Abstract
Because the human brain consumes a disproportionate fraction of the resting body's energy, positron emission tomography (PET) measurements of absolute glucose metabolism (CMR(glc)) can serve as disease biomarkers. Global mean normalization (GMN) of PET data reveals disease-based differences from healthy individuals as fractional changes across regions relative to a global mean. To assess the impact of GMN applied to metabolic data, we compared CMR(glc) with and without GMN in healthy awake volunteers with eyes closed (i.e., control) against specific physiological/clinical states, including healthy/awake with eyes open, healthy/awake but congenitally blind, healthy/sedated with anesthetics, and patients with disorders of consciousness. Without GMN, global CMR(glc) alterations compared to control were detected in all conditions except in congenitally blind where regional CMR(glc) variations were detected in the visual cortex. However, GMN introduced regional and bidirectional CMR(glc) changes at smaller fractions of the quantitative delocalized changes. While global information was lost with GMN, the quantitative approach (i.e., a validated method for quantitative baseline metabolic activity without GMN) not only preserved global CMR(glc) alterations induced by opening eyes, sedation, and varying consciousness but also detected regional CMR(glc) variations in the congenitally blind. These results caution the use of GMN upon PET-measured CMR(glc) data in health and disease.