Risk score model to automatically detect prostate cancer patients by integrating diagnostic parameters.

Introduction: Prostate cancer (PCa) is one of the prevailing forms of cancer among men. At present, multiparametric MRI is the imaging method for localizing tumors and staging cancer. Radiomics plays a key role and hold potential for PCa detection, reducing the need for unnecessary biopsies, characterizing tumor aggression, and overseeing PCa recurrence post-treatment.

A Framework of Analysis to Facilitate the Harmonization of Multicenter Radiomic Features in Prostate Cancer.

Pooling radiomic features coming from different centers in a statistical framework is challenging due to the variability in scanner models, acquisition protocols, and reconstruction settings. To remove technical variability, commonly called batch effects, different statistical harmonization strategies have been widely used in genomics but less considered in radiomics. The aim of this work was to develop a framework of analysis to facilitate the harmonization of multicenter radiomic features extracted from prostate T2-weighted magnetic resonance imaging (MRI) and to improve the power of radiomics for prostate cancer (PCa) management in order to develop robust non-invasive biomarkers translating into clinical practice.

Evaluation of a multiparametric MRI radiomic-based approach for stratification of equivocal PI-RADS 3 and upgraded PI-RADS 4 prostatic lesions.

Despite the key-role of the Prostate Imaging and Reporting and Data System (PI-RADS) in the diagnosis and characterization of prostate cancer (PCa), this system remains to be affected by several limitations, primarily associated with the interpretation of equivocal PI-RADS 3 lesions and with the debated role of Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI), which is only used to upgrade peripheral PI-RADS category 3 lesions to PI-RADS category 4 if enhancement is focal. We aimed at investigating the usefulness of radiomics for detection of PCa lesions (Gleason Score ≥ 6) in PI-RADS 3 lesions and in peripheral PI-RADS 3 upgraded to PI-RADS 4 lesions (upPI-RADS 4). Multiparametric MRI (mpMRI) data of patients who underwent prostatic mpMRI between April 2013 and September 2018 were retrospectively evaluated.

The use of chest ultrasonography in suspected cases of COVID-19 in the emergency department.

Aim: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus-specific reverse transcriptase-polymerase chain reaction (RT-PCR) represents the diagnostic gold standard. We explored the value of chest ultrasonography to predict positivity to SARS-CoV-2 on RT-PCR in suspected COVID-19 cases.

Patients & Methods: Consecutive patients with suspect COVID-19 were included if they had fever and/or history of cough and/or dyspnea.

Dual energy computed tomography evaluation of skeletal traumas.

Skeletal traumas are among the most common routine challenges faced by Emergency Radiologists, in particular in case of radiographically occult nondisplaced fractures or in case of soft tissue injuries. With the development of Dual Energy Computed Tomography (DECT) technology, new post-processing applications have gained a useful diagnostic role in many fields of musculoskeletal imaging including acute skeletal trauma imaging. In addition to conventional CT images, DECT allows for the generation of virtual calcium-suppressed images subtracting calcium from unenhanced CT images based on the fact that material attenuation varies at different energy levels.