Evaluation of C-Reactive Protein and Computer-Aided Analysis of Chest X-rays as Tuberculosis Triage Tests at Health Facilities in Lesotho and South Africa.

Background: To improve tuberculosis case-finding, rapid, non-sputum triage tests need to be developed according to the World Health Organization target product profile (TPP) (>90% sensitivity, >70% specificity). We prospectively evaluated and compared artificial intelligence-based, computer-aided detection software, CAD4TBv7, and C-reactive protein assay (CRP) as triage tests at health facilities in Lesotho and South Africa.

Methods: Adults (≥18 years) presenting with ≥1 of the 4 cardinal tuberculosis symptoms were consecutively recruited between February 2021 and April 2022.

Magnetic Resonance Imaging Findings Corresponding to Vasculitis as Defined via [F]FDG Positron Emission Tomography or Ultrasound.

We sought to investigate magnetic resonance imaging (MRI) parameters that correspond to vasculitis observed via [F]FDG positron emission tomography/computed tomography (PET/CT) and ultrasound in patients with large-vessel giant cell arteritis (LV-GCA). We performed a cross-sectional analysis of patients diagnosed with LV-GCA. Patients were selected if MRI, PET/CT, and vascular ultrasound were performed at the time of LV-GCA diagnosis.

Back-to-Africa introductions of Mycobacterium tuberculosis as the main cause of tuberculosis in Dar es Salaam, Tanzania.

In settings with high tuberculosis (TB) endemicity, distinct genotypes of the Mycobacterium tuberculosis complex (MTBC) often differ in prevalence. However, the factors leading to these differences remain poorly understood. Here we studied the MTBC population in Dar es Salaam, Tanzania over a six-year period, using 1,082 unique patient-derived MTBC whole-genome sequences (WGS) and associated clinical data.

Performance of a deep learning tool to detect missed aortic dilatation in a large chest CT cohort.

Purpose: Thoracic aortic (TA) dilatation (TAD) is a risk factor for acute aortic syndrome and must therefore be reported in every CT report. However, the complex anatomy of the thoracic aorta impedes TAD detection. We investigated the performance of a deep learning (DL) prototype as a secondary reading tool built to measure TA diameters in a large-scale cohort.

Associations between fully-automated, 3D-based functional analysis of the left atrium and classification schemes in atrial fibrillation.

Background: Atrial fibrillation (AF) has been linked to left atrial (LA) enlargement. Whereas most studies focused on 2D-based estimation of static LA volume (LAV), we used a fully-automatic convolutional neural network (CNN) for time-resolved (CINE) volumetry of the whole LA on cardiac MRI (cMRI). Aim was to investigate associations between functional parameters from fully-automated, 3D-based analysis of the LA and current classification schemes in AF.

Is sleep disordered breathing a risk factor for COVID-19 or ?

https://bit.ly/37v5Gyz.

Case Report: Opposite Effects of Inhibition on Closely Related Clonal Myeloid Disorders.

Langerhans cell histiocytosis (LCH) commonly co-occurs with additional myeloid malignancies. The introduction of targeted therapies, blocking "driver" mutations (e.g.

From cold-blooded reptiles to embryological remnants: Persistent myocardial sinusoids.

In nature, basically 2 types of myocardial vascular patterns exist: the sinusoidal and the coronary type. In the sinusoidal type, the sinusoid is completely fed by blood coming directly from the ventricle through a spongy sinusoidal network. This pattern is found in cold-blooded animals and in the early embryologic development of human (warm-blooded) hearts.

Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium.

Background: Artificial intelligence can assist in cardiac image interpretation. Here, we achieved a substantial reduction in time required to read a cardiovascular magnetic resonance (CMR) study to estimate left atrial volume without compromising accuracy or reliability. Rather than deploying a fully automatic black-box, we propose to incorporate the automated LA volumetry into a human-centric interactive image-analysis process.

Exercise capacity impairment after COVID-19 pneumonia is mainly caused by deconditioning.

https://bit.ly/2XVvr6C

Fully automated guideline-compliant diameter measurements of the thoracic aorta on ECG-gated CT angiography using deep learning.

Background: Manually performed diameter measurements on ECG-gated CT-angiography (CTA) represent the gold standard for diagnosis of thoracic aortic dilatation. However, they are time-consuming and show high inter-reader variability. Therefore, we aimed to evaluate the accuracy of measurements of a deep learning-(DL)-algorithm in comparison to those of radiologists and evaluated measurement times (MT).

Ninety-day outcome of patients with severe COVID-19 treated with tocilizumab - a single centre cohort study.

Objectives: Patients with severe COVID-19 may be at risk of longer term sequelae. Long-term clinical, immunological, pulmonary and radiological outcomes of patients treated with anti-inflammatory drugs are lacking.

Methods: In this single-centre prospective cohort study, we assessed 90-day clinical, immunological, pulmonary and radiological outcomes of hospitalised patients with severe COVID-19 treated with tocilizumab from March 2020 to May 2020.

Deep learning-based automated detection of pulmonary embolism on CT pulmonary angiograms: No significant effects on report communication times and patient turnaround in the emergency department nine months after technical implementation.

