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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, 70.7 % men) underwent chest CT to assess PE. We investigated PE's association with 30-day mortality, ICU admission, and the need for mechanical ventilation., Results: PE was detected in 31.5 % of patients, showing a significant correlation with 30-day mortality (47.5 % in non-survivors vs. 27.3 % in survivors, p < 0.001), with a hazard ratio of 2.22 (95 % CI 1.65-2.99, p < 0.001). No significant association was found between PE volume or density and mortality. ICU admissions were noted in 46.8 % of patients, while mechanical ventilation was required for 26.7 %., Conclusion: Pleural effusion is present in a significant portion of COVID-19 patients and independently predicts increased 30-day mortality, underscoring its value as a prognostic marker. Its identification, irrespective of volume or density, should be a priority in radiological reports to guide clinical decision-making., Competing Interests: Declaration of competing interest The authors have no competing interests to declare that are relevant to the content of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

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. We produced segmentation masks for both the original and augmented scans, and we calculated the alignment metrics between these segmentation masks., Results: Our results demonstrate strong correlation between the segmentation quality of the original scan and the average alignment between the masks of the original and augmented CT scans. These results were further validated by supporting metrics, including the coefficient of variance and the average symmetric surface distance, indicating that agreement with augmented-scan segmentation masks is a valid proxy for segmentation quality., Conclusions: Overall, our framework offers a pipeline for evaluating segmentation performance without relying on manually labeled ground truth data, establishing a foundation for future advancements in automated medical image analysis.

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). The acquired sample included 1379 patients, 389 (28.2%) women and 990 (71.8%) men. In each case, chest CT was analyzed and pectoralis muscle area and density were calculated. Data were analyzed by means of descriptive statistics. Group differences were calculated using the Mann-Whitney-U test and Fisher's exact test. Univariable and multivariable logistic regression analyses were performed., Results: The 30-day mortality was 17.9%. Using median values as thresholds, low pectoralis muscle density (LPMD) was a strong and independent predictor of 30-day mortality, HR=2.97, 95%-CI: 1.52-5.80, p=0.001. Also in male patients, LPMD predicted independently 30-day mortality, HR=2.96, 95%-CI: 1.42-6.18, p=0.004. In female patients, the analyzed pectoralis muscle parameters did not predict 30-day mortality. For patients under 60 years of age, LPMD was strongly associated with 30-day mortality, HR=2.72, 95%-CI: 1.17;6.30, p=0.019. For patients over 60 years of age, pectoralis muscle parameters could not predict 30-day mortality., Conclusion: In male patients with COVID-19, low pectoralis muscle density is strongly associated with 30-day mortality and can be used for risk stratification. In female patients with COVID-19, pectoralis muscle parameters cannot predict 30-day mortality., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

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. However, very few of these, if any, find their way into routine clinical use, a discrepancy that reflects the divide between AI research and successful AI translation. The goal of this paper is to give an overview of the intersection of AI and medical imaging landscapes. We also want to inform the readers about the importance of using standards in their radiology workflow and the challenges associated with deploying AI models in the clinical workflow. The main focus of this paper is to examine the existing condition of radiology workflow and identify the challenges hindering the implementation of AI in hospital settings. This report reflects extensive weekly discussions and practical problem-solving expertise accumulated over multiple years by industry experts, imaging informatics professionals, research scientists, and clinicians. To gain a deeper understanding of the requirements for deploying AI models, we introduce a taxonomy of AI use cases, supplemented by real-world instances of AI model integration within hospitals. We will also explain how the need for AI integration in radiology can be addressed using the Medical Open Network for AI (MONAI). MONAI is an open-source consortium for providing reproducible deep learning solutions and integration tools for radiology practice in hospitals., (©Vikash Gupta, Barbaros Erdal, Carolina Ramirez, Ralf Floca, Bradley Genereaux, Sidney Bryson, Christopher Bridge, Jens Kleesiek, Felix Nensa, Rickmer Braren, Khaled Younis, Tobias Penzkofer, Andreas Michael Bucher, Ming Melvin Qin, Gigon Bae, Hyeonhoon Lee, M Jorge Cardoso, Sebastien Ourselin, Eric Kerfoot, Rahul Choudhury, Richard D White, Tessa Cook, David Bericat, Matthew Lungren, Risto Haukioja, Haris Shuaib. Originally published in JMIR AI (https://ai.jmir.org), 09.12.2024.)

