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

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.

Pulmonary thromboembolic events in COVID‐19—A systematic literature review

“…Studies are needed to develop AI‐based algorithms for the identification of patients with COVID‐19 who have additional acute/chronic pulmonary vascular conditions, and for the prediction of treatment outcomes. This will require the use of large, machine‐readable databases of imaging/clinical data such as that generated by the Radiological Cooperative Network (RACOON) project in Germany 69 …”

“…This will require the use of large, machine-readable databases of Accepted Article imaging/clinical data such as that generated by the Radiological Cooperative Network (RACOON) project in Germany. 69 Studies included in the SLR showed little standardization of TE reporting (location, definition, etc.) and a low rate of detection of vasculopathy during the acute phase of COVID-19 infection.…”

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

“…A nationwide infrastructure is also being established within the "Radiological Cooperative Network" (RACOON) for the structured collection of radiological data from COVID-19 cases [6]. For this purpose, all 36 university radiology departments from Germany have joined forces to face the challenges of the COVID-19 pandemic from a radiological perspective [7]. The infrastructure in the RACOON project is based in particular on a nationwide server system with network nodes (RACOON-NODE) at all German university hospitals.…”

“…mint Lesion™ is a certified medical software for the assessment of radiological images. The software is primarily aimed at radiologists, physicians and researchers for context-supported reporting of findings using the integrated EDC component and for structured reporting in radiology [7].…”

Radiologische Diagnostik und Prognostik von COVID-19: Einsatz von künstlicher Intelligenz und Zusammenhang mit muskulo-skelettaler Bildgebung

“…mit anderen Datenquellen zusammenzuführen und statistisch auszuwerten [28]. Da diese Zusammenführung in Echtzeit möglich sein soll, wird hieraus ein Frühwarnsystem aufgebaut [26]. Sollten also künftig in deutschen Universitätsradiologien spezifische Befunde unüblich häufig anfallen, würde dies vom RACOON Netzwerk auf dem entsprechenden Dashboard automatisch erkannt werden, inclusive der Information in welchen Landesteilen diese Entwicklung erfolgt.…”