Fine scale hippocampus morphology variation cross 552 healthy subjects from age 20 to 80

Qinzhu Yang, Shuxiu Cai, Guojing Chen, Xiaxia Yu, Renee F. Cattell, Tammy Riklin Raviv, Chuan Huang, Nu Zhang, Yi Gao

Research output: Contribution to journalArticlepeer-review

Abstract

The cerebral cortex varies over the course of a person's life span: at birth, the surface is smooth, before becoming more bumpy (deeper sulci and thicker gyri) in middle age, and thinner in senior years. In this work, a similar phenomenon was observed on the hippocampus. It was previously believed the fine-scale morphology of the hippocampus could only be extracted only with high field scanners (7T, 9.4T); however, recent studies show that regular 3T MR scanners can be sufficient for this purpose. This finding opens the door for the study of fine hippocampal morphometry for a large amount of clinical data. In particular, a characteristic bumpy and subtle feature on the inferior aspect of the hippocampus, which we refer to as hippocampal dentation, presents a dramatic degree of variability between individuals from very smooth to highly dentated. In this report, we propose a combined method joining deep learning and sub-pixel level set evolution to efficiently obtain fine-scale hippocampal segmentation on 552 healthy subjects. Through non-linear dentation extraction and fitting, we reveal that the bumpiness of the inferior surface of the human hippocampus has a clear temporal trend. It is bumpiest between 40 and 50 years old. This observation should be aligned with neurodevelopmental and aging stages.

Original languageEnglish
Article number1162096
JournalFrontiers in Neuroscience
Volume17
DOIs
StatePublished - 1 Jan 2023

Keywords

  • deep learning
  • fine-scale segmentation
  • hippocampus
  • MRI
  • shape analysis

ASJC Scopus subject areas

  • General Neuroscience

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