Comparison of hippocampal subfield segmentation agreement between 2 automated protocols across the adult life span
05 Aug 2021-American Journal of Neuroradiology (American Journal of Neuroradiology)-Vol. 42, Iss: 10, pp 1783-1789
TL;DR: In this article, the authors compared the results of two automated segmentation algorithms for hippocampal subfields (FreeSurfer v6.0 and volBrain) within a single imaging data set from adults across a wide age range (20-79 years).
Abstract: BACKGROUND AND PURPOSE: The hippocampus is a frequent focus of quantitative neuroimaging research, and structural hippocampal alterations are related to multiple neurocognitive disorders. An increasing number of neuroimaging studies are focusing on hippocampal subfield regional involvement in these disorders using various automated segmentation approaches. Direct comparisons among these approaches are limited. The purpose of this study was to compare the agreement between two automated hippocampal segmentation algorithms in an adult population. MATERIALS AND METHODS: We compared the results of 2 automated segmentation algorithms for hippocampal subfields (FreeSurfer v6.0 and volBrain) within a single imaging data set from adults (n = 176, 89 women) across a wide age range (20–79 years). Brain MR imaging was acquired on a single 3T scanner as part of the IXI Brain Development Dataset and included T1- and T2-weighted MR images. We also examined subfield volumetric differences related to age and sex and the impact of different intracranial volume and total hippocampal volume normalization methods. RESULTS: Estimated intracranial volume and total hippocampal volume of both protocols were strongly correlated (r = 0.93 and 0.9, respectively; both P CONCLUSIONS: The hippocampal subfield volume relationship to demographic factors and disease states should undergo nuanced interpretation, especially when considering different segmentation protocols.
Citations
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TL;DR: Hippocampal subfield volumes demonstrated potential as imaging biomarkers in the diagnosis and detection of AD and Aβ deposition, respectively.
Abstract: Characteristic atrophy patterns of hippocampal subfield volumes and cortical amyloid‐beta (Aβ) deposition are two important neuroimaging biomarkers in Alzheimer’s disease (AD). We investigated the relationship between hippocampal subfield volumes and cortical Aβ deposition in AD.
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TL;DR: The findings suggest that the eight subfield regions, which were strongly associated with AD PGRS are likely involved in the early stage ADD and a specific focus on the left hemisphere could enhance the early prediction of ADD.
Abstract: Hippocampal subfield atrophy is a prime structural change in the brain, associated with cognitive aging and neurodegenerative diseases such as Alzheimer’s disease. Recent developments in genome-wide association studies (GWAS) have identified genetic loci that characterize the risk of hippocampal volume loss based on the processes of normal and abnormal aging. Polygenic risk scores are the genetic proxies mimicking the genetic role of the pre-existing vulnerabilities of the underlying mechanisms influencing these changes. Discriminating the genetic predispositions of hippocampal subfield atrophy between cognitive aging and neurodegenerative diseases will be helpful in understanding the disease etiology. In this study, we evaluated the polygenic risk of Alzheimer’s disease (AD PGRS) for hippocampal subfield atrophy in 1,086 individuals (319 cognitively normal (CN), 591 mild cognitively impaired (MCI), and 176 Alzheimer’s disease dementia (ADD)). Our results showed a stronger association of AD PGRS effect on the left hemisphere than on the right hemisphere for all the hippocampal subfield volumes in a mixed clinical population (CN+MCI+ADD). The subfields CA1, CA4, hippocampal tail, subiculum, presubiculum, molecular layer, GC-ML-DG, and HATA showed stronger AD PGRS associations with the MCI+ADD group than with the CN group. The subfields CA3, parasubiculum, and fimbria showed moderately higher AD PGRS associations with the MCI+ADD group than with the CN group. Our findings suggest that the eight subfield regions, which were strongly associated with AD PGRS are likely involved in the early stage ADD and a specific focus on the left hemisphere could enhance the early prediction of ADD.
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513 citations