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学術論文

A nation-wide initiative for brain imaging and clinical phenotype data federation in Swiss university memory centres

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Draganski,  Bogdan
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
LREN, Department of Clinical Neurosciences, University Hospital Centre (CHUV), University of Lausanne (UNIL), Switzerland;
Leenaards Memory Centre, Department of clinical neurosciences, Uni-versity Hospital Centre (CHUV) and University of Lausanne (UNIL), Switzerland;

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引用

Draganski, B., Kherif, F., Damian, D., & Demonet, J.-F. (2019). A nation-wide initiative for brain imaging and clinical phenotype data federation in Swiss university memory centres. Current Opinion in Neurology, 32(4), 557-563. doi:10.1097/WCO.0000000000000721.


引用: https://hdl.handle.net/21.11116/0000-0004-635F-3
要旨
PURPOSE OF REVIEW:

The goal of our nation-wide initiative is to provide clinicians intuitive and robust tools for accurate diagnosis, therapy monitoring and prognosis of cognitive decline that is based on large-scale multidomain data.
RECENT FINDINGS:

We describe a federation framework that allows for statistical analysis of aggregated brain imaging and clinical phenotyping data across memory clinics in Switzerland. The adaptation and deployment of readily available data capturing and federation modules is paralleled by developments in ontology, quality and regulatory control of brain imaging data. Our initiative incentivizes data sharing through the common resource in a way that provides individual researcher with access to large-scale data that surpasses the data acquisition capacity of a single centre. Clinicians benefit from fine-grained epidemiological characterization of own data compared with the rest additional to intuitive tools allowing for computer-based diagnosis of dementia. Finally, our concept aims at closing the loop between group-level results based on aggregate data and individual diagnosis by providing disease models, that is, classifiers for neurocognitive disorders that will enable the computer-based diagnosis of individual patients.
SUMMARY:

The obtained results will inform recommendations on best clinical practice in all relevant fields focusing on standardization and interoperability of acquired data, privacy protection framework and ethical consideration in the context of evolutive pathology.