FDG-PET Imaging May Be More Accurate for Showing Minimal Consciousness


FDG PET may be more accurate than active fMRI scans for showing brain activity consistent with even minimal consciousness, according to a new study.

FDG PET (positron emission tomography with 18F-fluorodeoxyglucose tracer) may be more accurate than active fMRI scans for showing brain activity consistent with even minimal consciousness, according to Belgian researchers led by Johan Sender, MD. Their study was published in The Lancet.

Of 130 clinically vegetative patients who were found, with one or the other imaging method, to show brain activity consistent with minimal consciousness, 9 eventually gained full awareness. FDG-PET was the more accurate method, the researchers said, correctly predicting outcomes in 75 of the 102 patients evaluated in their study (74%; 95% confidence interval [CI], 64%-81%). Active fMRI scans were less accurate, correctly predicting outcome in 36 of 65 patients undergoing the scans (56%; 95% CI, 43%-67%).

The patients in the study were at the University Hospital of Liège, Belgium, had been admitted between January 2008 and June 2012, and were diagnosed as having unresponsive wakefulness syndrome, having locked-in syndrome, or being in a minimally conscious state.

“Cerebral FDG PET was reliable in both acute and chronic stages, and across all causes,” the researchers wrote. “The test provided a higher rate of positive results in patients with traumatic brain injury than non-traumatic causes.”

The researchers said that cerebral FDG PET could be used to complement bedside examinations and predict long-term recovery of patients in unresponsive wakefulness syndrome (a vegetative state). They noted that there is a serious clinical need for a way to detect nonvolitional signs of consciousness because bedside clinical prognoses are highly uncertain even when using standardized scales.

“fMRI during mental tasks might complement the assessment with information about preserved cognitive capability, but should not be the main imaging-based differential diagnostic method,” the authors concluded. “Future work should aim to validate other promising neuroimaging-based differential diagnostic markers, such as quantified metabolic markers, resting state fMRI, or electroencephalography with transcranial magnetic stimulation.”

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