Child maltreatment is associated with respiratory sinus arrhythmia (RSA) dysregulation, a physiological indicator of emotion regulation that predicts elevated posttraumatic stress disorder (PTSD) symptoms and may be a mechanism of action for exposure-based therapies, such as trauma-focused cognitive behavioral therapy (TF-CBT). Animal-assisted therapy (AAT) has been proposed as an adjunct to TF-CBT for improving emotion regulation following maltreatment. The current study reports findings from a randomized controlled feasibility trial (N = 33; M age = 11.79 years, SD = 3.08; 63.6% White; 66.7% female) that measured youths' resting RSA, RSA reactivity, and RSA recovery in response to a pretreatment laboratory challenge. We tested whether (a) lower pretreatment resting RSA was associated with blunted RSA during the challenge; (b) either of the pretreatment RSA dimensions predicted more severe pretreatment PTSD symptoms; and (c) either of the pretreatment RSA dimensions predicted less severe posttreatment PTSD symptoms and, as an exploratory aim, whether this was moderated by treatment group (i.e., TF-CBT vs. TF-CBT + AAT). Results from multiple linear regression indicated that, after controlling for pretreatment symptom severity, there was a large effect size for higher resting RSA predicting less severe caregiver-reported posttreatment PTSD symptoms, β = -.52, p = .058, and higher RSA during recovery predicting less severe child-reported posttreatment PTSD symptoms, β = -.70, p = .056, although these findings were not significant. These preliminary results offer important insights for future studies to investigate how the ability to regulate RSA informs which children need additional support to benefit from psychotherapeutic treatment., (© 2024 The Authors. Journal of Traumatic Stress published by Wiley Periodicals LLC on behalf of International Society for Traumatic Stress Studies.)

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. We therefore investigated the value of quantitative measurements on a highly accelerated T2 mapping sequence, in order to establish a threshold to differentiate benign from malignant lesions. For this purpose, we evaluated a novel, highly accelerated T2 mapping research sequence that enables high-resolution image acquisition with short acquisition times in everyday clinical practice. In this retrospective single-center study, we included 54 patients with clinically indicated MRI of the prostate and biopsy-confirmed carcinoma (n = 37) or exclusion of carcinoma (n = 17). All patients had received a standard of care biopsy of the prostate, results of which were used to confirm or exclude presence of malignant lesions. We used the linear mixed-effects model-fit by REML to determine the difference between mean values of cancerous tissue and healthy tissue. We found good differentiation between malignant lesions and normal appearing tissue in the peripheral zone based on the mean T2 value. Specifically, the mean T2 value for tissue without malignant lesions was (151.7 ms [95% CI: 146.9-156.5 ms] compared to 80.9 ms for malignant lesions [95% CI: 67.9-79.1 ms]; p < 0.001). Based on this assessment, a limit of 109.2 ms is suggested. Aditionally, a significant correlation was observed between T2 values of the peripheral zone and PI-RADS scores (p = 0.0194). However, no correlation was found between the Gleason Score and the T2 relaxation time. Using REML, we found a difference of -82.7 ms in mean values between cancerous tissue and healthy tissue. We established a cut-off-value of 109.2 ms to accurately differentiate between malignant and non-malignant prostate regions. The addition of T2 mapping sequences to routine imaging could benefit automated lesion detection and facilitate contrast-free multiparametric MRI of the prostate., Competing Interests: Declarations. Ethics Approval: For this IRB approved (No. 19-299), retrospective case-control study, the hospital's PACS was searched by an independent investigator for prostate MRIs between 08/2018 and 07/2019. Consent to Participate: For the retrospective case-control study, no consent to participate was needed. Consent to Publish: For the anonymized data, no consent to publish is needed. Competing Interests: R.S. and T.H. are employed by Siemens Healthineers. T.P. receives funding from Berlin Institute of Health (Advanced Clinician Scientist Grant, Platform Grant), Ministry of Education and Research (BMBF, 01KX2021 (RACOON), 01KX2121 („NUM 2.0“, RACOON), 68GX21001A, 01ZZ2315D), German Research Foundation (DFG, SFB 1340/2), European Union (H2020, CHAIMELEON: 952172, DIGITAL, EUCAIM:101100633) and reports research agreements (no personal payments, outside of submitted work) with AGO, Aprea AB, ARCAGY-GINECO, Astellas Pharma Global Inc. (APGD), Astra Zeneca, Clovis Oncology, Inc., Holaira, Incyte Corporation, Karyopharm, Lion Biotechnologies, Inc., MedImmune, Merck Sharp & Dohme Corp, Millennium Pharmaceuticals, Inc., Morphotec Inc., NovoCure Ltd., PharmaMar S.A. and PharmaMar USA, Inc., Roche, Siemens Healthineers, and TESARO Inc., and fees for a book translation (Elsevier B.V.). A.M.B.: Bayer, Guebert, Siemens Healthineers (Consulting fees and travel Support)., (© 2024. The Author(s).)

