ArticleNeuroImage2009
Optimizing power to track brain degeneration in Alzheimer's disease and mild cognitive impairment with tensor-based morphometry: an ADNI study of 515 subjects.
Article in NeuroImage, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 3 of them syntheses 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
89 citing papers in PubMed, 3 syntheses or guidelines pooled it, 147 citations in OpenAlex.
- Pooled it
- A Systematic Review of Longitudinal Studies Which Measure Alzheimer's Disease Biomarkers.Journal of Alzheimer's disease : JAD · 2017Pooled it
- Systematic review of strengths and limitations of randomized controlled trials for non-pharmacological interventions in mild cognitive impairment: focus on Alzheimer's disease.The journal of nutrition, health & aging · 2015Pooled it
- Boosting power for clinical trials using classifiers based on multiple biomarkers.Neurobiology of aging · 2010Trial
- Decoupling MCI-specific signatures from shared neurobiological substrates of cognitive aging via deep learning.NPJ digital medicine · 2026Article
- Postmortem neuropathologies are associated with retrospective tensor-based morphometry findings in Alzheimer's dementia continuum.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Article
- Neuromorphic deviations associated with transcriptomic expression and specific cell type in Alzheimer's disease.Scientific reports · 2025Article
- Morphometry of medial temporal lobe subregions using high-resolution T2-weighted MRI in ADNI3: Why, how, and what's next?Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Review
- Contributions of the ADNI Biostatistics Core.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Review
- Registration by Regression (RbR): a framework for interpretable and flexible atlas registration.Biomedical image registration, ... proceedings. WBIR (Workshop : 2006- ) · 2024Article
- Growth-Associated Protein 43 and Tensor-Based Morphometry Indices in Mild Cognitive Impairment.Neuroinformatics · 2024Article
- A novel neuroimaging signature for ADRD risk stratification in the community.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Regional deep atrophy: Using temporal information to automatically identify regions associated with Alzheimer's disease progression from longitudinal MRI.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Toward a statistical validation of brain signatures as robust measures of behavioral substrates.Human brain mapping · 2023Article
- Limitations of clinical trial sample size estimate by subtraction of two measurements.Statistics in medicine · 2022Article
- Neuroanatomic Markers of Posttraumatic Epilepsy Based on MR Imaging and Machine Learning.AJNR. American journal of neuroradiology · 2022Article
- Cerebrospinal fluid biomarkers of neurodegeneration, synaptic dysfunction, and axonal injury relate to atrophy in structural brain regions specific to Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2020Article
- Machine Learning Classification Identifies Cerebellar Contributions to Early and Moderate Cognitive Decline in Alzheimer's Disease.Frontiers in aging neuroscience · 2020Article
- Inter-hemispheric Asymmetry Patterns in the ADHD Brain: A Neuroimaging Replication Study.Proceedings of SPIE--the International Society for Optical Engineering · 2019Article
- Article
29 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors at 4 institutions in 1 country.
Funding
Abstract
Tensor-based morphometry (TBM) is a powerful method to map the 3D profile of brain degeneration in Alzheimer's disease (AD) and mild cognitive impairment (MCI). We optimized a TBM-based image analysis method to determine what methodological factors, and which image-derived measures, maximize statistical power to track brain change. 3D maps, tracking rates of structural atrophy over time, were created from 1030 longitudinal brain MRI scans (1-year follow-up) of 104 AD patients (age: 75.7+/-7.2 years; MMSE: 23.3+/-1.8, at baseline), 254 amnestic MCI subjects (75.0+/-7.2 years; 27.0+/-1.8), and 157 healthy elderly subjects (75.9+/-5.1 years; 29.1+/-1.0), as part of the Alzheimer's Disease Neuroimaging Initiative (ADNI). To determine which TBM designs gave greatest statistical power, we compared different linear and nonlinear registration parameters (including different regularization functions), and different numerical summary measures derived from the maps. Detection power was greatly enhanced by summarizing changes in a statistically-defined region-of-interest (ROI) derived from an independent training sample of 22 AD patients. Effect sizes were compared using cumulative distribution function (CDF) plots and false discovery rate methods. In power analyses, the best method required only 48 AD and 88 MCI subjects to give 80% power to detect a 25% reduction in the mean annual change using a two-sided test (at alpha=0.05). This is a drastic sample size reduction relative to using clinical scores as outcome measures (619 AD/6797 MCI for the ADAS-Cog, and 408 AD/796 MCI for the Clinical Dementia Rating sum-of-boxes scores). TBM offers high statistical power to track brain changes in large, multi-site neuroimaging studies and clinical trials of AD.
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Registered trials
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.