Cloud computing and the internet are having a profound effect on the field of medicine. As more and more patients have their records digitized and posted in online medical sources, doctor’s are able to better track patient histories, conduct referrals, and make speedier diagnoses. And now, doctors at John Hopkins University are working on a cloud-computing project specifically for children’s brain scans.
By collecting and categorizing thousands of MRI scans from kids with normal and abnormal brains, they say the resulting database will give physicians a sophisticated, “Google-like” search system to help find similar scans as well as the medical records of those children. Such a system could help not only enhance the diagnosis of brain disorders, but the treatment as well, maybe even before clinical symptoms are obvious to the naked eye.
Michael I. Miller, a lead investigator on the project who also heads up the university’s Center for Imaging Science, said in a news release:
If doctors aren’t 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. 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.
Susumu Mori, a radiology professor at the Johns Hopkins School of Medicine and co-lead investigator on what he calls the “biobank,” says that a collection of brain scans of this size will also help neuroradiologists and physicians identify specific malformations far faster than is currently possible.
Mori has spent the past four-plus years working on a clinical database of more than 5,000 whole brain MRI scans of children who’ve come through Johns Hopkins. This project involved indexing anatomical data on 1,000 structural measurements in 250 brain regions that were ultimately sorted into 22 brain disease categories, including infections, psychiatric disorders, epilepsy, and chromosomal abnormalities.
The project, which was made possible by a three-year $600,000 grant from the National Institutes of Health, is still in its pilot stage and available only to physicians and patients within the Johns Hopkins medical system. But the researchers say it could open up and expand to other networks in the coming years. Such an expansion would presumably benefit not only other physicians and patients, but the database itself.
Researchers are also working on a similar project to collect scans of elderly patients to focus on age-related diseases and neurological disorders. Combined with the pediatric databank, this new brain scan archive will not only help recognize established neurological disorders, but could even possibly help identify and classify new ones as well.
But one of the key words here in anonymous. While cloud computing and patient files may raise the specter of privacy for many, the current project maintains patient confidentially. And one can further assume that voluntary compliance will be maintained as databases like these expand. After all, one does not need to know a patient’s name in order to examine what anomalies their brains exhibit.
And in the meantime, be sure to check out this video of Michael Miller explaining the new brain scan project and computational anatomy in greater detail: