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BackgroundMany neurodegenerative diseases affect the brainstem and often do so in an early stage. The overall goal of this project was (a) to develop a method to segment internal brainstem structures from T1 and T2 weighted sequences by taking advantage of the superior myelin contrast of the T1/T2 ratio image (RATIO) and (b) to test if this approach provides biological meaningful information by investigating the effects of aging on different brainstem gray matter structures.Methods675 T1 and T2 weighted images were obtained from the Human Connectome Project Aging. The intensities of the T1 and T2 images were re-scaled and RATIO images calculated. The brainstem was isolated and k-means clustering used to identify five intensity clusters. Non-linear diffeomorphic mapping was used to warp the five intensity clusters in subject space into a common space to generate probabilistic group averages/priors that were used to inform the final probabilistic segmentations at the single subject level. The five clusters corresponded to five brainstem tissue types (two gray matters, two mixed gray/white, and 1 csf/tissue partial volume).ResultsThese cluster maps were used to calculate Jacobian determinant maps and the mean Jacobians of 48 brainstem gray matter structures extracted. Significant linear or quadratic age effects were found for all but five structures.ConclusionsThese findings suggest that it is possible to obtain a biologically meaningful segmentation of internal brainstem structures from T1 and T2 weighted sequences using a fully automated segmentation procedure.

Observations in animal models suggest that amyloid can cause network hypersynchrony in the early preclinical phase of Alzheimer's disease (AD). The aim of this study was (a) to obtain evidence of paroxysmal hypersynchrony in cognitively intact subjects (CN) with increased brain amyloid load from task-free fMRI exams using a dynamic analysis approach, (b) to investigate if and how hypersynchrony interferes with memory performance, and (c) to describe its relationship with gray and white matter connectivity. Florbetapir-F18 PET and task-free 3T functional and structural MRI were acquired in 47 CN (age = 70.6 ± 6.6), 17 were amyloid pos (florbetapir SUVR >1.11). A parcellation scheme encompassing 382 regions of interest was used to extract regional gray matter volumes, FA-weighted fiber tracts and regional BOLD signals. Graph analysis was used to characterize the gray matter atrophy profile and the white matter connectivity of each subject. The fMRI data was processed using a combination of sliding windows, graph and hierarchical cluster analysis. Each activity cluster was characterized by identifying strength dispersion (difference between pos and neg strength) their maximal and minimal pos and neg strength rois and by investigating their distribution and association with memory performance and gray and white matter connectivity using spearman rank correlations (FDR p < 0.05). The cluster analysis identified eight different activity clusters. Cluster 8 was characterized by the largest strength dispersion indicating hypersynchrony. Its duration/subject was positively correlated with amyloid load (r = 0.42, p = 0.03) and negatively with memory performance (CVLT delayed recall r = −0.39 p = 0.04). The assessment of the regional strength distribution indicated a functional disconnection between mesial temporal structures and the rest of the brain. White matter connectivity was increased in left lateral and mesial temporal lobe and was positively correlated with strength dispersion in the cross-modality analysis suggesting that it enables widespread hypersynchrony. In contrast, precuneus, gray matter connectivity was decreased in the right fusiform gyrus and negatively correlated with high degrees of strength dispersion suggesting that progressing gray matter atrophy could prevent the generation of paroxysmal hypersynchrony in later stages of the disease.