Hippocampal subfield volumes across the healthy lifespan and the effects of MR sequence on estimates [article]

Aurelie Bussy, Eric Plitman, Raihaan Patel, Stephanie Tullo, Alyssa Salaciak, Saashi Bedford, Sarah Farzin, Marie-Lise Beland, Vanessa Valiquette, Christina Kazazian, Christine Tardif, Gabriel Devenyi (+1 others)
2020 bioRxiv   pre-print
The hippocampus has been extensively studied in various neuropsychiatric disorders throughout the lifespan. However, inconsistent results have been reported with respect to which subfield volumes are most related to age. Here, we investigate whether these discrepancies may be explained by experimental design differences that exist between studies. Multiple datasets were used to collect 1690 magnetic resonance scans from healthy individuals aged 18-95 years old. Standard T1-weighted (T1w; MPRAGE
more » ... sequence, 1 mm3 voxels), high-resolution T2-weighted (T2w; SPACE sequence, 0.64 mm3 voxels) and slab T2-weighted (Slab; 2D turbo spin echo, 0.4 x 0.4 x 2 mm3 voxels) images were acquired. The MAGeT Brain algorithm was used for segmentation of the hippocampal grey matter (GM) subfields and peri-hippocampal white matter (WM) subregions. Linear mixed-effect models and Akaike information criterion were used to examine linear, second or third order natural splines relationship between hippocampal volumes and age. We demonstrated that stratum radiatum/lacunosum/moleculare and fornix subregions expressed the highest relative volumetric decrease, while the cornus ammonis 1 presented a relative volumetric preservation of its volume with age. We also found that volumes extracted from slab images were often underestimated and demonstrated different age-related relationships compared to volumes extracted from T1w and T2w images. The current work suggests that although T1w, T2w and slab derived subfield volumetric outputs are largely homologous, modality choice plays a meaningful role in the volumetric estimation of the hippocampal subfields.
doi:10.1101/2020.05.28.121343 fatcat:yyl3xafgtvgmnnqk3whofm3mse