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
N1 - Funding Information:
We are grateful for the continued support from the National Science Foundation under NSF grants CNS-1532061 , CNS-133892 , CNS-1551221 , and CNS-1429345 . We also greatly appreciate the support of the Ware Foundation and the Florida ADRC .
Publisher Copyright:
© 2018
PY - 2019/4/1
Y1 - 2019/4/1
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 - Functional connectivity
KW - Mild cognitive impairment
KW - Multimodal neuroimaging
KW - Resting-state fMRI
KW - Task-based fMRI
KW - 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
VL - 317
SP - 121
EP - 140
JO - Journal of Neuroscience Methods
JF - Journal of Neuroscience Methods
SN - 0165-0270
ER -