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Pediatric Brain MR Image Bank to Be Searchable

By Medimaging International staff writers
Posted on 21 Jan 2014
To help physicians arrive at the optimal decision on cancer therapy for a specific patient, researchers are constructing a comprehensive digital library of magnetic resonance imaging (MRI) scans gathered from children with normal and abnormal brains. According to the scientists, the objective of the project is to provide physicians with a Google-like search system that will enhance the way they diagnose and treat young patients with brain disorders.

This cloud-computing project, being developed by a team of engineers and radiologists from Johns Hopkins University (Baltimore, MD, USA), should allow physicians to access thousands of pediatric scans to look for some that resemble their own patient’s images. The project is supported by a three-year USD 600,000 grant from the US National Institutes of Health (Bethesda, MD, USA).

“We’re creating a pediatric brain data bank that will let doctors look at MRI brain scans of children who have already been diagnosed with illnesses like epilepsy or psychiatric disorders,” said Michael I. Miller, a lead investigator on the study and a professor of biomedical engineering at Johns Hopkins and director of the University’s Center for Imaging Science. “It will provide a way to share important new discoveries about how changes in brain structures are linked to brain disorders. For the medical imaging world, this system will do what a search engine like Google does when you ask it to look for specific information on the Web.”

Prof. Miller, an innovator in the field of computational anatomy, is noted for the technology used for “brain parsing,” and is a core faculty member in the University’s Institute for Computational Medicine. The new pediatric brain imaging data bank, according to Prof. Miller, will be valuable in at least two ways. “If doctors are not sure which disease is causing a child’s condition, they could search the data bank for images that closely match their patient’s most recent scan,” he said. “If a diagnosis is already attached to an image from the data bank, that could steer the physician in the right direction. Also, the scans in our library may help a physician identify a change in the shape of a brain structure that occurs very early in the course of a disease, even before clinical symptoms appear. That could allow the physician to get an early start on the treatment.”

Prof. Miller’s co-lead investigator on the project is Susumu Mori, a professor of radiology in the Johns Hopkins School of Medicine. Prof. Mori emphasized out that such a “biobank” has the potential to impact physicians’ workflow drastically. “We empirically know that a certain type of anatomical abnormality is related to specific brain diseases,” he said. “This relationship, however, is not always clear and often is compounded by anatomical changes during the normal course of brain development. Therefore, neuroradiologists need extensive training to accumulate the knowledge. We hope our brain imaging data bank will not only assist such a learning process but also enhance the physician’s ability to understand the pathology and reach the best medical decision.”

Prof. Mori and his collaborator, Thierry Huisman, a professor of radiology and pediatrics and the director of pediatric radiology at the Johns Hopkins Children’s Center, have been working to establish a clinical database of more than 5,000 whole-brain MRI scans of children treated at Johns Hopkins. The computer software indexed anatomic data involving up to 1,000 structural measurements in 250 regions of the brain. These images were also sorted into 22 brain disease categories, including chromosomal abnormalities, congenital malformations, vascular diseases, infections, epilepsy, and psychiatric disorders.

According to Prof. Huisman, the new data bank now under development not only facilitates recognition and accurate classification of pediatric brain disorders, but the more objective image analysis also offers identification of injury and disease that may go undetected by the conventional, more subjective radiologic “eyeballing” of MR images. Furthermore, he noted, recognition of distinct patterns of injury and the ensuing category of these children based upon their characteristic patterns of MRI findings allow recognition and identification of new diseases as well as reclassification of earlier unclassified diseases. Lastly, according to Prof. Huisman, the data acquisition is free of ionizing radiation, allowing clinicians to study the most vulnerable, youngest patients and perhaps to help initiate disease-specific treatment before irreversible injury to the developing brain occurs.

With all of these data, physicians will be able to conduct a Google-like search for images associated with normal and abnormal pediatric and aging brain disorders. For example, a physician who is unclear about a child’s diagnosis could present that patient’s latest brain scan and request the medical records of children with similar images.

Currently, the pilot pediatric brain imaging data bank is limited to physicians and patients within the Johns Hopkins medical system, but the researchers say the data bank could be expanded or replicated elsewhere in coming years.

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