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.CT images of patients with confirmed intussusception were retrospectively acquired between 01/2008 and 12/2022. Available follow-up images and medical health records were evaluated to identify various imaging features, the cause of intussusception, and treatment strategies. Imaging interpretation was conducted by two blinded radiologists. A third radiologist was consulted in cases of disagreement.A total of 71 consecutive patients were included in this study (42 males, 29 females) with a median age of 56 years (interquartile range: 40.5-73.8 years). Enteroenteric intussusceptions in the small bowel were the most common type observed in adult patients. In contrast, colocolic intussusception was more frequently associated with malignancy, and this association was statistically significant (p < 0.05). Among the malignant tumors, adenocarcinoma was the most common, followed by metastases and lymphoma. Additionally, bowel obstruction and wall thickening were significantly correlated with malignancy (p < 0.05). The high negative predictive values (NPVs) and high specificities for ileus (NPV 88.5%, specificity 82.1%), bowel wall thickening (NPV 90.9%, specificity 71.4%), and acute abdomen (NPV 84.6%, specificity 78.8%) suggest that the absence of these features strongly predicts a low probability of malignancy in cases of adult intussusception.Active surveillance with follow-up exams is suitable for asymptomatic and transient intussusception when imaging features suggest a low likelihood of a neoplasm. Additionally, malignancy predictors such as ileus and thickening of the bowel wall in the affected segment could guide tailored treatment. Surgical interventions are essential for symptomatic cases, with adenocarcinoma being the most common malignancy found in colocolic intussusceptions.Intussusception in adults is rare and is often associated with underlying tumors, particularly in colocolic intussusceptions. Key imaging predictors for malignancy include bowel obstruction, wall thickening in the affected segment, and the presence of acute abdomen, with high NPVs and specificities indicating low malignancy risk when these features are absent. Active surveillance is recommended for asymptomatic cases with low neoplasm probability, while surgical intervention is the method of choice for symptomatic patients. · Reschke P, Le Hong QA, Gruenewald LD et al. Malignancy predictors and treatment strategies for adult intestinal intussusception. Fortschr Röntgenstr 2024; DOI 10.1055/a-2434-7932., Competing Interests: C.B. received speaking fees from Siemens Healthineers. I.Y. received a speaking fee from Siemens Healthineers., (Thieme. All rights reserved.)

