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In Netherlands, the Leiden University Medical Center (LUMC), Erasmus University Medical Center Rotterdam (Erasmus MC) and the Delft University of Technology are working on analysis techniques of medical imaging and other data. Large-scale imaging data sets containing brain scans of participants in long-term studies help to diagnose – and even predict – the onset of illness (a method known as ‘population imaging’). The accuracy of a prediction depends on the quantity of data available: the more data, the better the prediction. In this respect, collaboration over the advanced e-Infrastructure provided by SURF is crucial.

A publication developed by Marjolein van Trigt, Jan Bot and Nanda Bazuin and published by SURF in the Netherlands, reveals the major importance of data sharing in brain study to diagnose and predict the onset of illness.

The publication points the following:

“In healthcare, more and more treatments are being based on data from a single population study. The larger the population, the more data will be available and the more effectively specialists can determine which treatment has the greatest chance of success. Although the opportunities offered by big data are promising, scaling up a population study means that research institutes require access to each other’s data sets. The networks of medical centres are well secured in order to guarantee patient privacy, and sharing data sets is only possible if the institutions have a fast, secure connection.”

“Although there is funding available to scale up the population study, hospitals are encountering practical obstacles. Leiden University Medical Center (LUMC), Erasmus University Medical Center Rotterdam (Erasmus MC) and the Delft University of Technology decided to set up a trial system to demonstrate that it really is possible to centralise the analysis of data stored locally at various sites. The project focused on three key aspects: speed, response time and security. The institutions were connected via SURF light paths, which were used to transmit the imaging data (MRI and CT scans) remotely from hospitals at various locations for viewing and analysis. Light paths form a secure and reliable infrastructure, enabling the simultaneous transmission of large quantities of data via a secure connection.”

You can download the complete publication here:
https://www.surf.nl/binaries/content/assets/surf/en/knowledgebase/2014/best_practice_support4research_lumc_en.pdf

SURF is the collaborative ICT organisation for Dutch higher education and research; it offers students, lecturers and scientists in the Netherlands access to the best possible internet and ICT facilities through its connection to its advanced network: SURFnet.