4.5 Article

Fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA

期刊

NEUROIMAGE-CLINICAL
卷 32, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.nicl.2021.102874

关键词

Fusion analysis; Structural magnetic resonance imaging; Diffusion tensor imaging; Subjective cognitive decline; Mild cognitive impairment

资金

  1. National Natural Science Foundation of China [81760886, 81871443, 82060315, 82102032]
  2. Science and Technology Plan of Guangxi [14124004-1-27]
  3. Guangxi Natural Science Foundation [2016GXNSFAA380086]
  4. Natural Science Foundation of Guangdong Province [2021A1515011152]
  5. Shenzhen Peacock Plan [KQTD2016053112051497]
  6. Science, Technology and Innovation Commission of Shenzhen Munici-pality Technology Fund [2021SHIBS0003, KCXFZ20201221173400001]

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This study conducted fusion analysis of structural MRI and DTI using mCCA-jICA, revealing joint-discriminative independent components of GM and FA in SCD and MCI patients. The findings showed shared abnormalities in specific brain regions, confirming the simultaneous GM and WM changes underlying cognitive decline, suggesting that multimodal fusion analysis provides a more comprehensive understanding of the neuropathological mechanism in SCD and MCI.
Background: Previous multimodal neuroimaging studies analyzed each dataset independently in subjective cognitive decline (SCD) and mild cognitive impairment (MCI), missing the cross-information. Multi-modal fusion analysis can provide more integral and comprehensive information regarding the brain. There has been a paucity of research on fusion analysis of sMRI and DTI in SCD and MCI. Materials and Methods: In the present study, we conducted fusion analysis of structural MRI and DTI by applying multimodal canonical correlation analysis with joint independent component analysis (mCCA-jICA) to capture the cross-information of gray matter (GM) and white matter (WM) in 62 SCD patients, 99 MCI patients, and 70 healthy controls (HCs). We further analyzed correlations between the mixing coefficients of mCCA-jICA and neuropsychological scores among the three groups. Results: A set of joint-discriminative independent components of GM and fractional anisotropy (FA) exhibited significant links between SCD and HCs, as well as between MCI and HCs. The covariant abnormalities primarily involved the frontal lobe/middle temporal gyrus/calcarine sulcus-anterior thalamic radiation/superior longitudinal fasciculus in SCD, and middle temporal gyrus/ fusiform gyrus/caudate necleus-forceps minor/anterior thalamic radiation in MCI. There was no significant difference between SCD and MCI groups. Conclusions: The covariant GM-WM abnormalities in SCD and MCI were found in specific brain regions involved in cognitive processing, which confirms the simultaneous GM and WM changes underlying cognitive decline. These findings suggest that multimodal fusion analysis allows for a more comprehensive understanding of the association among different types of brain tissues and its crucial role in the neuropathological mechanism of SCD and MCI.

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