Integrating Biological and Radiological Data in a Structured Repository: a Data Model Applied to the COSMOS Case Study.

Autor: Garau N; Dipartimento Di Elettronica, Informazione E Bioingegneria, Politecnico Di Milano, Milano, Italy. noemi.garau@polimi.it.; Division of Radiology, IEO, European Institute of Oncology IRCCS, Milan, Italy. noemi.garau@polimi.it., Orro A; Institute for Biomedical Technologies, National Research Council (ITB-CNR), Segrate, Italy., Summers P; Division of Radiology, IEO, European Institute of Oncology IRCCS, Milan, Italy., De Maria L; Division of Radiology, IEO, European Institute of Oncology IRCCS, Milan, Italy., Bertolotti R; Division of Data Management, IEO European Institute of Oncology IRCCS, Milan, Italy., Bassis D; School of Medicine, University of Milan, Milan, Italy., Minotti M; Division of Radiology, IEO, European Institute of Oncology IRCCS, Milan, Italy., De Fiori E; Division of Radiology, IEO, European Institute of Oncology IRCCS, Milan, Italy., Baroni G; Dipartimento Di Elettronica, Informazione E Bioingegneria, Politecnico Di Milano, Milano, Italy.; Bioengineering Unit, CNAO Foundation, Pavia, Italy., Paganelli C; Dipartimento Di Elettronica, Informazione E Bioingegneria, Politecnico Di Milano, Milano, Italy., Rampinelli C; Division of Radiology, IEO, European Institute of Oncology IRCCS, Milan, Italy.
Jazyk: angličtina
Zdroj: Journal of digital imaging [J Digit Imaging] 2022 Aug; Vol. 35 (4), pp. 970-982. Date of Electronic Publication: 2022 Mar 16.
DOI: 10.1007/s10278-022-00615-w
Abstrakt: Integrating the information coming from biological samples with digital data, such as medical images, has gained prominence with the advent of precision medicine. Research in this field faces an ever-increasing amount of data to manage and, as a consequence, the need to structure these data in a functional and standardized fashion to promote and facilitate cooperation among institutions. Inspired by the Minimum Information About BIobank data Sharing (MIABIS), we propose an extended data model which aims to standardize data collections where both biological and digital samples are involved. In the proposed model, strong emphasis is given to the cause-effect relationships among factors as these are frequently encountered in clinical workflows. To test the data model in a realistic context, we consider the Continuous Observation of SMOking Subjects (COSMOS) dataset as case study, consisting of 10 consecutive years of lung cancer screening and follow-up on more than 5000 subjects. The structure of the COSMOS database, implemented to facilitate the process of data retrieval, is therefore presented along with a description of data that we hope to share in a public repository for lung cancer screening research.
(© 2022. The Author(s).)
Databáze: MEDLINE
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