Detecting hippocampal hypometabolism in Mild Cognitive Impairment using automatic voxel-based approaches

Abstract

While the hippocampus is constantly reported as the site of earliest and highest structural alteration in Alzheimer's disease (AD), findings regarding the metabolic status of this region are rather heterogeneous. It has been proposed that only a time-consuming individual region-of-interest (ROI) approach would allow the detection of hypometabolism in this complex and small area. Our main goal with this study is to assess whether more automatic and clinically useful methods would be sensitive enough when considering other methodological confounds. From a single PET data set collected in 28 patients with amnestic Mild Cognitive Impairment (aMCI) and 19 controls, we assessed the effects of partial volume effect (PVE) correction, scaling (using vermis or global means), and analysis method (individual ROI versus more automatic template-based ROI or voxel-based approaches) on hippocampal hypometabolism detection in aMCI. PVE correction and scaling both showed a significant effect on group comparison, while the analysis method (individual versus template-based ROI) surprisingly did not. Hippocampal metabolic decrease was significant in all vermis-scaled conditions, and more so after PVE correction. Our findings highlight the crucial relevance of using reference-region-based (instead of global) scaling, and the higher sensitivity of PVE-corrected PET measures, to detect hippocampal hypometabolism in aMCI. They also show that hippocampal metabolic decline can be detected using template-based ROI as well as voxel-based methods. These findings have clinical relevance since they support the validity of more automatic and time-saving approaches to assess hippocampal metabolism changes in aMCI and early AD.