ArticleAlzheimer's research & therapy2021
An MRI-based strategy for differentiation of frontotemporal dementia and Alzheimer's disease.
Article in Alzheimer's research & therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.
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Who cites it
34 citing papers in PubMed, 2 syntheses or guidelines pooled it, 59 citations in OpenAlex.
- Frontotemporal dementia: a systematic review of artificial intelligence approaches in differential diagnosis.Frontiers in aging neuroscience · 2025Pooled it
- Revolutionizing early Alzheimer's disease and mild cognitive impairment diagnosis: a deep learning MRI meta-analysis.Arquivos de neuro-psiquiatria · 2024Pooled it
- Stakeholders' perspectives on an autonomous brain MRI: An interview study.PEC innovation · 2026Article
- Structural MRI in frontotemporal dementia and Alzheimer's disease: stage-dependent atrophy patterns.Journal of neural transmission (Vienna, Austria : 1996) · 2026Review
- Plasma-Derived miRNAs as Fluid Biomarkers to Differentiate Alzheimer's and Frontotemporal Dementia.Current issues in molecular biology · 2026Article
- Multimodal non-invasive approaches for early Alzheimer's disease detection: a review of neuroelectrophysiological and neuroimaging techniques.Frontiers in psychiatry · 2026Review
- A computational ontology framework for the synthesis of multi-level pathology reports from brain MRI scans.Journal of Alzheimer's disease : JAD · 2025Article
- Interaction of metabolic and inflammatory dysregulation on central degeneration and cognitive function in behavioral variant Frontotemporal dementia.Journal of neurology · 2025Article
- Comprehensive Segmentation of Gray Matter Structures on T1-Weighted Brain MRI: A Comparative Study of Convolutional Neural Network, Convolutional Neural Network Hybrid-Transformer or -Mamba Architectures.AJNR. American journal of neuroradiology · 2025Article
- Regional CSF volume quantification using deep learning for comparative analysis of brain atrophy in frontotemporal dementia subtypes.Frontiers in aging neuroscience · 2025Article
- Integration of Neuroimaging and Molecular Biomarkers in the Diagnosis of Alzheimer's Disease and Frontotemporal Dementia: The Promise of fMRI.Current Alzheimer research · 2025Review
- EEG-based classification of Alzheimer's disease and frontotemporal dementia: a comprehensive analysis of discriminative features.Cognitive neurodynamics · 2024Article
- Automated Volumetric Software in Dementia: Help or Hindrance to the Neuroradiologist?AJNR. American journal of neuroradiology · 2024Article
- Diagnostic utility of brain MRI volumetry in comparing traumatic brain injury, Alzheimer disease and behavioral variant frontotemporal dementia.BMC neurology · 2024Article
- Contrast-enhanced to non-contrast-enhanced image translation to exploit a clinical data warehouse of T1-weighted brain MRI.BMC medical imaging · 2024Article
- The effect of aperiodic components in distinguishing Alzheimer's disease from frontotemporal dementia.GeroScience · 2024Article
- Strategies for translating proteomics discoveries into drug discovery for dementia.Neural regeneration research · 2024Review
- Advances in Alzheimer's Disease Biomarkers.Current Alzheimer research · 2024Review
- Divergent brain regional atrophy and associated fiber disruption in amnestic and non-amnestic MCI.Alzheimer's research & therapy · 2023Article
- The use of neuroimaging techniques in the early and differential diagnosis of dementia.Molecular psychiatry · 2023Review
Corrections and comments
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Authors and funding
15 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundThe differential diagnosis of frontotemporal dementia (FTD) and Alzheimer's disease (AD) is difficult due to the overlaps of clinical symptoms. Structural magnetic resonance imaging (sMRI) presents distinct brain atrophy and potentially helps in their differentiation. In this study, we aim at deriving a novel integrated index by leveraging the volumetric measures in brain regions with significant difference between AD and FTD and developing an MRI-based strategy for the differentiation of FTD and AD.
methodsIn this study, the data were acquired from three different databases, including 47 subjects with FTD, 47 subjects with AD, and 47 normal controls in the NACC database; 50 subjects with AD in the ADNI database; and 50 subjects with FTD in the FTLDNI database. The MR images of all subjects were automatically segmented, and the brain atrophy, including the AD resemblance atrophy index (AD-RAI), was quantified using AccuBrain®. A novel MRI index, named the frontotemporal dementia index (FTDI), was derived as the ratio between the weighted sum of the volumetric indexes in "FTD dominant" structures over that obtained from "AD dominant" structures. The weights and the identification of "FTD/AD dominant" structures were acquired from the statistical analysis of NACC data. The differentiation performance of FTDI was validated using independent data from ADNI and FTLDNI databases.
resultsAD-RAI is a proven imaging biomarker to identify AD and FTD from NC with significantly higher values (p < 0.001 and AUC = 0.88) as we reported before, while no significant difference was found between AD and FTD (p = 0.647). FTDI showed excellent accuracy in identifying FTD from AD (AUC = 0.90; SEN = 89%, SPE = 75% with threshold value = 1.08). The validation using independent data from ADNI and FTLDNI datasets also confirmed the efficacy of FTDI (AUC = 0.93; SEN = 96%, SPE = 70% with threshold value = 1.08).
conclusionsBrain atrophy in AD, FTD, and normal elderly shows distinct patterns. In addition to AD-RAI that is designed to detect abnormal brain atrophy in dementia, a novel index specific to FTD is proposed and validated. By combining AD-RAI and FTDI, an MRI-based decision strategy was further proposed as a promising solution for the differential diagnosis of AD and FTD in clinical practice.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.