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 pos...
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Nature Portfolio
2021
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oai:doaj.org-article:951bb53504434e748b68b1581a67d86c2021-12-02T18:03:27ZA reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data10.1038/s41746-021-00439-y2398-6352https://doaj.org/article/951bb53504434e748b68b1581a67d86c2021-04-01T00:00:00Zhttps://doi.org/10.1038/s41746-021-00439-yhttps://doaj.org/toc/2398-6352Abstract 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.Gabriel Alexander SalgMaria-Katharina GantenAndreas Michael BucherHannes Goetz KenngottMatthias Alexander FinkConstantin SeiboldRicarda Elisabeth FischbachKai SchlampCarlos Alberto VelandiaPhilipp FerversFelix DoellingerAnna LugerSaif AfatUta MerleMarkus K. DienerPhilippe L. PereiraTobias PenzkoferThorsten PersigehlAhmed OthmanClaus Peter HeußelMatthias BaumhauerGerlig WidmannKonstantinos StathopoulosBernd HammThomas J. VoglKonstantin NikolaouHans-Ulrich KauczorJens KleesiekNature PortfolioarticleComputer applications to medicine. Medical informaticsR858-859.7ENnpj Digital Medicine, Vol 4, Iss 1, Pp 1-9 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Computer applications to medicine. Medical informatics R858-859.7 |
| spellingShingle |
Computer applications to medicine. Medical informatics R858-859.7 Gabriel Alexander Salg Maria-Katharina Ganten Andreas Michael Bucher Hannes Goetz Kenngott Matthias Alexander Fink Constantin Seibold Ricarda Elisabeth Fischbach Kai Schlamp Carlos Alberto Velandia Philipp Fervers Felix Doellinger Anna Luger Saif Afat Uta Merle Markus K. Diener Philippe L. Pereira Tobias Penzkofer Thorsten Persigehl Ahmed Othman Claus Peter Heußel Matthias Baumhauer Gerlig Widmann Konstantinos Stathopoulos Bernd Hamm Thomas J. Vogl Konstantin Nikolaou Hans-Ulrich Kauczor Jens Kleesiek A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data |
| description |
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. |
| format |
article |
| author |
Gabriel Alexander Salg Maria-Katharina Ganten Andreas Michael Bucher Hannes Goetz Kenngott Matthias Alexander Fink Constantin Seibold Ricarda Elisabeth Fischbach Kai Schlamp Carlos Alberto Velandia Philipp Fervers Felix Doellinger Anna Luger Saif Afat Uta Merle Markus K. Diener Philippe L. Pereira Tobias Penzkofer Thorsten Persigehl Ahmed Othman Claus Peter Heußel Matthias Baumhauer Gerlig Widmann Konstantinos Stathopoulos Bernd Hamm Thomas J. Vogl Konstantin Nikolaou Hans-Ulrich Kauczor Jens Kleesiek |
| author_facet |
Gabriel Alexander Salg Maria-Katharina Ganten Andreas Michael Bucher Hannes Goetz Kenngott Matthias Alexander Fink Constantin Seibold Ricarda Elisabeth Fischbach Kai Schlamp Carlos Alberto Velandia Philipp Fervers Felix Doellinger Anna Luger Saif Afat Uta Merle Markus K. Diener Philippe L. Pereira Tobias Penzkofer Thorsten Persigehl Ahmed Othman Claus Peter Heußel Matthias Baumhauer Gerlig Widmann Konstantinos Stathopoulos Bernd Hamm Thomas J. Vogl Konstantin Nikolaou Hans-Ulrich Kauczor Jens Kleesiek |
| author_sort |
Gabriel Alexander Salg |
| title |
A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data |
| title_short |
A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data |
| title_full |
A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data |
| title_fullStr |
A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data |
| title_full_unstemmed |
A reporting and analysis framework for structured evaluation of COVID-19 clinical and imaging data |
| title_sort |
reporting and analysis framework for structured evaluation of covid-19 clinical and imaging data |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/951bb53504434e748b68b1581a67d86c |
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