Background/Objectives : 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). Methods : 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. Results : Overall, 35% progressed to mCRPC biochemically vs. 23% radiographically vs. 42% biochemically + radiographically. The PSA nadir in mHSPC (1.4 vs. 0.4 vs. 0.8 ng/mL) and PSA level at mCRPC progression (15 vs. 2 vs. 21 ng/mL, both p ≤ 0.01) were significantly higher for biochemical vs. radiographic vs. both progressed patients. In PFS and OS analyses, no significant differences were observed among all three compared groups. In the comparison of the staging used for progression to mCRPC, 67% received conventional vs. 33% PSMA-PET/CT, with higher metastatic burden in mHSPC and osseous lesions in mCRPC for conventionally staged patients (both p < 0.01). In PFS (15.3 vs. 10.1 months, hazard ratio [HR]: 0.75) and OS analyses (52.6 vs. 34.3 months, HR: 0.61, both p < 0.05), PSMA-PET/CT harbored better prognosis; however, this did not hold after multivariable adjustment. Similar results were observed for further analyses in second- and third-line mCRPC or patients with a PSA level of ≥2 ng/mL. Conclusions : The cause of progression to mCRPC seems not to influence cancer-control outcomes, despite important baseline tumor characteristic differences. The PSMA-PET/CT staging modality might be associated with better PFS and OS outcomes, possibly due to its more sensitive detection of progression or new metastatic lesions.

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. The study also compared the prevalence of ossa sesamoidea and non-fusion of the major and minor horns of the hyoid bone between both diagnostic methods., Results: The detection of fractures showed a very good correlation between autopsy and pmCT results (κ = 0.905), with the McNemar test showing no statistically significant difference between the two methods. PmCT identified 28 sesamoid bones, 45 non-fusions of the major horns, and 47 non-fusions of the minor horns of the hyoid bone, compared to four, six, and zero, respectively, identified by autopsy ( p < 0.0001)., Conclusions: Autopsy and pmCT findings correlate well and can be used in a complementary manner. PmCT is superior to autopsy in identifying dislocations and detecting anatomical variations in the laryngohyoid complex, which can lead to misinterpretations during autopsy. Therefore, we do not advocate replacing autopsy with pmCT but propose using a structured workflow, including our standardized reporting template, for evaluating lesions in the laryngohyoid complex.

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., Materials and Methods:  The MEDLINE library, Cochrane, and SCOPUS databases were screened for associations between CT-defined features and mortality in COVID-19 patients up to June 2021. In total, 21 studies were included in the present analysis. The quality of the included studies was assessed by the Newcastle-Ottawa Scale. The meta-analysis was performed using RevMan 5.3. Heterogeneity was calculated by means of the inconsistency index I2. DerSimonian and Laird random-effect models with inverse variance weights were performed without any further correction., Results:  The included studies comprised 4621 patients. The prevalence of thoracic lymphadenopathy varied between 1 % and 73.4 %. The pooled prevalence was 16.7 %, 95 % CI = (15.6 %; 17.8 %). The hospital mortality was higher in patients with thoracic lymphadenopathy (34.7 %) than in patients without (20.0 %). The pooled odds ratio for the influence of thoracic lymphadenopathy on mortality was 2.13 (95 % CI = [1.80-2.52], p < 0.001)., Conclusion:  The prevalence of thoracic lymphadenopathy in COVID-19 is 16.7 %. The presence of thoracic lymphadenopathy is associated with an approximately twofold increase in the risk for hospital mortality in COVID-19., Key Points:   · The prevalence of lymphadenopathy in COVID-19 is 16.7 %.. · Patients with lymphadenopathy in COVID-19 have a higher risk of mortality during hospitalization.. · Lymphadenopathy nearly doubles mortality and plays an important prognostic role.., Citation Format: · Bucher AM, Sieren M, Meinel F et al. Prevalence and prognostic role of thoracic lymphadenopathy in Covid-19. Fortschr Röntgenstr 2024; DOI: 10.1055/a-2293-8132., Competing Interests: R. K.: Consulting fees from Boston Scientific, Bristol Myers Squibb, Guerbet, Roche, and Sirtex; payment for lectures from BTG, Eisai, Guerbet, Ipsen, Roche, Siemens, Sirtex, and MSD Sharp & Dohme; chair of the European Society of Radiology Audit and Standards Subcommittee.A.M.B.: Bayer, Guebert, Siemens Healthineers (Consulting fees and travel Support) T.P.: Fördermittel vom Berlin Institute of Health (Advanced Clinician Scientist Grant, Platform Grant), Bundesministerium für Bildung und Forschung (BMBF, 01KX2021 (RACOON), 01KX2121 (“NUM 2. 0” RACOON), 68GX21001A, 01ZZ2315D), Deutsche Forschungsgemeinschaft (DFG, SFB 1340/2), Europäische Union (H2020, CHAIMELEON: 952172, DIGITAL, EUCAIM:101100633) und berichtet über Forschungsvereinbarungen (keine persönlichen Zuwendungen, außerhalb der eingereichten Arbeit) mit AGO, Aprea AB, ARCAGY-GINECO, Astellas Pharma Global Inc. (APGD), Astra Zeneca, Clovis Oncology, Inc, Holaira, Incyte Corporation, Karyopharm, Lion Biotechnologies, Inc, MedImmune, Merck Sharp & Dohme Corp, Millennium Pharmaceuticals, Inc, Morphotec Inc, NovoCure Ltd, PharmaMar S.A. und PharmaMar USA, Inc, Roche, Siemens Healthineers und TESARO Inc, sowie Honorare für eine Buchübersetzung (Elsevier B.V.)., (Thieme. All rights reserved.)

