Background and Purpose: Intracranial hemorrhage has been observed in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (COVID-19), but the clinical, imaging, and pathophysiological features of intracranial bleeding during COVID-19 infection remain poorly characterized. This study describes clinical and imaging characteristics of patients with COVID-19 infection who presented with intracranial bleeding in a European multicenter cohort. Methods: This is a multicenter retrospective, observational case series including 18 consecutive patients with COVID-19 infection and intracranial hemorrhage. Data were collected from February to May 2020 at five designated European special care centers for COVID-19. The diagnosis of COVID-19 was based on laboratory-confirmed diagnosis of SARS-CoV-2. Intracranial bleeding was diagnosed on computed tomography (CT) of the brain within one month of the date of COVID-19 diagnosis. The clinical, laboratory, radiologic, and pathologic findings, therapy and outcomes in COVID-19 patients presenting with intracranial bleeding were analyzed. Results: Eighteen patients had evidence of acute intracranial bleeding within 11 days (IQR 9–29) of admission. Six patients had parenchymal hemorrhage (33.3%), 11 had subarachnoid hemorrhage (SAH) (61.1%), and one patient had subdural hemorrhage (5.6%). Three patients presented with intraventricular hemorrhage (IVH) (16.7%). Conclusion: This study represents the largest case series of patients with intracranial hemorrhage diagnosed with COVID-19 based on key European countries with geospatial hotspots of SARS-CoV-2. Isolated SAH along the convexity may be a predominant bleeding manifestation and may occur in a late temporal course of severe COVID-19.

To quantitatively and qualitatively evaluate and compare the performance of leading large language models (LLMs), including proprietary models (GPT-4, GPT-3.5 Turbo, Claude-3-Opus, and Gemini Ultra) and open-source models (Mistral-7b and Mistral-8×7b), in simplifying 109 interventional radiology reports. Qualitative performance was assessed using a five-point Likert scale for accuracy, completeness, clarity, clinical relevance, naturalness, and error rates, including trust-breaking and post-therapy misconduct errors. Quantitative readability was assessed using Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FKGL), SMOG Index, and Dale-Chall Readability Score (DCRS). Paired t-tests and Bonferroni-corrected p-values were used for statistical analysis. Qualitative evaluation showed no significant differences between GPT-4 and Claude-3-Opus for any metrics evaluated (all Bonferroni-corrected p-values: p = 1), while they outperformed other assessed models across five qualitative metrics (p < 0.001). GPT-4 had the fewest content and trust-breaking errors, with Claude-3-Opus second. However, all models exhibited some level of trust-breaking and post-therapy misconduct errors, with GPT-4-Turbo and GPT-3.5-Turbo with few-shot prompting showing the lowest error rates, and Mistral-7B and Mistral-8×7B showing the highest. Quantitatively, GPT-4 surpassed Claude-3-Opus in all readability metrics (all p < 0.001), with a median FRE score of 69.01 (IQR: 64.88-73.14) versus 59.74 (IQR: 55.47-64.01) for Claude-3-Opus. GPT-4 also outperformed GPT-3.5-Turbo and Gemini Ultra (both p < 0.001). Inter-rater reliability was strong (κ = 0.77-0.84). GPT-4 and Claude-3-Opus demonstrated superior performance in generating simplified IR reports, but the presence of errors across all models, including trust-breaking errors, highlights the need for further refinement and validation before clinical implementation. With the increasing complexity of interventional radiology (IR) procedures and the growing availability of electronic health records, simplifying IR reports is critical to improving patient understanding and clinical decision-making. This study provides insights into the performance of various LLMs in rewriting IR reports, which can help in selecting the most suitable model for clinical patient-centered applications.

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.

Objective: To identify facilitators and barriers and derive concrete measures towards better workplace integration of migrants working in the German healthcare sector. Design: Two-centre cross-sectional quantitative online survey of experiences of discrimination among healthcare professionals with a migration history in two large German university hospitals. Participants: 251 participants fully completed the questionnaires. Main outcome measures: Experiences of discrimination and perception of inequality. Results: Fifty-five percent of migrant health workers had had at least some command of German before arriving in Germany. Members of all professional groups surveyed expressed experiences of discrimination related to language, nationality, race/ethnicity, and sex/gender. The proportions of staff with experiences of discrimination by peers differed significantly among occupational roles, with nurses and technologists having the most experiences of discrimination. The perception of inequality was reported more frequently than experiences of discrimination and had a negative impact on workplace satisfaction. Specifically, the compulsion to compete was a frequent feeling stated by participants. Conclusion: The mechanisms of discrimination and structural inequality revealed by our survey could inform specific measures, for example at the management level, to increase workplace satisfaction and attract migrant health workers in the long term.

Evaluating small coronary stents with dual-source photon-counting computed tomography: effect of different scan modes on image quality and performance in a phantom - Diagnostic and Interventional Radiology

Metal artifacts notoriously pose significant challenge in computed tomography (CT), leading to inaccuracies in image formation and interpretation. Artifact reduction tools have been designed to improve cone beam computed tomography (CBCT) image quality by reducing artifacts caused by certain high-density materials. Metal artifact reduction (MAR) tools are specific algorithms that are applied during image reconstruction to minimize or eliminate artifacts degrading CBCT images. The purpose of the study is to evaluate the effect of a MAR algorithm on image quality in CBCT performed for evaluating patients before transarterial radioembolization (TARE). We retrospectively included 40 consecutive patients (aged 65 ± 13 years; 23 males) who underwent 45 CBCT examinations (Allura FD 20, XperCT Roll protocol, Philips Healthcare, Best, The Netherlands) in the setting of evaluation for TARE between January 2017 and December 2018. Artifacts caused by coils, catheters, and surgical clips were scored subjectively by four readers on a 5-point scale (1 = artifacts affecting diagnostic information to 5 = no artifacts) using a side-by-side display of uncorrected and MAR-corrected images. In addition, readers scored tumor visibility and vessel discrimination. MAR-corrected images were assigned higher scores, indicating better image quality. The differences between the measurements with and without MAR were most impressive for coils with a mean improvement of 1.6 points (95%CI [1.5 1.8]) on the 5-point likert scale, followed by catheters 1.4 points (95%CI [1.3 1.5]) and clips 0.7 points (95%CI [0.3 1.1]). Improvements for other artifact sources were consistent but relatively small (below 0.25 points on average). Interrater agreement was good to perfect (Kendall’s W coefficient = 0.68–0.95) and was higher for MAR-corrected images, indicating that MAR improves diagnostic accuracy. A metal artifact reduction algorithm can improve diagnostic and interventional accuracy of cone beam CT in patients undergoing radioembolization by reducing artifacts caused by diagnostic catheters and coils, lowering interference of metal artifacts with adjacent major structures, and improving tumor visibility.