A survey on applications and analysis methods of functional magnetic resonance imaging for Alzheimer's disease

TY - JOUR

T1 - A survey on applications and analysis methods of functional magnetic resonance imaging for Alzheimer's disease

AU - Forouzannezhad, Parisa

AU - Abbaspour, Alireza

AU - Fang, Chen

AU - Cabrerizo, Mercedes

AU - Loewenstein, David

AU - Duara, Ranjan

AU - Adjouadi, Malek

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Background: Functional magnetic resonance imaging (fMRI) is an MRI-based neuroimaging technique that measures brain activity on the basis of blood oxygenation level. This study reviews the main fMRI methods reported in the literature and their related applications in clinical and preclinical studies, focusing on relating functional brain networks in the prodromal stages of Alzheimer's disease (AD), with a focus on the transition phases from cognitively normal (CN) to mild cognitive impairment (MCI) and from MCI to AD. New method: The purpose of this study is to present and compare different approaches of supervised and unsupervised fMRI analyses and to highlight the different applications of fMRI in the diagnosis of MCI and AD. Results: Survey article asserts that brain network disruptions of a given dysfunction or in relation to disease prone areas of the brain in neurodegenerative dementias could be extremely useful in ascertaining the extent of cognitive deficits at the different stages of the disease. Identifying the earliest changes in these activity patterns is essential for the early planning of treatment and therapeutic protocols. Comparison with existing methods: Analysis methods such as independent component analysis (ICA) and graph theory-based approaches are strong analytical techniques most suitable for functional connectivity investigations. However, graph theory-based approaches have received more attention due to the higher performance they achieve in both functional and effective connectivity studies. Conclusion: This article shows that the disruption of brain connectivity patterns of MCI and AD could be associated with cognitive decline, an interesting finding that could augment the prospects for early diagnosis. More importantly, results reveal that changes in functional connectivity as obtained through fMRI precede detection of cortical thinning in structural MRI and amyloid deposition in positron emission tomography (PET). However, a major challenge in using fMRI as a single imaging modality, like all other imaging modalities used in isolation, is in relating a particular disruption in functional connectivity in relation to a specific disease. This is a challenge that requires more thorough investigation, and one that could perhaps be overcome through multimodal neuroimaging by consolidating the strengths of these individual imaging modalities.

AB - Background: Functional magnetic resonance imaging (fMRI) is an MRI-based neuroimaging technique that measures brain activity on the basis of blood oxygenation level. This study reviews the main fMRI methods reported in the literature and their related applications in clinical and preclinical studies, focusing on relating functional brain networks in the prodromal stages of Alzheimer's disease (AD), with a focus on the transition phases from cognitively normal (CN) to mild cognitive impairment (MCI) and from MCI to AD. New method: The purpose of this study is to present and compare different approaches of supervised and unsupervised fMRI analyses and to highlight the different applications of fMRI in the diagnosis of MCI and AD. Results: Survey article asserts that brain network disruptions of a given dysfunction or in relation to disease prone areas of the brain in neurodegenerative dementias could be extremely useful in ascertaining the extent of cognitive deficits at the different stages of the disease. Identifying the earliest changes in these activity patterns is essential for the early planning of treatment and therapeutic protocols. Comparison with existing methods: Analysis methods such as independent component analysis (ICA) and graph theory-based approaches are strong analytical techniques most suitable for functional connectivity investigations. However, graph theory-based approaches have received more attention due to the higher performance they achieve in both functional and effective connectivity studies. Conclusion: This article shows that the disruption of brain connectivity patterns of MCI and AD could be associated with cognitive decline, an interesting finding that could augment the prospects for early diagnosis. More importantly, results reveal that changes in functional connectivity as obtained through fMRI precede detection of cortical thinning in structural MRI and amyloid deposition in positron emission tomography (PET). However, a major challenge in using fMRI as a single imaging modality, like all other imaging modalities used in isolation, is in relating a particular disruption in functional connectivity in relation to a specific disease. This is a challenge that requires more thorough investigation, and one that could perhaps be overcome through multimodal neuroimaging by consolidating the strengths of these individual imaging modalities.

KW - Alzheimer's disease

KW - fMRI

KW - Functional connectivity

KW - Mild cognitive impairment

KW - Multimodal neuroimaging

KW - Resting-state fMRI

KW - Task-based fMRI

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U2 - 10.1016/j.jneumeth.2018.12.012

DO - 10.1016/j.jneumeth.2018.12.012

M3 - Review article

C2 - 30593787

AN - SCOPUS:85060842403

JO - Journal of Neuroscience Methods

JF - Journal of Neuroscience Methods

SN - 0165-0270

ER -