fMRI task-specific brain activation may vary up to 16.5 mm

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fMRI researchers and practitioners should factor variability in the center of task-specific brain activation by investigating site into their decision making and test the reliability of local results by percentage signal change (PSC) and contrast-to-noise ratio (CNR), according to a study published online March 22 in Radiology.

Increasing research and clinical applications of fMRI highlight the need for providers to understand variability in results and parameters for a given functional localization. Moritz C. Wurnig, MD, from the department of neurology at Medical University of Vienna, and colleagues prospectively enrolled eight women and seven men undergoing fMRI prior to brain surgery at three sites to assess MR variability, using PSC and CNR as quality measures.

During each visit, patients performed two separate tasks, a highly standardized task and a motor task, with the contralesional hand; data were analyzed by a neurologist and radiologist using variability metrics.

For the highly standardized task, the median localization error in terms of peak activation variability was 7.9 mm, according to Wurnig et al. The corresponding figure for the motor task was 8.3 mm. The researchers observed a significant interaction between task and site comparison and task and subject comparison for peak activation variability.

“The major finding of our study was that the diagnostic uncertainty clinicians face with functional MR imaging localizations is in an average range of 6-8 mm for the sensorimotor cortex. However, in individual cases, clinical functional MR imaging variability can be substantial and vary up to 20-40 mm.”

The implications are critical for clinical localization of essential cortex functions and for valid setup of fMRI biomarker research studies.

Wurnig and colleagues concluded by recommending that providers and researchers incorporate the possible variability of 16.5 mm by investigating site into decision making. They suggested maximizing fMRI signal strength and comparing local data with PSC and CNR measures.