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• Clinical Article •
Application of automated fiber quantification in research of facial emotion recognition in patients with Alzheimer's disease
JIABA Jianming  LUO Lin  YUAN Xiaojun  CHEN Qiang 

Cite this article as: JIABA J M, LUO L, YUAN X J, et al. Application of automated fiber quantification in research of facial emotion recognition in patients with Alzheimer's disease[J]. Chin J Magn Reson Imaging, 2023, 14(5): 66-71. DOI:10.12015/issn.1674-8034.2023.05.013.


[Abstract] Objective To explore the application of automated fiber quantification (AFQ) based on diffusion tensor imaging (DTI) in the neurological basic research of facial emotion recognition (FER) disorder in patients with Alzheimer's disease (AD).Materials and Methods FER test and 3.0T MR Scan were performed in 17 AD patients (AD group) and 2l normal control patients (NC group). Fibers like inferior fronto-occipital fasciculus (IFOF), uncinate fasciculus (UF) and inferior longitudinal fasciculus (ILF) were divided into 100 nodes using AFQ, and then extracted the fractional anisotropy (FA) and mean diffusivity (MD) values of main fibers. The differences in FA and MD values between the two groups of fibers mentioned above were compared using two-tailed t-tests. Age, gender and mini-mental state examination were regarded as covariates, partial correlation analysis was conducted between DTI parameters of damaged fibers and FER scores.Results AFQ analysis showed that the FA values of the middle part (nodes 44-46) of left IFOF and the inferior segment (nodes 89-99) of left UF in AD group were significantly lower than that in NC group (t values were -6.319 and -7.825, both P＜0.05), and were positively correlated with the negative FER scores (r values were 0.386 and 0.384, both P＜0.05). The MD value of the middle part (nodes 45-64) of left inferior ILF in AD group was significantly higher than that in NC group (t=3.059, P＜0.05), and was negatively correlated with the negative FER scores (r=-0.485, P=0.003).Conclusions AFQ can be used to detect the damaged segment of white matter fiber accurately. The impaired of the middle segment of left ILF, left IFOF, and the inferior part of left UF may be the potential neural basis of negative FER disorder in AD patients.
[Keywords] Alzheimer's disease；facial emotion recognition；diffusion tensor imaging；automated fiber quantification；magnetic resonance imaging

JIABA Jianming1, 2   LUO Lin2   YUAN Xiaojun2   CHEN Qiang2*  

1 Baotou Medical College, Inner Mongolia University of Science & Technology, Baotou 014040, China

2 Department of Medical Imaging, the First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science & Technology, Baotou 014010, China

Corresponding author: Chen Q, E-mail: xy198033@sina.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Scientific Research Project of Colleges and Universities in Inner Mongolia Autonomous Region (No. NJZY23021).
Received  2022-11-14
Accepted  2023-04-23
DOI: 10.12015/issn.1674-8034.2023.05.013
Cite this article as: JIABA J M, LUO L, YUAN X J, et al. Application of automated fiber quantification in research of facial emotion recognition in patients with Alzheimer's disease[J]. Chin J Magn Reson Imaging, 2023, 14(5): 66-71. DOI:10.12015/issn.1674-8034.2023.05.013.

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