Quantifying numerical and spatial reliability of hippocampal and amygdala subdivisions in FreeSurfer

Abstract

On-going, large-scale neuroimaging initiatives can aid in uncovering neurobiological causes and correlates of poor mental health, disease pathology, and many other important conditions. As projects grow in scale with hundreds, even thousands, of individual participants and scans collected, quantification of brain structures by automated algorithms is becoming the only truly tractable approach. Here, we assessed the spatial and numerical reliability for newly deployed automated segmentation of hippocampal subfields and amygdala nuclei in FreeSurfer 7. In a sample of participants with repeated structural imaging scans (N = 928), we found numerical reliability (as assessed by intraclass correlations, ICCs) was reasonable. Approximately 95% of hippocampal subfields had “excellent” numerical reliability (ICCs ≥ 0.90), while only 67% of amygdala subnuclei met this same threshold. In terms of spatial reliability, 58% of hippocampal subfields and 44% of amygdala subnuclei had Dice coefficients ≥ 0.70. Notably, multiple regions had poor numerical and/or spatial reliability. We also examined correlations between spatial reliability and person-level factors (e.g., participant age; T1 image quality). Both sex and image scan quality were related to variations in spatial reliability metrics. Examined collectively, our work suggests caution should be exercised for a few hippocampal subfields and amygdala nuclei with more variable reliability. Graphical Abstract

Atrophy patterns in hippocampal subregions and their relationship with cognitive function in fibromyalgia patients with mild cognitive impairment

“…We also extracted the estimated total intracranial volume (eTIV) from the segmentation files as a covariate in the statistical analysis of data; this volume plays a vital role in evaluating hippocampal subfield volumes. Importantly, the reliability and validity of the FreeSurfer hippocampal segmentation protocol have been previously demonstrated ( Iglesias et al, 2015 ; Kahhale et al, 2023 ).…”

Differential longitudinal changes of hippocampal subfields in patients with anorexia nervosa

“…granule cell and molecular layer of the dentate gyrus). 47 Including additional scans of the hippocampus in higher resolutions or incorporating T2 imaging sequences could mitigate such underestimations.…”

“…We included the hippocampal fissure in the main analysis model but excluded it from further examination since it does not measure GM mass, but rather cerebrospinal fluid and has high numeric and spatial measurement uncertainty. 47 Statistical analyses of the cross-sectional data For the cross-sectional analyses, hippocampal subfield volumes were modeled using general linear models (GLMs) with the study group (AcAN-TP1, HC) as the predictor of interest, and, as covariates, age up to quadratic terms based on previous literature 10,48,49 in line with ENIGMA studies, 50,51 and estimated total intracranial volume (eTIV) as an established correction method of brain volumes for head size variation. 52 Multiple testing adjustment of P-values using false discovery rate (FDR) 53 was applied across all hippocampal subfields.…”