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., Methods: Our study included 132 thoracic CT scans from clinical practice, annotated by 13 radiologists. In three iterative training experiments, we aimed to improve and accelerate segmentation of the heart and mediastinum. Each experiment started with manual segmentation of 5-25 CT scans, which served as training data for a nnU-Net. Further iterations incorporated AI pre-segmentation and human correction to improve accuracy, accelerate the annotation process, and reduce human involvement over time., Results: Results showed consistent improvement in AI model quality with each iteration. Resampled datasets improved the Dice similarity coefficients for both the heart (DCS 0.91 [0.88; 0.92]) and the mediastinum (DCS 0.95 [0.94; 0.95]). Our AI models reduced human interaction time by 50 % for heart and 70 % for mediastinum segmentation in the most potent iteration. A model trained on only five datasets achieved satisfactory results (DCS > 0.90)., Conclusions: The iterative training workflow provides an efficient method for training AI-based segmentation models in multi-center studies, improving accuracy over time and simultaneously reducing human intervention. Future work will explore the use of fewer initial datasets and additional pre-processing methods to enhance model quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

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., Methods: This single-center, prospective, intraindividual, observational study assesses cardiac function, global and segment-based strains, and tissue characterization in 29 age- and sex-matched children with PCS and healthy children using a 3 T magnetic resonance imaging (MRI)., Results: Cardiac MRI was carried out over 36.4 ± 24.9 weeks post-COVID infection. The study cohort has an average age of 14.0 ± 2.8 years, for which the majority of individuals experience from fatigue, concentration disorders, dyspnea, dizziness, and muscle ache. Children with PSC in contrast to the control group exhibited elevated heart rate (83.7 ± 18.1 beats per minute vs 75.2 ± 11.2 beats per minute, P = 0.019), increased indexed right ventricular end-diastolic volume (95.2 ± 19.2 mlm -2 vs 82.0 ± 21.5 mlm -2 , P = 0.018) and end-systolic volume (40.3 ± 7.9 mlm -2 vs 34.8 ± 6.2 mlm -2 , P = 0.005), and elevated basal and midventricular T1 and T2 relaxation times ( P < 0.001 to P = 0.013). Based on the updated Lake Louise Criteria, myocardial inflammation is present in 20 (69%) children with PCS. No statistically significant difference was observed for global strains., Conclusions: Cardiac MRI revealed altered right ventricular volumetrics and elevated T1 and T2 mapping values in children with PCS, suggestive for a diffuse myocardial inflammation, which may be useful for the diagnostic workup of PCS in children., Competing Interests: Conflicts of interest and sources of funding: Ministry for Science and Culture of Lower Saxony in Germany (grant number: ZN3894); Radiological Cooperative Network (RACOON) of the Network University Medicine (NUM) under the BMBF grant numbers 01KX2021 and 01KX2121., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.)

