ArticleHuman brain mapping2014
The power of neuroimaging biomarkers for screening frontotemporal dementia.
Article in Human brain mapping, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.
- Morphometric MRI as a diagnostic biomarker of frontotemporal dementia: A systematic review to determine clinical applicability.NeuroImage. Clinical · 2018Pooled it
- Distinct and shared multimodal neuroimaging patterns in clinical frontotemporal dementia syndromes.Brain communications · 2026Article
- Multiparametric MRI-based biomarkers in the non-fluent and semantic variants of primary progressive aphasia.Journal of neurology · 2025Article
- Atrophy in behavioural variant frontotemporal dementia spans multiple large-scale prefrontal and temporal networks.Brain : a journal of neurology · 2023Article
- Association of blood pressure variability during acute care hospitalization and incident dementia.Frontiers in neurology · 2023Article
- Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference.Network neuroscience (Cambridge, Mass.) · 2023Article
- A Reproducible Deep-Learning-Based Computer-Aided Diagnosis Tool for Frontotemporal Dementia Using MONAI and Clinica Frameworks.Life (Basel, Switzerland) · 2022Article
- Neuroimaging in Frontotemporal Lobar Degeneration: Research and Clinical Utility.Advances in experimental medicine and biology · 2021Review
- Isolation and characterization of antibody fragments selective for human FTD brain derived TDP-43 variants.BMC neuroscience · 2020Article
- Evaluating the reliability of neurocognitive biomarkers of neurodegenerative diseases across countries: A machine learning approach.NeuroImage · 2020Article
- The pulvinar nucleus and antidepressant treatment: dynamic modeling of antidepressant response and remission with ultra-high field functional MRI.Molecular psychiatry · 2019Article
- Cortical microstructure in the behavioural variant of frontotemporal dementia: looking beyond atrophy.Brain : a journal of neurology · 2019Article
- [Pattern recognition analysis of Alzheimer's disease based on brain structure network].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2019Article
- Measurement Challenges in Research With Individuals With Cognitive Impairment.Research in gerontological nursing · 2019Article
- Tau PET imaging predicts cognition in atypical variants of Alzheimer's disease.Human brain mapping · 2018Article
- Single-subject classification of presymptomatic frontotemporal dementia mutation carriers using multimodal MRI.NeuroImage. Clinical · 2018Article
- Longitudinal Diffusion Tensor Imaging Resembles Patterns of Pathology Progression in Behavioral Variant Frontotemporal Dementia (bvFTD).Frontiers in aging neuroscience · 2018Article
- Systems Biology Understanding of the Effects of Lithium on Affective and Neurodegenerative Disorders.Frontiers in neuroscience · 2018Article
- Towards a Unified Understanding of Lithium Action in Basic Biology and its Significance for Applied Biology.The Journal of membrane biology · 2017Review
- Brain network efficiency is influenced by the pathologic source of corticobasal syndrome.Neurology · 2017Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous neurodegenerative disease that can result from either frontotemporal lobar degeneration (FTLD) or Alzheimer's disease (AD) pathology. It is critical to establish statistically powerful biomarkers that can achieve substantial cost-savings and increase the feasibility of clinical trials. We assessed three broad categories of neuroimaging methods to screen underlying FTLD and AD pathology in a clinical FTD series: global measures (e.g., ventricular volume), anatomical volumes of interest (VOIs) (e.g., hippocampus) using a standard atlas, and data-driven VOIs using Eigenanatomy. We evaluated clinical FTD patients (N = 93) with cerebrospinal fluid, gray matter (GM) magnetic resonance imaging (MRI), and diffusion tensor imaging (DTI) to assess whether they had underlying FTLD or AD pathology. Linear regression was performed to identify the optimal VOIs for each method in a training dataset and then we evaluated classification sensitivity and specificity in an independent test cohort. Power was evaluated by calculating minimum sample sizes required in the test classification analyses for each model. The data-driven VOI analysis using a multimodal combination of GM MRI and DTI achieved the greatest classification accuracy (89% sensitive and 89% specific) and required a lower minimum sample size (N = 26) relative to anatomical VOI and global measures. We conclude that a data-driven VOI approach using Eigenanatomy provides more accurate classification, benefits from increased statistical power in unseen datasets, and therefore provides a robust method for screening underlying pathology in FTD patients for entry into clinical trials.
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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.