Head Injury in the Cloud

USING CLOUD-BASED “BACKFILL CYCLES” ON BRIDGES ENABLES VERY HIGH RESOLUTION FUNCTIONAL BRAIN IMAGING

From children’s playing fields to professional stadiums to battle fields, doctors are more and more worried about traumatic brain injury (TBI) that lurks after a seemingly minor concussion. Don Krieger is part of a team of clinician-researchers at the University of Pittsburgh who are studying TBI. They produce very high resolution functional brain images from magnetoencephalographic (MEG) recordings using a powerful new method called “referee consensus processing.” Their calculations rely on opportunistic use of “backfill” and other unused cycles on PSC’s Bridges and other supercomputers. Their results show great promise in providing high resolution functional images of normal and TBI-affected brain activity.

Why It’s Important

From children’s playing fields to professional stadiums to battlefields, doctors are more and more worried about brain trauma that lurks after a seemingly minor concussion. Kids and adults may walk off the field and suffer from headaches, difficulty thinking, memory problems, attention deficits and mood swings for weeks, months or longer. A key problem in finding better ways to diagnose and treat concussion is that imaging studies show no abnormalities in more than 80 percent of TBI patients. For most, doctors don’t know whether the imaging methods aren’t sensitive enough or even whether there is any structural damage to detect.

Don Krieger is part of a team of clinician-researchers at the University of Pittsburgh who are studying TBI. They produce very high resolution functional brain images from magnetoencephalographic (MEG) recordings using a powerful new method called “referee consensus processing.” MEG measures the magnetic fields caused by cooperative nerve-cell activity. The technology is noninvasive, silent and safe. But it’s also computationally expensive, requiring supercomputers to generate images. 

“We’re trying to understand concussion. Even when nothing can be found in standard brain imaging studies, about 20 percent of those with concussion experience persistent symptoms for months or years. A detailed functional exam almost always reveals real problems, but we typically cannot identify the neurologic cause.” —Don Krieger, University of Pittsburgh

How PSC and XSEDE Helped

To carry out their computations the Pitt team used the Open Science Grid (OSG). OSG is a loosely coupled supercomputing resource composed of compute cycles donated by government laboratory and academic computing centers throughout the Americas. Using the OSG reduced the time required for the calculations from many decades to one to two years. To reduce that time further, they turned to two additional systems that work very efficiently with the referee consensus solver the Pitt scientists had developed: PSC’s Bridges and Comet, at the San Diego Supercomputer Center (SDSC). Employing backfill and other unused cycles on the two supercomputers made more computing time available, did not impact other researchers using the same machines and required only a few changes in the Pitt team’s software. PSC’s Anirban Jana and Derek Simmel and SDSC’s Mahidhar Tatineni helped the team make these minor adjustments in just a few days. The work was supported by grants from XSEDE, the NSF network of supercomputing sites that includes both PSC and SDSC, and with continuing support from OSG operations and University of Southern California Viterbi School of Engineering’s Mats Rynge. 

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Krieger and his colleagues analyzed MEG data from 64 volunteers with persistent symptoms of TBI, most of whom were combat veterans. They compared the scans with MEG data from 414 individuals who were similar to the TBI volunteers other than not having TBI symptoms. This second group of scans had been collected by the Cambridge (UK) Centre for Ageing and Neuroscience (CamCAN). The latter served as “controls,” providing the researchers with recordings from people without TBI symptoms to compare with the volunteers’ recordings. 

Together, Bridges and Comet reduced the computational time for the critical CamCAN control recordings from an estimated 20 months to seven. With the results from the CamCAN cohort, scientists have a picture with unprecedented resolution of patterns of cooperative neural activity from brains that are unaffected by TBI. Comparing these results with those from symptomatic patients will help the scientists identify the mechanisms which cause symptoms in TBI. It may also help them find better treatments.