Infectious sacroiliitis: MRI- and CT-based assessment of disease extent, complications, and anatomic correlation.

Objective: To describe the frequency of MR and CT features of infectious sacroiliitis (ISI) and assess its extent and complications MATERIALS AND METHODS: This retrospective study included patients with ISI who were evaluated between 2008 and 2021 in a single center. Two radiologists reviewed MRI and CT images to determine the anatomical distribution (unilateral/bilateral, iliac/sacral bone, proximal/middle/distal), severity (bone marrow edema [BME]/periostitis/erosions), concurrent infection (vertebral/nonvertebral), and complications (abscess/probable adjacent osteomyelitis/cavitation/devitalized areas/sequestrum/pelvic venous thrombosis) of ISI. Interobserver reproducibility was assessed.

Radiological pulmonary sequelae after COVID-19 and correlation with clinical and functional pulmonary evaluation: results of a prospective cohort.

Objectives: Whether COVID-19 leads to long-term pulmonary sequelae or not remains unknown. The aim of this study was to assess the prevalence of persisting radiological pulmonary fibrotic lesions in patients hospitalized for COVID-19.

Materials And Methods: We conducted a prospective single-center study among patients hospitalized for COVID-19 between March and May 2020.

Understanding a mass in the paraspinal region: an anatomical approach.

The paraspinal region encompasses all tissues around the spine. The regional anatomy is complex and includes the paraspinal muscles, spinal nerves, sympathetic chains, Batson's venous plexus and a rich arterial network. A wide variety of pathologies can occur in the paraspinal region, originating either from paraspinal soft tissues or the vertebral column.

Pulmonary Hypertension in Patients with Common Variable Immunodeficiency.

Purpose: Common variable immunodeficiency (CVID) is known to cause infectious, inflammatory, and autoimmune manifestations. Pulmonary hypertension (PH) is an unusual complication of CVID with largely unknown characteristics and mechanisms.

Methods: We report the clinical, functional, hemodynamics, radiologic and histologic characteristics, and outcomes of CVID-associated PH patients from the French PH Network.

Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients.

The SARS-COV-2 pandemic has put pressure on intensive care units, so that identifying predictors of disease severity is a priority. We collect 58 clinical and biological variables, and chest CT scan data, from 1003 coronavirus-infected patients from two French hospitals. We train a deep learning model based on CT scans to predict severity.