A5083010859- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Radiomics and Machine Learning in Medical Imaging
- Radiation Dose and Imaging
- Radiology practices and education
- MRI in cancer diagnosis
- Medical Imaging and Pathology Studies
- Viral Infections and Immunology Research
- Nutrition and Health in Aging
- Body Composition Measurement Techniques
- Cardiac Structural Anomalies and Repair
- Medical Imaging Techniques and Applications
- Pulmonary Hypertension Research and Treatments
- Cardiac Imaging and Diagnostics
- Glioma Diagnosis and Treatment
- Lung Cancer Treatments and Mutations
- Soft tissue tumor case studies
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Reliability and Agreement in Measurement
- Bone health and osteoporosis research
- Artificial Intelligence in Healthcare and Education
- Pelvic and Acetabular Injuries
- Systemic Sclerosis and Related Diseases
- Advanced X-ray and CT Imaging
- Radiation Detection and Scintillator Technologies
Essen University Hospital
2023-2025
University of Duisburg-Essen
2023-2024
Institut für Medizinische Informatik, Biometrie und Epidemiologie
2023
Background: This study aimed to evaluate the impact of an AI-assisted fracture detection program on radiology residents’ performance in pediatric and adult trauma patients assess its implications for residency training. Methods: study, conducted retrospectively, included 200 radiographs from participants aged 1 95 years (mean age: 40.7 ± 24.5 years), encompassing various body regions. Among these, 50% (100/200) displayed at least one fracture, totaling hundred thirty-five fractures, assessed...
Objectives Double-dose contrast-enhanced brain imaging improves tumor delineation and detection of occult metastases but is limited by concerns about gadolinium-based contrast agents' effects on patients the environment. The purpose this study was to test benefit a deep learning–based signal amplification in true single-dose T1-weighted (T-SD) images creating artificial double-dose (A-DD) for metastasis magnetic resonance imaging. Materials Methods In prospective, multicenter study, method...
Abstract Background This study aimed to develop an automated algorithm noninvasively distinguish gliomas from other intracranial pathologies, preventing misdiagnosis and ensuring accurate analysis before further glioma assessment. Methods A cohort of 1280 patients with a variety pathologies was included. It comprised 218 (mean age 54.76 ± 13.74 years; 136 males, 82 females), 514 brain metastases 59.28 12.36 228 286 366 inflammatory lesions 41.94 14.57 142 224 99 intracerebral hemorrhages...
Objectives Deep learning for body composition analysis (BCA) is gaining traction in clinical research, offering rapid and automated ways to measure features like muscle or fat volume. However, most current methods prioritize computed tomography (CT) over magnetic resonance imaging (MRI). This study presents a deep approach automatic BCA using MR T2-weighted sequences. Methods Initial segmentations (10 regions 4 parts) were generated by mapping CT from organ (BOA) model synthetic images...
Purpose: Idiopathic pulmonary fibrosis (IPF) is the most common interstitial lung disease, with a median survival time of 2 to 5 years. The focus this study establish novel imaging biomarker. Materials and Methods: In study, 79 patients (19% female) age 70 years were studied retrospectively. Fully automated body composition analysis (BCA) features (bone, muscle, total adipose tissue, intermuscular, intramuscular tissue) combined into Sarcopenia, Fat, Myosteatosis indices compared between...
Non-specific interstitial pneumonia (NSIP) is an lung disease that can result in end-stage fibrosis. We investigated the influence of body composition and pulmonary fat attenuation volume (CTpfav) on overall survival (OS) NSIP patients.
The aim of the study was to evaluate impact newly developed Similar patient search (SPS) Web Service, which supports reading complex lung diseases in computed tomography (CT), on diagnostic accuracy residents. SPS is an image-based engine for pre-diagnosed cases along with related clinical reference content ( https://eref.thieme.de ). database constructed using 13,658 annotated regions interest (ROIs) from 621 patients, comprising 69 diseases. For validation, 50 CT scans were evaluated by...
Percutaneous image-guided tumor ablation of liver malignancies has become an indispensable therapeutic procedure. The aim this evaluation the prospectively managed multinational registry voluntary German Society for Interventional Radiology and Minimally Invasive Therapy (DeGIR) was to analyze its use, technical success, complications in clinical practice.
Abstract A novel software, DiffTool, was developed in-house to keep track of changes made by board-certified radiologists preliminary reports created residents and evaluate its impact on radiological hands-on training. Before (t 0 ) after 2−4 the deployment 18 (median age: 29 years; 33% female) completed a standardized questionnaire professional At t participants were also requested respond three additional questions software. Responses recorded via six-point Likert scale ranging from 1...
Abstract Background Primary central nervous system lymphomas (PCNSL) pose a challenge as they may mimic gliomas on magnetic resonance imaging (MRI) imaging, compelling precise differentiation for appropriate treatment. This study focuses developing an automated MRI-based workflow to distinguish between PCNSL and gliomas. Methods MRI examinations of 240 therapy-naive patients (141 males 99 females, mean age: 55.16 years) with cerebral PCNSLs (216 24 PCNSLs), each comprising non-contrast...
Cystic fibrosis bone disease (CFBD) is a common comorbidity in adult people with cystic (pwCF), resulting an increased risk of fractures. This study evaluated the capacity artificial intelligence (AI)-assisted low-dose chest CT (LDCT) opportunistic screening for detecting low mineral density (BMD) pwCF.
Recently, deep learning (DL)-based methods have been proposed for the computational reduction of gadolinium-based contrast agents (GBCAs) to mitigate adverse side effects while preserving diagnostic value. Currently, two main challenges these approaches are accurate prediction enhancement and synthesis realistic images. In this work, we address both by utilizing signal encoded in subtraction images pre-contrast post-contrast image pairs. To avoid any noise or artifacts solely focus on...
Background In a previous study from our group, CT biomarkers derived fully automated body composition analysis (BCA) correlated with overall survival in patients idiopathic pulmonary fibrosis (IPF). The aim of the present was to verify whether BCA also NSIP.
Abstract Background Cardiovascular adverse events including myocarditis associated with immune checkpoint inhibitor (ICI) therapy remain a challenge in clinical practice. Diagnostic assessment of ICI-related (ICI-M) is challenging due to variable phenotype, confounding effects and limited sensitivity diagnostic tools. Cardiac magnetic resonance imaging (CMR) used diagnose non-ICI myocarditis, but evidence on low, particularly patients discrete phenotype. Here, we aim assess the impact CMR...
Zielsetzung Das Ziel dieser Studie war es, die Voraussagekraft einer vollautomatisierten Analyse der Körperzusammensetzung (BCA) in Bezug auf das Gesamtüberleben von Patienten mit idiopathischer pulmonaler Fibrose (IPF) zu überprüfen.
<b>Background:</b> Idiopathic pulmonary fibrosis (IPF) is the most common interstitial lung disease with a median survival time of 2.5 years without treatment. For this rare disease, there still lack validated biomarkers for mortality risk assessment. Over last few years, body composition analysis (BCA) has emerged as predictive tool in various diseases. <b>Aim:</b> To inverstigate whether fully automated BCA derived markers correlate overall (OS) patients IPF. <b>Patients and Methods:</b>...