulties are understandable given the continuous evolution of FILD classifications and their complexity. Both early-stage diseases and advanced or combined patterns are not easily classifiable, and many end up being labelled ‘indeterminate´ or ‘unclassifiable´. Especially in these cases, optimal patient management involves collaboration and communication between different specialists. Here, we discuss the most critical aspects of radiological interpretation in FILD diagnosis based on the most recent classifications. We believe that the clinicians´ awareness of radiological diagnostic issues of FILD would improve comprehension and dialogue between physicians and radiologists, leading to better clinical practice.