Evaluation of surface-based hippocampal registration using ground-truth subfield definitions

• Published in: eLife Vol. 12
• Main Authors: DeKraker, Jordan, Palomero-Gallagher, Nicola, Kedo, Olga, Ladbon-Bernasconi, Neda, Muenzing, Sascha E A, Axer, Markus, Amunts, Katrin, Khan, Ali R, Bernhardt, Boris C, Evans, Alan C
• Format: Journal Article
• Language: English
• Published: England eLife Science Publications, Ltd 13.11.2023; eLife Sciences Publications Ltd; eLife Sciences Publications, Ltd
• Subjects: Amunts, Katrin; Brain; Datasets; hippocampal subfields; Hippocampus; Hippocampus - diagnostic imaging; Hippocampus - pathology; Histological Techniques; Histology; image registration; Magnetic Resonance Imaging - methods; MRI; Nervous system diseases; Neurological diseases; Neuroscience; Registration; Temporal Lobe; Tools and Resources; visualization; Canada; visualization; hippocampal subfields; histology; MRI; image registration; neuroscience; human
• ISSN: 2050-084X; 2050-084X
• DOI: 10.7554/eLife.88404

The hippocampus is an archicortical structure, consisting of subfields with unique circuits. Understanding its microstructure, as proxied by these subfields, can improve our mechanistic understanding of learning and memory and has clinical potential for several neurological disorders. One prominent issue is how to parcellate, register, or retrieve homologous points between two hippocampi with grossly different morphologies. Here, we present a surface-based registration method that solves this issue in a contrast-agnostic, topology-preserving manner. Specifically, the entire hippocampus is first analytically unfolded, and then samples are registered in 2D unfolded space based on thickness, curvature, and gyrification. We demonstrate this method in seven 3D histology samples and show superior alignment with respect to subfields using this method over more conventional registration approaches.