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). The acquired sample comprises 1197 patients, 363 (30.3%) women and 834 (69.7%) men. In every case, chest computed tomography was analyzed for PE. Data about 30-day mortality, need for mechanical ventilation and need for intensive care unit (ICU) admission were collected. Data were evaluated by means of descriptive statistics. Group differences were calculated with Mann-Whitney test and Fisher exact test. Uni-and multivariable regression analyses were performed., Results: Overall, 46.4% of the patients were admitted to ICU, mechanical lung ventilation was performed in 26.6% and 30-day mortality was 24%. PE was identified in 159 patients (13.3%). The presence of PE was associated with 30-day mortality: HR= 1.54, CI 95% (1.05; 2.23), p = 0.02 (univariable analysis), and HR= 1.60, CI 95% (1.03; 2.48), p = 0.03 (multivariable analysis). Furthermore, density of PE was associated with the need for intubation (OR=1.02, CI 95% (1.003; 1.05), p = 0.03) and the need for ICU admission (OR=1.03, CI 95% (1.005; 1.05), p = 0.01) in univariable regression analysis. The presence of PE was associated with 30-day mortality in male patients, HR= 1.56, CI 95%(1.01-2.43), p = 0.04 (multivariable analysis). In female patients, none of PE values predicted clinical outcomes., Conclusion: The prevalence of PE in Covid 19 is 13.3%. PE is an independent predictor of 30-day mortality in male patients with Covid 19. In female patients, PE plays no predictive role., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

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. We show that it is possible to enhance generalizability without huge resources by carefully curating the dataset and combining machine learning with medical expertise. Multiple machine learning techniques (self-supervision (SSL), attention (A), and data augmentation (DA)) are used to train a fast and fully-automated lung lobe segmentation model based on 2D U-Net. Our study involved evaluating these techniques on a diverse dataset collected under the RACOON project, encompassing 100 CT chest scans from patients with bacterial, viral, or SARS-CoV2 infections. We compare our model to a baseline U-Net trained on the same dataset. Our approach significantly improved segmentation accuracy (Dice score of 92.8% vs. 82.3%, p < 0.001). Moreover, our model achieved state-of-the-art performance (Dice score of 92.8% vs. 90.8% for the literature's state-of-the-art, p = 0.102) with reduced training examples (69 vs. 231 CT Scans). Among the techniques, data augmentation with expert knowledge displayed the most significant impact, enhancing the Dice score by +0.056. Notably, these enhancements are not limited to lobe segmentation but can be seamlessly integrated into various medical imaging segmentation tasks, demonstrating their versatility and potential for broader applications.

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. Additionally, it offers the opportunity of maintaining and keeping the data locally. Thus, data safety issues can be avoided because patient data must not be shared. Machine learning models are trained on local data by sharing the model and through an established network. In addition to commercial applications, there are also numerous academic and customized implementations of network infrastructures available. The configuration of these networks primarily differs, yet adheres to a standard framework composed of fundamental components. In this technical note, we propose basic infrastructure requirements for data governance, data science workflows, and local node set-up, and report on the advantages and experienced pitfalls in implementing the local infrastructure with the German Radiological Cooperative Network initiative as the use case example. We show how the infrastructure can be built upon some base components to reflect the needs of a federated learning network and how they can be implemented considering both local and global network requirements. After analyzing the deployment process in different settings and scenarios, we recommend integrating the local node into an existing clinical IT infrastructure. This approach offers benefits in terms of maintenance and deployment effort compared to external integration in a separate environment (e.g., the radiology department). This proposed groundwork can be taken as an exemplary development guideline for future applications of federated learning networks in clinical and scientific environments.

