Structural brain imaging in Alzheimer’s disease and mild cognitive impairment: biomarker analysis and shared morphometry database

Abstract

Magnetic resonance (MR) imaging is a powerful technique for non-invasive in-vivo imaging of the human brain. We employed a recently validated method for robust cross-sectional and longitudinal segmentation of MR brain images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. Specifically, we segmented 5074 MR brain images into 138 anatomical regions and extracted time-point specific structural volumes and volume change during follow-up intervals of 12 or 24 months. We assessed the extracted biomarkers by determining their power to predict diagnostic classification and by comparing atrophy rates to published meta-studies. The approach enables comprehensive analysis of structural changes within the whole brain. The discriminative power of individual biomarkers (volumes/atrophy rates) is on par with results published by other groups. We publish all quality-checked brain masks, structural segmentations, and extracted biomarkers along with this article. We further share the methodology for brain extraction (pincram) and segmentation (MALPEM, MALPEM4D) as open source projects with the community. The identified biomarkers hold great potential for deeper analysis, and the validated methodology can readily be applied to other imaging cohorts.

Longitudinal atrophy in early Braak regions in preclinical Alzheimer's disease

“…we observed a 1.03%/year atrophy rate, which is lower than that of prior studies of MCI (Chincarini et al, 2016;Das et al, 2012;Holland, McEvoy, Desikan, & Dale, 2012;Iglesias et al, 2016;Jack et al, 2000;Kulason et al, 2019;Ledig et al, 2018;Leung et al, 2010;Morra et al, 2009;Schuff et al, 2009;Tward et al, 2017;Wolz et al, 2010) (range from 1.55%/year to 3.2%/year). This discrepancy is likely due to segmentation protocol and analysis methodology differences and/or the fact that we only included EMCI patients, who are expected to be at an earlier disease stage than most MCI cohorts in other studies.…”

The Aging Slopes of Brain Structures Vary by Ethnicity and Sex: Evidence From a Large Magnetic Resonance Imaging Dataset From a Single Scanner of Cognitively Healthy Elderly People in Korea

“…Existing findings are mainly a reflection of Caucasians (Resnick et al, 2003 ; Scahill et al, 2003 ; Sowell et al, 2003 ; Ledig et al, 2018 ). Furthermore, in recent years, more and more studies are increasingly dependent on only a few data sources that are virtually monopolistic, such as the Alzheimer’s Disease Neuroimaging Initiative (ADNI; Weiner et al, 2015 ; Ledig et al, 2018 ). Asia now accounts for more than half of the world’s elderly population, and the proportion is expected to increase to two-thirds by 2050 (He et al, 2016 ).…”

The genetic architecture of human brainstem structures and their involvement in common brain disorders

“…Notably, we found a highly similar pattern in individuals with MCI. To our knowledge, there is no previous study showing reduced brainstem volumes in MCI, although one recent report found greater whole brainstem volume reduction over one year in individuals with MCI that converted to dementia than in those who did not convert 51 . There is a scarcity of structural brainstem studies in dementia, yet the results of the present study are consistent with a few previous findings suggesting volume decreases mainly in midbrain and pons in dementia 20,52 .…”