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

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....

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Autores principales:	Lingyan Liang, Zaili Chen, Yichen Wei, Fei Tang, Xiucheng Nong, Chong Li, Bihan Yu, Gaoxiong Duan, Jiahui Su, Wei Mai, Lihua Zhao, Zhiguo Zhang, Demao Deng
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Fusion analysis Structural magnetic resonance imaging Diffusion tensor imaging Subjective cognitive decline Mild cognitive impairment Computer applications to medicine. Medical informatics R858-859.7 Neurology. Diseases of the nervous system RC346-429
Acceso en línea:	https://doaj.org/article/fc227cdae3fb45f58bea4dc796e3892e
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spelling	oai:doaj.org-article:fc227cdae3fb45f58bea4dc796e3892e2021-11-14T04:32:40ZFusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA2213-158210.1016/j.nicl.2021.102874https://doaj.org/article/fc227cdae3fb45f58bea4dc796e3892e2021-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2213158221003181https://doaj.org/toc/2213-1582Background: 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.Lingyan LiangZaili ChenYichen WeiFei TangXiucheng NongChong LiBihan YuGaoxiong DuanJiahui SuWei MaiLihua ZhaoZhiguo ZhangDemao DengElsevierarticleFusion analysisStructural magnetic resonance imagingDiffusion tensor imagingSubjective cognitive declineMild cognitive impairmentComputer applications to medicine. Medical informaticsR858-859.7Neurology. Diseases of the nervous systemRC346-429ENNeuroImage: Clinical, Vol 32, Iss , Pp 102874- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Fusion analysis Structural magnetic resonance imaging Diffusion tensor imaging Subjective cognitive decline Mild cognitive impairment Computer applications to medicine. Medical informatics R858-859.7 Neurology. Diseases of the nervous system RC346-429
spellingShingle	Fusion analysis Structural magnetic resonance imaging Diffusion tensor imaging Subjective cognitive decline Mild cognitive impairment Computer applications to medicine. Medical informatics R858-859.7 Neurology. Diseases of the nervous system RC346-429 Lingyan Liang Zaili Chen Yichen Wei Fei Tang Xiucheng Nong Chong Li Bihan Yu Gaoxiong Duan Jiahui Su Wei Mai Lihua Zhao Zhiguo Zhang Demao Deng Fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA
description	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.
format	article
author	Lingyan Liang Zaili Chen Yichen Wei Fei Tang Xiucheng Nong Chong Li Bihan Yu Gaoxiong Duan Jiahui Su Wei Mai Lihua Zhao Zhiguo Zhang Demao Deng
author_facet	Lingyan Liang Zaili Chen Yichen Wei Fei Tang Xiucheng Nong Chong Li Bihan Yu Gaoxiong Duan Jiahui Su Wei Mai Lihua Zhao Zhiguo Zhang Demao Deng
author_sort	Lingyan Liang
title	Fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA
title_short	Fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA
title_full	Fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA
title_fullStr	Fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA
title_full_unstemmed	Fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA
title_sort	fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal cca-joint ica
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/fc227cdae3fb45f58bea4dc796e3892e
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Fusion analysis of gray matter and white matter in subjective cognitive decline and mild cognitive impairment by multimodal CCA-joint ICA

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