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A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data

Salg, G. A.; Ganten, M.-K.; Bucher, A. M.; Kenngott, H. G.; Fink, M. A.; Seibold, C.; Fischbach, R. E.; Schlamp, K.; Velandia, C. A.; Fervers, P.; Doellinger, F.; Luger, A.; Afat, S.; Merle, U.; Diener, M. K.; Pereira, P. L.; Penzkofer, T.; Persigehl, T.; Othman, A.; Heußel, C. P.; ... mehr

Abstract:
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 LesionTM 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.

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Verlagsausgabe §
DOI: 10.5445/IR/1000131867
Veröffentlicht am 30.04.2021
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2021
Sprache Englisch
Identifikator ISSN: 2398-6352
KITopen-ID: 1000131867
Erschienen in npj Digital Medicine
Verlag Nature Research
Band 4
Heft 1
Seiten 69
Nachgewiesen in Scopus
Web of Science
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