ArticleHeliyon2022
MRI biomarkers for Alzheimer's disease: the impact of functional connectivity in the default mode network and structural connectivity between lobes on diagnostic accuracy.
Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Obstructive sleep apnea and attention deficits: A systematic review of magnetic resonance imaging biomarkers and neuropsychological assessments.Brain and behavior · 2023Pooled it
- Targeted nanomedicine strategies for Alzheimer's disease therapy.Discover nano · 2026Review
- Using diffusion MRI to relate hippocampal subfield microstructure to delayed verbal memory in cognitively intact individuals at genetic risk for developing Alzheimer's disease.Experimental gerontology · 2026Article
- Multimodal MRI to elucidate cross-organ coupling mechanisms of the heart-brain axis.Frontiers in cardiovascular medicine · 2026Review
- Neurite Degradation Mediates the Effect of Amyloid Deposition on Global Cognition in Asymptomatic Older Adults.medRxiv : the preprint server for health sciences · 2025Article
- Obstructive Sleep Apnea Treatment for Brain Health: Improvement in Connectivity but Not Measurable Function?American journal of respiratory and critical care medicine · 2025Article
- Advances in the fMRI analysis of the default mode network: a review.Brain structure & function · 2024Review
- Which neuroimaging and fluid biomarkers method is better in theranostic of Alzheimer's disease? An umbrella review.IBRO neuroscience reports · 2024Review
- Lateralized brunt of sleep deprivation on white matter injury in a rat model of Alzheimer's disease.GeroScience · 2024Article
- Beyond CSF and Neuroimaging Assessment: Evaluating Plasma miR-145-5p as a Potential Biomarker for Mild Cognitive Impairment and Alzheimer's Disease.ACS chemical neuroscience · 2024Article
- BNLoop-GAN: a multi-loop generative adversarial model on brain network learning to classify Alzheimer's disease.Frontiers in neuroscience · 2023Review
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAt present, clinical use of MRI in Alzheimer's disease (AD) is mostly focused on the assessment of brain atrophy, namely in the hippocampal region. Despite this, multiple biomarkers reflecting structural and functional brain connectivity changes have shown promising results in the assessment of AD. To help identify the most relevant ones that may stand a chance of being used in clinical practice, we compared multiple biomarker in terms of their value to discriminate AD from healthy controls and analyzed their age dependency.
methods20 AD patients and 20 matched controls underwent MRI-scanning (3T GE), including T1-weighted, diffusion-MRI, and resting-state-fMRI (rsfMRI). Whole brain, white matter, gray matter, cortical gray matter and hippocampi volumes were measured using icobrain. rsfMRI between regions of the default-mode-network (DMN) was assessed using group independent-component-analysis. Median diffusivity and kurtosis were determined in gray and white-matter. DTI data was used to evaluate pairwise structural connectivity between lobar regions and the hippocampi.Logistic-Regression and Random-Forest models were trained to classify AD-status based on, respectively different isolated features and age, and feature-groups combined with age.
resultsHippocampal features, features reflecting the functional connectivity between the medial-Pre-Frontal-Cortex (mPFC) and the posterior regions of the DMN, and structural interhemispheric frontal connectivity showed the strongest differences between AD-patients and controls. Structural interhemispheric parietal connectivity, structural connectivity between the parietal lobe and hippocampus in the right hemisphere, and mPFC-DMN-features, showed only an association with AD-status (p < 0.05) but not with age. Hippocampi volumes showed an association both with age and AD-status (p < 0.05).Smallest-hippocampus-volume was the most discriminative feature. The best performance (accuracy:0.74, sensitivity:0.74, specificity:0.74) was obtained with an RF-model combining the best feature from each feature-group (smallest hippocampus volume, WM volume, median GM MD, lTPJ-mPFC connectivity and structural interhemispheric frontal connectivity) and age.
conclusionsBrain connectivity changes caused by AD are reflected in multiple MRI-biomarkers. Decline in both the functional DMN-connectivity and the parietal interhemispheric structural connectivity may assist sepparating healthy-aging driven changes from AD, complementing hippocampal volumes which are affected by both aging and AD.
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