Evaluating Medical Image Segmentation Models Using Augmentation.

Background: Medical imagesegmentation is an essential step in both clinical and research applications, and automated segmentation models-such as TotalSegmentator-have become ubiquitous. However, robust methods for validating the accuracy of these models remain limited, and manual inspection is often necessary before the segmentation masks produced by these models can be used.

Methods: To address this gap, we have developed a novel validation framework for segmentation models, leveraging data augmentation to assess model consistency.

CT-Defined Pectoralis Muscle Density Predicts 30-Day Mortality in Hospitalized Patients with COVID-19: A Nationwide Multicenter Study.

Rationale And Objectives: The prognostic role of computed tomography (CT)-defined skeletal muscle features in COVID-19 is still under investigation. The aim of the present study was to evaluate the prognostic role of CT-defined skeletal muscle area and density in patients with COVID-19 in a multicenter setting.

Materials And Methods: This retrospective study is a part of the German multicenter project RACOON (Radiological Cooperative Network of the COVID-19 pandemic).

Current State of Community-Driven Radiological AI Deployment in Medical Imaging.

Artificial intelligence (AI) has become commonplace in solving routine everyday tasks. Because of the exponential growth in medical imaging data volume and complexity, the workload on radiologists is steadily increasing. AI has been shown to improve efficiency in medical image generation, processing, and interpretation, and various such AI models have been developed across research laboratories worldwide.

The prognostic relevance of pleural effusion in patients with COVID-19 - A German multicenter study.

Purpose: This study evaluates the prognostic significance of pleural effusion (PE) in COVID-19 patients across thirteen centers in Germany, aiming to clarify its role in predicting clinical outcomes.

Methods: In this retrospective analysis within the RACOON project (Radiological Cooperative Network of the COVID-19 pandemic), 1183 patients (29.3 % women, 70.

Assessment of Different Castration Resistance Definitions and Staging Modalities in Metastatic Castration-Resistant Prostate Cancer.

: Progression to metastatic castration-resistant prostate cancer (mCRPC) is defined either biochemically, radiographically or both. Moreover, staging for mCRPC can be performed either conventionally or with molecular imaging such as prostate-specific membrane antigen computer tomography (PSMA-PET/CT). : We relied on the Frankfurt Metastatic Cancer Database of the Prostate (FRAMCAP) database to compare progression-free (PFS) and overall survival (OS) outcomes regarding the cause of castration resistance and the staging modality used.

Real-world federated learning in radiology: hurdles to overcome and benefits to gain.

Objective: Federated Learning (FL) enables collaborative model training while keeping data locally. Currently, most FL studies in radiology are conducted in simulated environments due to numerous hurdles impeding its translation into practice. The few existing real-world FL initiatives rarely communicate specific measures taken to overcome these hurdles.

Malignancy predictors and treatment strategies for adult intestinal intussusception.

Intussusception in adult patients is a rare medical finding, which is accompanied by an underlying tumor in some cases. However, no accepted method has been established to identify patients at risk for tumor-related intussusception. This study aimed to identify imaging features as predictors for tumor-related intussusception.

Enhancing Forensic Diagnostics: Structured Reporting of Post-Mortem CT versus Autopsy for Laryngohyoid Complex Fractures in Strangulation.

Background: The purpose of this study was to establish a standardized structured workflow to compare findings from high-resolution, optimized reconstructions from post-mortem computed tomography (pmCT) with autopsy results in the detection of fractures of the laryngohyoid complex in strangulation victims.

Method: Forty-two strangulation cases were selected, and pmCT scans of the laryngohyoid complex were obtained. Both pmCT scans and autopsy reports were analyzed using a structured template and compared using Cohen's kappa coefficient (κ) and the McNemar test.

Prevalence and prognostic role of thoracic lymphadenopathy in Covid-19.

Purpose:  The prevalent coronavirus disease 2019 (COVID-19) pandemic has spread throughout the world and is considered a serious threat to global health. The prognostic role of thoracic lymphadenopathy in COVID-19 is unclear. The aim of the present meta-analysis was to analyze the prognostic role of thoracic lymphadenopathy for the prediction of 30-day mortality in patients with COVID-19.

Value of MRI - T2 Mapping to Differentiate Clinically Significant Prostate Cancer.

Standardized reporting of multiparametric prostate MRI (mpMRI) is widespread and follows international standards (Pi-RADS). However, quantitative measurements from mpMRI are not widely comparable. Although T2 mapping sequences can provide repeatable quantitative image measurements and extract reliable imaging biomarkers from mpMRI, they are often time-consuming.

Cooperative AI training for cardiothoracic segmentation in computed tomography: An iterative multi-center annotation approach.

Purpose: Radiological reporting is transitioning to quantitative analysis, requiring large-scale multi-center validation of biomarkers. A major prerequisite and bottleneck for this task is the voxelwise annotation of image data, which is time-consuming for large cohorts. In this study, we propose an iterative training workflow to support and facilitate such segmentation tasks, specifically for high-resolution thoracic CT data.

Lightweight Techniques to Improve Generalization and Robustness of U-Net Based Networks for Pulmonary Lobe Segmentation.

Lung lobe segmentation in chest CT is relevant to a wide range of clinical applications. However, existing segmentation pipelines often exhibit vulnerabilities and performance degradations when applied to external datasets. This is usually attributed to the size of the available dataset or model.

Pericardial Effusion Predicts Clinical Outcomes in Patients with COVID-19: A Nationwide Multicenter Study.

