Published in European radiology
To study whether a trained convolutional neural network (CNN) can be of assistance to radiologists in differentiating Coronavirus disease (COVID)-positive from COVID-negative patients using chest X-ray (CXR) through an ambispective clinical study. To identify subgroups of patients where artificial intelligence (AI) can be of particular value and an...
Published in European radiology
To recognize most common patterns of upper extremity (UE) injuries in victims of Intimate Partner Violence (IPV). Radiological review of 308 patients who reported physical IPV at our institution from January 2013 to June 2018, identified 55 patients with 88 unique UE injuries. Demographic data and injury patterns and associations were collected fro...
Published in European radiology
To evaluate the influence of audio-guided self-hypnosis on claustrophobia in a high-risk cohort undergoing magnetic resonance (MR) imaging. In this prospective observational 2-group study, 55 patients (69% female, mean age 53.6 ± 13.9) used self-hypnosis directly before imaging. Claustrophobia included premature termination, sedation, and coping ac...
Published in European radiology
Published in European Radiology
Objectives To assess the frequency, intensity, and clinical impact of [18F]FDG-avidity of axillary lymph nodes after vaccination with COVID-19 vaccines BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) in patients referred for oncological FDG PET/CT. Methods One hundred forty patients referred for FDG PET/CT during February and March 2021 after fi...
Published in European Radiology
Objective During the COVID-19 pandemic, there was a temporary cessation of mammography screening. However, in some facilities, diagnostic breast imaging services continued for patients with a high clinical suspicion of breast cancer. The objective of this study was to evaluate changes in the diagnostic interval (DI) of non-screening patients presen...
Published in European Radiology
Objectives In the midst of the coronavirus disease 2019 (COVID-19) outbreak, chest X-ray (CXR) imaging is playing an important role in diagnosis and monitoring of patients with COVID-19. We propose a deep learning model for detection of COVID-19 from CXRs, as well as a tool for retrieving similar patients according to the model’s results on their C...
Published in European Radiology
Objective It is unknown how patients prioritize gadolinium-based contrast media (GBCM) benefits (detection sensitivity) and risks (reactions, gadolinium retention, cost). The purpose of this study is to measure preferences for properties of GBCM in women at intermediate or high risk of breast cancer undergoing annual screening MRI. Methods An insti...
Published in European Radiology
Objectives To develop a deep learning–based pulmonary vessel segmentation algorithm (DLVS) from noncontrast chest CT and to investigate its clinical implications in assessing vascular remodeling of chronic obstructive lung disease (COPD) patients. Methods For development, 104 pulmonary CT angiography scans (49,054 slices) using a dual-source CT wer...
Published in European Radiology
Objective The aims of this study were to develop a multiparametric prognostic model for death in COVID-19 patients and to assess the incremental value of CT disease extension over clinical parameters. Methods Consecutive patients who presented to all five of the emergency rooms of the Reggio Emilia province between February 27 and March 23, 2020, f...
