The University of Arkansas for Medical Sciences (UAMS) will use an $8.3 million grant to expand and enhance an archive of freely accessible cancer medical images and data. On Tuesday (Oct. 31), UAMS announced it received the grant from the National Cancer Institute (NCI).
The Cancer Imaging Archive (TCIA) is a free online service with a large collection of cancer-related medical images the public can download. All patient identifying information has been removed from the images, and data from the archive has been used for nearly 500 academic papers.
In 2015, the archive moved to UAMS, from Washington University in St. Louis, when its principal investigator Fred Prior accepted the position of chair for the UAMS Department of Biomedical Informatics. Prior is professor of the Department of Bioinformatics in the UAMS College of Medicine.
The grant, TCIA Sustainment and Scalability: Platforms for Quantitative Imaging Informatics in Precision Medicine, will allow the archive to expand its capacity to “provide data driven information and images for use in research studies; adding new high-quality data collections; and encourage the engagement, collaboration and dissemination of information among the research community,” according to a news release.
The archive “has encouraged and supported cancer-related research by acquiring, curating, hosting and managing collections of images and other data essential to the discovery process” since 2011, Prior said. The grant will allow the archive to undergo “continuous improvements and expansion necessary to provide the large collections of data required to test and validate cancer research studies for years to come.”
Biomedical informatics uses computers instead of traditional laboratories to “extract knowledge from large sets of data,” the release shows. The bioinformatics department has grown to nearly 50 faculty and staff under Prior’s leadership. The goal of the archive is the “advancement of precision medicine,” allowing for therapies to be “tailored to the individual needs of each patient based on the specific makeup of his or her cancer.” Prior and his team use computers to understand medical images “in new ways” and apply the tools “across multiple formats, from microscope images of tumor biopsy samples to CT images of the lung.”
Prior hopes the computers will allow for a more accurate and quicker cancer diagnosis and to determine more quickly whether a patient is responding to a specific therapy.
The team also is working on a new database to manage and redistribute to scientists the results of previous research. “After the computers learn the image features that are important to cancer diagnosis, they can be linked to genetic markers and other individual patient characteristics, enabling our ability to more precisely identify the unique qualities of a given patient and the disease they have contracted,” he said.
The research team includes Lawrence Tarbox, Mathias Brochhausen, Tracy Nolan, Kirk Smith, William Bennett, Roosevelt Dobbins, Diana Stockton and Sean Berryman.