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

doi:10.3389/fnins.2023.1162096

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

Front Neurosci. 2023 Aug 31:17:1162096. doi: 10.3389/fnins.2023.1162096. eCollection 2023.

Authors

Qinzhu Yang¹, Shuxiu Cai¹, Guojing Chen¹, Xiaxia Yu¹, Renee F Cattell^{2

3}, Tammy Riklin Raviv⁴, Chuan Huang^{5

6}, Nu Zhang⁷, Yi Gao^{1

8

9}

Affiliations

¹ School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, Guangdong, China.
² Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States.
³ Department of Radiation Oncology, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, United States.
⁴ The School of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Be'er Sheva, Israel.
⁵ Department of Psychiatry, Stony Brook University, Stony Brook, NY, United States.
⁶ Department of Radiology, Stony Brook University, Stony Brook, NY, United States.
⁷ Department of Neurosurgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China.
⁸ Shenzhen Key Laboratory of Precision Medicine for Hematological Malignancies, Shenzhen, China.
⁹ Marshall Laboratory of Biomedical Engineering, Shenzhen University, Shenzhen, China.

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.

Keywords: MRI; deep learning; fine-scale segmentation; hippocampus; shape analysis.

Grants and funding

This work was partially supported by the Key-Area Research and Development Program of Guangdong Province (Grant Number 2021B0101420005), the Key Technology Development Program of Shenzhen (Grant Number JSGG20210713091811036), the Department of Education of Guangdong Province (Grant Number 2017KZDXM072), the National Natural Science Foundation of China (Grant Number 61601302), the Shenzhen Key Laboratory Foundation (Grant Number ZDSYS20200811143757022), Shenzhen Peacock Plan (Grant Number KQTD2016053112051497), and the SZU Top Ranking Project (Grant Number 86000000210).