PURPOSE: Image analysis is one of the most promising applications of artificial intelligence (AI) in health care, potentially improving prediction, diagnosis, and treatment of diseases. Although scientific advances in this area critically depend on the accessibility of large-volume and high-quality data, sharing data between institutions faces various ethical and legal constraints as well as organizational and technical obstacles. METHODS: The Joint Imaging Platform (JIP) of the German Cancer Consortium (DKTK) addresses these issues by providing federated data analysis technology in a secure and compliant way. Using the JIP, medical image data remain in the originator institutions, but analysis and AI algorithms are shared and jointly used. Common standards and interfaces to local systems ensure permanent data sovereignty of participating institutions. RESULTS: The JIP is established in the radiology and nuclear medicine departments of 10 university hospitals in Germany (DKTK partner sites). In multiple complementary use cases, we show that the platform fulfills all relevant requirements to serve as a foundation for multicenter medical imaging trials and research on large cohorts, including the harmonization and integration of data, interactive analysis, automatic analysis, federated machine learning, and extensibility and maintenance processes, which are elementary for the sustainability of such a platform. CONCLUSION: The results demonstrate the feasibility of using the JIP as a federated data analytics platform in heterogeneous clinical information technology and software landscapes, solving an important bottleneck for the application of AI to large-scale clinical imaging data.

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.

The COVID-19 pandemic has worldwide individual and socioeconomic consequences. Chest computed tomography has been found to support diagnostics and disease monitoring. A standardized approach to generate, collect, analyze, and share clinical and imaging information in the highest quality possible is urgently needed. We developed systematic, computer-assisted and context-guided electronic data capture on the FDA-approved mint Lesion^TM software platform to enable cloud-based data collection and real-time analysis. The acquisition and annotation include radiological findings and radiomics performed directly on primary imaging data together with information from the patient history and clinical data. As proof of concept, anonymized data of 283 patients with either suspected or confirmed SARS-CoV-2 infection from eight European medical centers were aggregated in data analysis dashboards. Aggregated data were compared to key findings of landmark research literature. This concept has been chosen for use in the national COVID-19 response of the radiological departments of all university hospitals in Germany.

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.