Objectives: Rapid communication of CT exams positive for pulmonary embolism (PE) is crucial for timely initiation of anticoagulation and patient outcome. It is unknown if deep learning automated detection of PE on CT Pulmonary Angiograms (CTPA) in combination with worklist prioritization and an electronic notification system (ENS) can improve communication times and patient turnaround in the Emergency Department (ED).

Methods: In 01/2019, an ENS allowing direct communication between radiology and ED was installed.

Automated CT Lung Density Analysis of Viral Pneumonia and Healthy Lungs Using Deep Learning-Based Segmentation, Histograms and HU Thresholds.

CT patterns of viral pneumonia are usually only qualitatively described in radiology reports. Artificial intelligence enables automated and reliable segmentation of lungs with chest CT. Based on this, the purpose of this study was to derive meaningful imaging biomarkers reflecting CT patterns of viral pneumonia and assess their potential to discriminate between healthy lungs and lungs with viral pneumonia.

Lethal COVID-19: Radiologic-Pathologic Correlation of the Lungs.

Purpose: The purpose of this retrospective study was to correlate CT patterns of fatal cases of coronavirus disease 2019 (COVID-19) with postmortem pathology observations.

Materials And Methods: The study included 70 lung lobes of 14 patients who died of reverse-transcription polymerase chain reaction-confirmed COVID-19. All patients underwent antemortem CT and autopsy between March 9 and April 30, 2020.

Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings.

Objective: To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict patient management.

Materials And Methods: All initial chest CTs of patients who tested positive for severe acute respiratory syndrome coronavirus 2 at our emergency department between March 25 and April 25, 2020, were identified (n = 120). Three patient management groups were defined: group 1 (outpatient), group 2 (general ward), and group 3 (intensive care unit [ICU]).

Acute aortic dissection with entry tear at the aortic arch: long-term outcome.

Objectives: The goal was to evaluate outcomes after conservative or surgical treatment of acute aortic arch dissections.

Methods: Between January 2009 and December 2018, patients with a diagnosis of acute aortic dissection were analysed. Aortic arch aortic dissection was defined as a dissection with an isolated entry tear at the aortic arch with no involvement of the ascending aorta.

Development and clinical implementation of tailored image analysis tools for COVID-19 in the midst of the pandemic: The synergetic effect of an open, clinically embedded software development platform and machine learning.

Purpose: During the emerging COVID-19 pandemic, radiology departments faced a substantial increase in chest CT admissions coupled with the novel demand for quantification of pulmonary opacities. This article describes how our clinic implemented an automated software solution for this purpose into an established software platform in 10 days. The underlying hypothesis was that modern academic centers in radiology are capable of developing and implementing such tools by their own efforts and fast enough to meet the rapidly increasing clinical needs in the wake of a pandemic.

Treatment of COVID-19 With Conestat Alfa, a Regulator of the Complement, Contact Activation and Kallikrein-Kinin System.

A dysregulated immune response with hyperinflammation is observed in patients with severe coronavirus disease 2019 (COVID-19). The aim of the present study was to assess the safety and potential benefits of human recombinant C1 esterase inhibitor (conestat alfa), a complement, contact activation and kallikrein-kinin system regulator, in severe COVID-19. Patients with evidence of progressive disease after 24 h including an oxygen saturation <93% at rest in ambient air were included at the University Hospital Basel, Switzerland in April 2020.

[Assessment of lung impairment in patients with cystic fibrosis : Novel magnetic resonance imaging methods].

Clinical/methodological Issue: The differentiated assessment of respiratory mechanics, gas exchange and pulmonary circulation, as well as structural impairment of the lung are essential for the treatment of patients with cystic fibrosis (CF). Clinical lung function measurements are often not sufficiently specific and are often difficult to perform.

Standard Radiological Methods: The standard procedures for pulmonary imaging are chest X‑ray and computed tomography (CT) for assessing lung morphology.

Automated detection of pulmonary embolism in CT pulmonary angiograms using an AI-powered algorithm.

Objectives: To evaluate the performance of an AI-powered algorithm for the automatic detection of pulmonary embolism (PE) on chest computed tomography pulmonary angiograms (CTPAs) on a large dataset.

Methods: We retrospectively identified all CTPAs conducted at our institution in 2017 (n = 1499). Exams with clinical questions other than PE were excluded from the analysis (n = 34).

Assessment of a Deep Learning Algorithm for the Detection of Rib Fractures on Whole-Body Trauma Computed Tomography.

Objective: To assess the diagnostic performance of a deep learning-based algorithm for automated detection of acute and chronic rib fractures on whole-body trauma CT.

Materials And Methods: We retrospectively identified all whole-body trauma CT scans referred from the emergency department of our hospital from January to December 2018 (n = 511). Scans were categorized as positive (n = 159) or negative (n = 352) for rib fractures according to the clinically approved written CT reports, which served as the index test.

Impact of Modified Frozen Elephant Trunk Procedure on Downstream Aorta Remodeling in Acute Aortic Dissection: CT Scan Follow-Up.

Objectives: The aim was to evaluate the impact of a modified frozen elephant trunk procedure (mFET) on remodeling of the downstream aorta following acute aortic dissections.

Methods: Over a period of 8 years, 205 patients (mean age 62.6 ± 12.