ArticleNeuroImage. Clinical2023
Alzheimer's and vascular disease classification using regional texture biomarkers in FLAIR MRI.
Article in NeuroImage. Clinical, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Machine learning applications in vascular neuroimaging for the diagnosis and prognosis of cognitive impairment and dementia: a systematic review and meta-analysis.Alzheimer's research & therapy · 2025Pooled it
- Impact of cardiometabolic factors and AD plasma biomarkers on white matter hyperintensities volume in individuals with cognitive complaints from the global south.Neuroscience · 2026Article
- Developmental Curves of the Paediatric Brain Using FLAIR MRI Texture Biomarkers.Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes · 2025Article
- Research on magnetic resonance imaging in diagnosis of Alzheimer's disease.European journal of medical research · 2024Review
- Altered brain texture features in end-stage renal disease patients: a voxel-based 3D brain texture analysis study.Frontiers in neuroscience · 2024Article
- Stratifying vascular disease patients into homogeneous subgroups using machine learning and FLAIR MRI biomarkers.Npj imaging · 2024Article
- Brain Maturation Patterns on Normalized FLAIR MR Imaging in Children and Adolescents.AJNR. American journal of neuroradiology · 2023Article
- In Search of a Function for the N6-Methyladenosine in Epitranscriptome, Autophagy and Neurodegenerative Diseases.Neurology international · 2023Review
- Synthesis of diffusion-weighted MRI scalar maps from FLAIR volumes using generative adversarial networks.Frontiers in neuroinformatics · 2023Article
- Detecting conversion from mild cognitive impairment to Alzheimer's disease using FLAIR MRI biomarkers.NeuroImage. Clinical · 2023Article
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Interactions between subcortical vascular disease and dementia due to Alzheimer's disease (AD) are unclear, and clinical overlap between the diseases makes diagnosis challenging. Existing studies have shown regional microstructural changes specific to each disease, and that textures in fluid-attenuated inversion recovery (FLAIR) MRI images may characterize abnormalities in tissue microstructure. This work aims to investigate regional FLAIR biomarkers that can differentiate dementia cohorts with and without subcortical vascular disease. FLAIR and diffusion MRI (dMRI) volumes were obtained in 65 mild cognitive impairment (MCI), 21 AD, 44 subcortical vascular MCI (scVMCI), 22 Mixed etiology, and 48 healthy elderly patients. FLAIR texture and intensity biomarkers were extracted from the normal appearing brain matter (NABM), WML penumbra, blood supply territory (BST), and white matter tract regions of each patient. All FLAIR biomarkers were correlated to dMRI metrics in each region and global WML load, and biomarker means between groups were compared using ANOVA. Binary classifications were performed using Random Forest classifiers to investigate the predictive nature of the regional biomarkers, and SHAP feature analysis was performed to further investigate optimal regions of interest for differentiating disease groups. The regional FLAIR biomarkers were strongly correlated to MD, while all biomarker regions but white matter tracts were strongly correlated to WML burden. Classification between Mixed disease and healthy, AD, and scVMCI patients yielded accuracies of 97%, 81%, and 72% respectively using WM tract biomarkers. Classification between scVMCI and healthy, MCI, and AD patients yielded accuracies of 89%, 84%, and 79% respectively using penumbra biomarkers. Only the classification between AD and healthy patients had optimal results using NABM biomarkers. This work presents novel regional FLAIR biomarkers that may quantify white matter degeneration related to subcortical vascular disease, and which indicate that investigating degeneration in specific regions may be more important than assessing global WML burden in vascular disease groups.
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