Journal of Shanghai Jiao Tong University (Medical Science) ›› 2023, Vol. 43 ›› Issue (3): 342-349.doi: 10.3969/j.issn.1674-8115.2023.03.010

• Techniques and methods • Previous Articles    

Application of digital terrain analysis to the study of cerebral cortex morphology

YANG Zihao1,2(), CHEN Nan1,2(), LIN Siwei3   

  1. 1.Key Lab for Spatial Data Mining and Information Sharing of Education Ministry, Fuzhou University, Fuzhou 350108, China
    2.The Academy of Digital China, Fuzhou University, Fuzhou 350108, China
    3.School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210023, China
  • Received:2022-09-29 Accepted:2023-02-25 Online:2023-03-28 Published:2023-03-28
  • Contact: CHEN Nan E-mail:172732351@qq.com;chennan@fzu.edu.cn
  • Supported by:
    National Nature Science Fundation of China(41771423)

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Abstract:

Objective ·To propose a theoretical method based on geosciences for the expression and quantitative description of the surface morphology of the cerebral cortex. Methods ·Eighty-five samples of normal cognition (NC) and 84 samples of Alzheimer′s disease (AD) were downloaded from the Alzheimer′s Disease Neuroimaging Initiative (ADNI) database, and the cerebral cortex data of magnetic resonance imaging (MRI) images of the human brain were extracted by using SPM 12 software package. The undulating cerebral cortex image was mapped into the point cloud data after three-dimensional reconstruction, and the digital elevation model (DEM) of the brain was further constructed according to the theoretical method of digital terrain analysis to realize the digital expression of the cerebral cortex morphology. The study introduced terrain factors′ indicators such as roughness, relief amplitude and elevation in geoscience to quantitatively describe the morphological characteristics of the cerebral cortex. Covariance analysis was conducted with age as the covariate, and independent sample t test was conducted with gender into groups and NC samples and AD samples as the variables, terrain factors as the group and left and right hemispheres as the variables to reveal the change rule of cerebral cortex morphology. Results ·The roughness, relief amplitude and thickness of the cerebral cortex were linearly distributed with age, and the differences between the AD group and the NC group were all statistically significant (all P<0.05); the roughness and relief amplitude of both men and women showed that the AD group was larger than the NC group (both P<0.05), the cortical thickness showed that the AD group was smaller than the NC group (P=0.000), and the elevation only had an inter-group difference in women (P=0.043); the left hemisphere roughness, relief amplitude and elevation values of NC group were higher than those of the right hemisphere (all P<0.05), while AD only had inter-group differences in elevation indicators (P=0.000). Conclusion ·Terrain factors can significantly distinguish the cerebral cortex differences between AD and NC patients, and has a good distinction when age, gender and left and right hemisphere are used as variables. It is expected to provide an auxiliary means for the medical quantification of cerebral cortex morphology.

Key words: digital terrain analysis, terrain factor, cerebral cortex, Alzheimer′s disease (AD), cortical thickness

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