Incomplete hippocampal inversion and hippocampal subfield volumes: Implementation and inter-reliability of automatic segmentation

TL;DR

This study evaluates the reliability of automatic hippocampal subfield segmentation methods and investigates how incomplete hippocampal inversion relates to specific subfield volume differences in healthy young adults.

Contribution

It demonstrates high inter-method reliability for automatic segmentation and reveals associations between IHI scores and subfield volume variations.

Findings

Strong correlation between segmentation methods.

Higher IHI scores linked to larger subiculum.

Higher IHI scores linked to smaller CA1.

Abstract

The incomplete hippocampal inversion (IHI) is an atypical anatomical pattern of the hippocampus. However, the hippocampus is not a homogeneous structure, as it consists of segregated subfields with specific characteristics. While IHI is not related to whole hippocampal volume, higher IHI scores have been associated to smaller CA1 in aging. Although the segmentation of hippocampal subfields is challenging due to their small size, there are algorithms allowing their automatic segmentation. By using a Human Connectome Project dataset of healthy young adults, we first tested the inter-reliability of two methods for automatic segmentation of hippocampal subfields, and secondly, we explored the relationship between IHI and subfield volumes. Results evidenced strong correlations between volumes obtained thorough both segmentation methods. Furthermore, higher IHI scores were associated to bigger subiculum and smaller CA1 volumes. Here, we provide new insights regarding IHI subfields volumetry, and we offer support for automatic segmentation inter-method reliability.