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Massive Imaging Database Created to Aid Research

By MedImaging International staff writers
Posted on 30 May 2017
A large healthcare system in the U.S. has announced the creation of a massive, anonymous imaging database that will integrate clinical imaging and electronic health records using data from more than 1 million patients.

The goal of the project is to dramatically improve clinical care and translational research, and enable clinicians to investigate patterns and traits of specific diseases or conditions. The project will help clinicians find common features among large groups of patients, and identify genetic or other similarities that could lead to new diagnostic techniques and treatments. The Imaging Research Warehouse (IRW) was developed by the Mount Sinai Translational and Molecular Imaging Institute (TMII) of the Mount Sinai Health System.

Image: Functional Magnetic Resonance Imaging (fMRI) brain scans intended to identify biomarkers for autism (Photo courtesy of SpectrumNews).
Image: Functional Magnetic Resonance Imaging (fMRI) brain scans intended to identify biomarkers for autism (Photo courtesy of SpectrumNews).

The IRW is intended to advance research in mammography, prostate cancer, genomics, spine injuries, neuro-degenerative diseases, and bowel disease, and has the potential to change the way radiologists read and collect data. Together with the help of machine learning algorithms, radiologists could use the system to better evaluate known abnormalities in imaging scans. Other possible outcomes include new and more accurate Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) imaging protocols and techniques.

Vice Chair, Radiology, Mount Sinai Health System, David Mendelson, MD, professor at the Icahn School of Medicine at Mount Sinai, said, “The Imaging Research Warehouse is a unique resource that will provide large volumes of de-identified images to the research community. This model fills a gap in the new world of healthcare ‘big data.’ The data contained within patients’ radiological images is hard to make use of, and this warehouse is the solution to expose this information for analysis.”


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