Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review
Resting-state fMRI (rs-fMRI) detects functional connectivity (FC) abnormalities that occur in the brains of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). FC of the default mode network (DMN) is commonly impaired in AD and MCI. We conducted a systematic review aimed...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley-Liss Inc.
2021
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| Online Access: | http://psasir.upm.edu.my/id/eprint/96716/1/ABSTRACT.pdf |
| _version_ | 1825937753775276032 |
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| author | Ibrahim, Buhari Suppiah, Subapriya Ibrahim, Normala Mohamad, Mazlyfarina Abu Hassan, Hasyma Syed Nasser, Nisha Saripan, M. Iqbal |
| author_facet | Ibrahim, Buhari Suppiah, Subapriya Ibrahim, Normala Mohamad, Mazlyfarina Abu Hassan, Hasyma Syed Nasser, Nisha Saripan, M. Iqbal |
| author_sort | Ibrahim, Buhari |
| collection | UPM |
| description | Resting-state fMRI (rs-fMRI) detects functional connectivity (FC) abnormalities that occur in the brains of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). FC of the default mode network (DMN) is commonly impaired in AD and MCI. We conducted a systematic review aimed at determining the diagnostic power of rs-fMRI to identify FC abnormalities in the DMN of patients with AD or MCI compared with healthy controls (HCs) using machine learning (ML) methods. Multimodal support vector machine (SVM) algorithm was the commonest form of ML method utilized. Multiple kernel approach can be utilized to aid in the classification by incorporating various discriminating features, such as FC graphs based on "nodes" and "edges" together with structural MRI-based regional cortical thickness and gray matter volume. Other multimodal features include neuropsychiatric testing scores, DTI features, and regional cerebral blood flow. Among AD patients, the posterior cingulate cortex (PCC)/Precuneus was noted to be a highly affected hub of the DMN that demonstrated overall reduced FC. Whereas reduced DMN FC between the PCC and anterior cingulate cortex (ACC) was observed in MCI patients. Evidence indicates that the nodes of the DMN can offer moderate to high diagnostic power to distinguish AD and MCI patients. Nevertheless, various concerns over the homogeneity of data based on patient selection, scanner effects, and the variable usage of classifiers and algorithms pose a challenge for ML-based image interpretation of rs-fMRI datasets to become a mainstream option for diagnosing AD and predicting the conversion of HC/MCI to AD. |
| first_indexed | 2024-03-06T11:04:19Z |
| format | Article |
| id | upm.eprints-96716 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T11:04:19Z |
| publishDate | 2021 |
| publisher | Wiley-Liss Inc. |
| record_format | dspace |
| spelling | upm.eprints-967162022-12-01T08:49:30Z http://psasir.upm.edu.my/id/eprint/96716/ Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review Ibrahim, Buhari Suppiah, Subapriya Ibrahim, Normala Mohamad, Mazlyfarina Abu Hassan, Hasyma Syed Nasser, Nisha Saripan, M. Iqbal Resting-state fMRI (rs-fMRI) detects functional connectivity (FC) abnormalities that occur in the brains of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). FC of the default mode network (DMN) is commonly impaired in AD and MCI. We conducted a systematic review aimed at determining the diagnostic power of rs-fMRI to identify FC abnormalities in the DMN of patients with AD or MCI compared with healthy controls (HCs) using machine learning (ML) methods. Multimodal support vector machine (SVM) algorithm was the commonest form of ML method utilized. Multiple kernel approach can be utilized to aid in the classification by incorporating various discriminating features, such as FC graphs based on "nodes" and "edges" together with structural MRI-based regional cortical thickness and gray matter volume. Other multimodal features include neuropsychiatric testing scores, DTI features, and regional cerebral blood flow. Among AD patients, the posterior cingulate cortex (PCC)/Precuneus was noted to be a highly affected hub of the DMN that demonstrated overall reduced FC. Whereas reduced DMN FC between the PCC and anterior cingulate cortex (ACC) was observed in MCI patients. Evidence indicates that the nodes of the DMN can offer moderate to high diagnostic power to distinguish AD and MCI patients. Nevertheless, various concerns over the homogeneity of data based on patient selection, scanner effects, and the variable usage of classifiers and algorithms pose a challenge for ML-based image interpretation of rs-fMRI datasets to become a mainstream option for diagnosing AD and predicting the conversion of HC/MCI to AD. Wiley-Liss Inc. 2021 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/96716/1/ABSTRACT.pdf Ibrahim, Buhari and Suppiah, Subapriya and Ibrahim, Normala and Mohamad, Mazlyfarina and Abu Hassan, Hasyma and Syed Nasser, Nisha and Saripan, M. Iqbal (2021) Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review. Human Brain Mapping, 42 (9). 2941 - 2968. ISSN 1065-9471; ESSN: 1097-0193 https://onlinelibrary.wiley.com/doi/10.1002/hbm.25369 10.1002/hbm.25369 |
| spellingShingle | Ibrahim, Buhari Suppiah, Subapriya Ibrahim, Normala Mohamad, Mazlyfarina Abu Hassan, Hasyma Syed Nasser, Nisha Saripan, M. Iqbal Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review |
| title | Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review |
| title_full | Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review |
| title_fullStr | Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review |
| title_full_unstemmed | Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review |
| title_short | Diagnostic power of resting-state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: a systematic review |
| title_sort | diagnostic power of resting state fmri for detection of network connectivity in alzheimer s disease and mild cognitive impairment a systematic review |
| url | http://psasir.upm.edu.my/id/eprint/96716/1/ABSTRACT.pdf |
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