Rationale And Objectives: The prognostic role of pericardial effusion (PE) in Covid 19 is unclear. The aim of the present study was to estimate the prognostic role of PE in patients with Covid 19 in a large multicentre setting.

Materials And Methods: This retrospective study is a part of the German multicenter project RACOON (Radiological Cooperative Network of the Covid 19 pandemic).

Multiparametric Cardiovascular MRI Assessment of Post-COVID Syndrome in Children in Comparison to Matched Healthy Individuals.

Background: Post-COVID syndrome (PCS) can adversely affect the quality of life of patients and their families. In particular, the degree of cardiac impairment in children with PCS is unknown.

Objective: The aim of this study was to identify potential cardiac inflammatory sequelae in children with PCS compared with healthy controls.

Challenges in Implementing the Local Node Infrastructure for a National Federated Machine Learning Network in Radiology.

Data-driven machine learning in medical research and diagnostics needs large-scale datasets curated by clinical experts. The generation of large datasets can be challenging in terms of resource consumption and time effort, while generalizability and validation of the developed models significantly benefit from variety in data sources. Training algorithms on smaller decentralized datasets through federated learning can reduce effort, but require the implementation of a specific and ambitious infrastructure to share data, algorithms and computing time.

Work expectations, their fulfillment, and exhaustion among radiologists of all career levels: what can be learned from the example of Germany.

Objectives: To evaluate work expectations of radiologists at different career levels, their fulfillment, prevalence of exhaustion, and exhaustion-associated factors.

Methods: A standardized digital questionnaire was distributed internationally to radiologists of all career levels in the hospital and in ambulatory care via radiological societies and sent manually to 4500 radiologists of the largest German hospitals between December 2020 and April 2021. Statistics were based on age- and gender-adjusted regression analyses of respondents working in Germany (510 out of 594 total respondents).

AI support for accurate and fast radiological diagnosis of COVID-19: an international multicenter, multivendor CT study.

Objectives: Differentiation between COVID-19 and community-acquired pneumonia (CAP) in computed tomography (CT) is a task that can be performed by human radiologists and artificial intelligence (AI). The present study aims to (1) develop an AI algorithm for differentiating COVID-19 from CAP and (2) evaluate its performance. (3) Evaluate the benefit of using the AI result as assistance for radiological diagnosis and the impact on relevant parameters such as accuracy of the diagnosis, diagnostic time, and confidence.

Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation.

Automatic segmentation of ground glass opacities and consolidations in chest computer tomography (CT) scans can potentially ease the burden of radiologists during times of high resource utilisation. However, deep learning models are not trusted in the clinical routine due to failing silently on out-of-distribution (OOD) data. We propose a lightweight OOD detection method that leverages the Mahalanobis distance in the feature space and seamlessly integrates into state-of-the-art segmentation pipelines.

CODEX Meets RACOON - A Concept for Collaborative Documentation of Clinical and Radiological COVID-19 Data.

Within the scope of the two NUM projects CODEX and RACOON we developed a preliminary technical concept for documenting clinical and radiological COVID-19 data in a collaborative approach and its preceding findings of a requirement analysis. At first, we provide an overview of NUM and its two projects CODEX and RACOON including the GECCO data set. Furthermore, we demonstrate the foundation for the increased collaboration of both projects, which was additionally supported by a survey conducted at University Hospital Frankfurt.

Work and Training Conditions of German Residents and Young Radiologists in Interventional Radiology - A Nationwide Survey.

With the increasing need for minimally invasive procedures based on lower complication rates, higher patient acceptance, and technical developments, there is a growing focus on the sound interventional training of young radiologists. This survey aimed to analyze the current situation in interventional radiology (IR) training in Germany to detect shortcomings and identify areas for improvement.From November 1-30, 2020, an online questionnaire was distributed to representative radiological associations and societies with the request to forward it to radiology residents and radiologists < 40 years.

Image Fusion Improves Interdisciplinary Communication in the Treatment of Head and Neck Cancer.

Introduction: The diagnosis and therapy of oral squamous cell carcinoma (Osee) in Germany is according to guidelines and relies on interdisciplinary board meetings. Standard examination techniques are computed tomography (CT) and magnet resonance imaging (MRI). These technologies are used as objective tools for serial presentation in an oncologic board meeting.

Phantom study for comparison between computed tomography- and C-Arm computed tomography-guided puncture applied by residents in radiology.

Purpose: Comparison of puncture deviation and puncture duration between computed tomography (CT)- and C-arm CT (CACT)-guided puncture performed by residents in training (RiT).

Methods: In a cohort of 25 RiTs enrolled in a research training program either CT- or CACT-guided puncture was performed on a phantom. Prior to the experiments, the RiT's level of training, experience playing a musical instrument, video games, and ball sports, and self-assessed manual skills and spatial skills were recorded.

Impact of the COVID-19 Pandemic on Radiology in Inpatient and Outpatient Care in Germany: A Nationwide Survey Regarding the First and Second Wave.

Objectives: To find out the opinion of radiological inpatient and outpatient medical staff regarding the measures taken in relation to the COVID-19 pandemic during the first and second waves and to identify the measures that are still perceived as needing improvement.

Materials And Methods: We conducted an anonymous online survey among more than 10 000 radiologists/technicians in Germany from January 5 to January 31, 2021. A total of 862 responses (head physicians, n = 225 [inpatient doctors, n = 138; outpatient doctors, n = 84; N/A, n = 3]; radiologic personnel, n = 637 [inpatient doctor, n = 303; outpatient doctor, n = 50; inpatient technician, n = 217; outpatient technician, n = 26; N/A, n = 41]) were received.