IT Challenges for fMRI

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After unlocking secrets to brain function for the past two decades at research sites, functional MRI is gaining value in clinical practice, particularly in managing patients with brain tumors and arteriovenous malformations. The large fMRI data files these systems create, increasing number of scans and complex image processing also are challenging IT professionals to practically manage this massive image bulk.

Since its introduction in the early 1980s, functional magnetic resonance imaging (fMRI) has gained widespread acceptance among neuroscientists as a tool used to detect regional changes in cerebral metabolism related to cognitive, perceptual, behavioral and emotional functionality. The most widely adopted technique uses blood oxygenation level dependent (BOLD) contrast to exploit the different magnetic properties of oxygenated and deoxygenated blood. Resultant activity maps are superimposed as an overlay on the anatomic images produced by the MR scan.

Functional MRI is on the move from the research center to the clinical setting in the management of patients with brain tumors and AVMs (arteriovenous malformations). And at the same time, post-image acquisition processing procedures and management of large image and data files requires sophisticated network configuration by IT professionals to facilitate workflow.

Keith Thulborn, MD, PhD, professor of radiology, physiology and biophysics in the Center for Magnetic Resonance Research at the University of Illinois in Chicago explains that by their very nature, fMRI studies are extremely complex. They include not only the images an MR scanner produces, but also non-image data such as the behavioral patient response to a task, changes produced by patient movement or underlying physiologic functions such as breathing or heart rate, and the requirement that all of that data be correlated with image data in real time.

For example, a patient may be asked to read several sentences and answer a question relating to each sentence to test for comprehension. That task performance will be analyzed for accuracy and to determine response time. The patient who reads three sentences in 30 seconds and answers all questions correctly is different from the patient who reads five sentences, but has an accuracy comprehension rate of 50 percent, demonstrating probable guesses to some questions.

"If you don't know the performance, you can't evaluate the activation map," says Thulborn. "Someone with an accuracy rate of 50 percent will have a different activation map than someone who is reading and accurately answering questions."


Two components impact the ability to accomplish fMRI studies in real time - the speed of the scanners, and post-processing tasks required to analyze and correlate all of the data produced during the study.

Kyle Salem, PhD, manager of MR research collaborations for Siemens Medical Solutions, explains that although some researchers and clinicians use a 1.5 Tesla magnet, Siemens Magnetom ALLEGRA 3T short-bore, superconductive magnet scanner has been optimized for neuroscience with a gradient of 40mT/m SR 400 to offer a maximum BOLD signal, and enable extremely fast studies. Ninety percent of their market for the ALLEGRA involves research departments in universities that conduct studies in neuropsychology and other neurosciences.

"For IT, the No. 1 issue is the huge volume of imaging studies," explains Salem. "They image the entire brain every 2 to 3 seconds, and the total study takes about 10 minutes. So if you do 30 slices every two seconds, that means 900 images every minute, times a 10 minute study equals 9K images."

With 128 x 128 matrices, this means about 64K per image - creating 576 MB in 10 minutes. For eight channels, about 4.6 GB is received in about 10 minutes, Salem says. What does this mean for managing images per week? For a one-hour study, including about 4 functional runs, about 25 GB of data or more is acquired. For 10 hours of imaging each day (often more in many facilities), you accumulate about 250 GB of data, which are often networked with various servers for processing in individual labs. Thus, more than 1 terabyte in images needs to be routed, processed and stored each week.

Siemens customers use the MR neuro task card in syngo to facilitate productivity of real-time fMRI studies, including 3D image renderings.

"The advent of parallel imaging is both good and bad," Salem concludes. "Better information