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)., Results: The most frequent expectations were "joy at work" (97%) and a "good working atmosphere" (97%), which were considered fulfilled by at least 78%. The expectation of a "structured residency within the regular time interval" (79%) was more frequently judged fulfilled by senior physicians (83%, odds ratio (OR) 4.31 [95% confidence interval (95% CI) 1.95-9.52]), chief physicians (85%, 6.81 [95% CI 1.91-24.29]), and radiologists outside the hospital (88%, 7.59 [95% CI 2.40-24.03]) than by residents (68%). Exhaustion was most common among residents (physical exhaustion: 38%; emotional exhaustion: 36%), in-hospital specialists (29%; 38%), and senior physicians (30%; 29%). In contrast to paid extra hours, unpaid extra hours were associated with physical exhaustion (5-10 extra hours: OR 2.54 [95% CI 1.54-4.19]). Fewer opportunities to shape the work environment were related to a higher probability of physical (2.03 [95% CI 1.32-3.13]) and emotional (2.15 [95% CI 1.39-3.33]) exhaustion., Conclusions: While most radiologists enjoy their work, residents wish for more training structure. Ensuring payment of extra hours and employee empowerment may help preventing burnout in high-risk groups., Key Points: • Most important work expectations of radiologists who work in Germany are "joy at work," a "good working atmosphere," "support for further qualification," and a "structured residency within the regular time interval," with the latter containing potential for improvement according to residents. • Physical and emotional exhaustion are common at all career levels except for chief physicians and for radiologists who work outside the hospital in ambulatory care. • Exhaustion as a major burnout criterion is associated with unpaid extra hours and reduced opportunities to shape the work environment., (© 2023. The Author(s).)

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. The 44 questions covered six distinct areas from personal working conditions to the characterization of the IR department, training conditions, role of women in IR, and attendance at congresses/external training.A total of 330 participants completed the questionnaire. 77 % of participants expressed a high interest in IR, and 47 % could even imagine subspecializing in interventional radiology. Most institutions provided the necessary learning conditions and infrastructure. The rate of overall satisfaction with IR training conditions was 45 % (vs. a dissatisfaction rate of 39 %). However, females showed a lower satisfaction rate with their training environment than male participants (28 % vs. 51 %; P = 0.06). Positive correlations with work satisfaction were found for the presence and duration of the IR rotation, the number of partly independently/mentored performed interventions, and structured feedback. Moreover, the need for a structured training curriculum was expressed by 67 % of participants.Radiological residents and young radiologists expressed a high interest in interventional radiology, and they rate the infrastructure of German hospitals regarding IR as sufficient. However, they expressed the need for consistent IR rotations and better-structured resident and postgraduate education (curricula & interviews).Interest in interventional radiology among radiological residents and young radiologists in Germany is high, but satisfaction with interventional radiology training leaves room for improvement. The most frequently mentioned aspects that can improve IR training were · organized rotations of at least 6 months. · structured curriculums with face-to-face feedback. · structured guidance by senior interventionists during procedures. CITATION FORMAT: · Sieren M, Katoh M, Mahnken AH et al. Work and Training Conditions of German Residents and Young Radiologists in Interventional Radiology - A Nationwide Survey. Fortschr Röntgenstr 2022; 194: 1346 - 1357., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Trauma-Focused Cognitive-Behavioral Therapy (TF-CBT) is a well-established treatment for pediatric posttraumatic stress disorder (PTSD). Animal-assisted therapy (AAT) has been proposed as an adjunct to TF-CBT that may improve treatment effects through enhanced targeting of affect regulation, as indexed by specific changes in the respiratory sinus arrhythmia (RSA). The current study reports results from a randomized controlled feasibility trial (N = 33; M age  = 11.79 [SD = 3.08]; 64% White; 67% female) that measured RSA during Sessions 1, 4, 8, and 12 of a twelve-session TF-CBT protocol and tested whether: 1) TF-CBT + AAT achieved higher average RSA amplitudes relative to TF-CBT alone, and 2) RSA regulation, defined as less variability around person-specific RSA slopes during treatment, explained variation in post-treatment PTSD symptoms. Multilevel modeling failed to support an effect for TF-CBT + AAT on RSA amplitudes (δ 001  = 0.08, p = 0.844). However, regardless of treatment condition, greater RSA withdrawal was observed within Sessions 4 (γ 11  = -.01, p < .001) and 12 (γ 13  = -.01, p = .015) relative to the Session 1 baseline. The average level of RSA amplitude in Session 8 was also significantly lower compared to Session 1 (γ 02  = -0.70, p = .046). Intraindividual regression models demonstrated that greater RSA regulation predicted improved PTSD symptoms at post-treatment after adjusting for pre-treatment levels (b 3  = 20.00, p = .012). These preliminary results offer support for future confirmatory trials testing whether affect regulation, as indexed by changes in RSA, is a mechanism of action for TF-CBT in the treatment of pediatric PTSD., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

