Age-related differences in hippocampal subfield volumes across the human lifespan: A meta-analysis.

The human hippocampus (Hc) is critical for memory function across the lifespan. It is comprised of cytoarchitectonically distinct subfields: dentate gyrus (DG), cornu ammonis sectors (CA) 1-4, and subiculum, each of which may be differentially susceptible to neurodevelopmental and neurodegenerative mechanisms. Identifying age-related differences in Hc subfield volumes can provide insights into neural mechanisms of memory function across the lifespan. Limited evidence suggests that DG and CA3 volumes differ across development while other regions remain relatively stable, and studies of adulthood implicate a downward trend in all subfield volumes with prominent age effects on CA1. Due to differences in methods and limited sampling for any single study, the magnitude of age effects on Hc subfield volumes and their probable lifespan trajectories remain unclear. Here, we conducted a meta-analysis on cross-sectional studies (n = 48,278 participants, ages = 4-94 years) to examine the association between age and Hc subfield volumes in development (n = 11 studies), adulthood (n = 30 studies), and a combined lifespan sample (n = 41 studies) while adjusting estimates for sample sizes. In development, age was positively associated with DG and CA3-4 volumes, whereas in adulthood a negative association was observed with all subfield volumes. Notably, the observed age effects were not different across subfield volumes within each age group. All subfield volumes showed a nonlinear age pattern across the lifespan with DG and CA3-4 volumes showing a more distinct age trajectory as compared to the other subfields. Lastly, among all the study-level variables, only female percentage of the study sample moderated the age effect on CA1 volume: a higher female-to-male ratio in the study sample was linked to the greater negative association between age and CA1 volume. These results document that Hc subfield volumes differ as a function of age offering broader implications for constructing theoretical models of lifespan memory development.

Development and validation of a quality control procedure for automatic segmentation of hippocampal subfields.

Automatic segmentation methods for in vivo magnetic resonance imaging are increasing in popularity because of their high efficiency and reproducibility. However, automatic methods can be perfectly reliable and consistently wrong, and the validity of automatic segmentation methods cannot be taken for granted. Quality control (QC) by trained and reliable human raters is necessary to ensure the validity of automatic measurements. Yet QC practices for applied neuroimaging research are underdeveloped. We report a detailed QC and correction procedure to accompany our validated atlas for hippocampal subfield segmentation. We document a two-step QC procedure for identifying segmentation errors, along with a taxonomy of errors and an error severity rating scale. This detailed procedure has high between-rater reliability for error identification and manual correction. The latter introduces at maximum 3% error variance in volume measurement. All procedures were cross-validated on an independent sample collected at a second site with different imaging parameters. The analysis of error frequency revealed no evidence of bias. An independent rater with a third sample replicated procedures with high within-rater reliability for error identification and correction. We provide recommendations for implementing the described method along with hypothesis testing strategies. In sum, we present a detailed QC procedure that is optimized for efficiency while prioritizing measurement validity and suits any automatic atlas.