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. Based on the survey results mint Lesion™, developed by Mint Medical and used at all project sites within RACOON, was selected as the "Electronic Data Capture" (EDC) system for CODEX. Moreover, to avoid duplicate entry of GECCO data into both EDC systems, an early effort was made to consider a collaborative and efficient technical approach to reduce the workload for the medical documentalists. As a first effort we present a preliminary technical concept representing the current and possible future data workflow of CODEX and RACOON. This concept includes a software component to synchronize GECCO data sets between the two EDC systems using the HL7 FHIR standard. Our first approach of a collaborative use of an EDC system and its medical documentalists could be beneficial in combination with the presented synchronization component for all participating project sites of CODEX and RACOON with regard to an overall reduced documentation workload.

This clinical trial examined animal-assisted therapy (AAT) as an adjunct to Trauma-Focused Cognitive-Behavioral Therapy (TF-CBT) for abused youth with posttraumatic stress disorder (PTSD). Youth between the ages of 6 and 17 ( M = 11.79, SD = 3.08) were randomized to receive standard TF-CBT or TF-CBT with adjunctive AAT (TF-CBT+AAT) employing retired service dogs. Feasibility metrics evaluating the addition of AAT were collected in addition to common clinical outcomes evaluated in TF-CBT trials. The inclusion of AAT increased the number of potential participants who declined participation and there were no noted benefits for treatment retention or satisfaction with services. Analyses showed that the inclusion of AAT did not enhance improvement of PTSD symptom severity (β = .90, t = .94, p = .351) or a number of other outcomes. On the contrary, there were indications from analyses and clinician feedback that AAT may have attenuated improvement in many cases. This study identified a number of important feasibility considerations in the design of studies testing AAT. However, the results examining clinical outcomes suggest that the inclusion of AAT with TF-CBT in the treatment of maltreated youth with PTSD is not warranted at this time.

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. Questions of approximation, yes/no questions, and Likert scales were used., Results: During the first/second wave, 70 % (86/123)/43 % (45/104) of inpatient and 26 % (17/66)/10 % (5/52) of outpatient head physicians agreed that they received financial support from the authorities but the majority rated the financial support as insufficient. During the first and second wave, 33 % (8/24) and 80 % (16/20) of outpatient technicians agreed that they were adequately provided with personal protective equipment. The perceived lack of personal protective equipment improved for all participants during the second wave. Inpatient [outpatient] technicians perceived an increased workload in the first and second wave: 72 % (142/198) [79 % (19/24)] and 84 % (146/174) [80 % (16/20)]., Conclusion: Technicians seem increasingly negatively affected by the COVID-19 pandemic in Germany. Financial support by the competent authorities seems to be in need of improvement., Key Points: · The accessibility of personal protective equipment resources improved in the second wave.. · In particular, radiology technicians seem increasingly negatively affected by the COVID-19 pandemic.. · Financial and consulting support from the government could be improved.., Citation Format: · Bernatz S, Afat S, Othman AE et al. Impact of the COVID-19 Pandemic on Radiology in Inpatient and Outpatient Care in Germany: A Nationwide Survey Regarding the First and Second Wave. Fortschr Röntgenstr 2022; 194: 70 - 82., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)