ArticleNeuroImage2014
Improved DTI registration allows voxel-based analysis that outperforms tract-based spatial statistics.
Article in NeuroImage, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 118 papers, 2 of them syntheses that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
118 citing papers in PubMed, 2 syntheses or guidelines pooled it, 180 citations in OpenAlex.
- Uncovering the hidden effects of repetitive subconcussive head impact exposure: A mega-analytic approach characterizing seasonal brain microstructural changes in contact and collision sports athletes.Human brain mapping · 2024Pooled it
- Assessing White Matter Pathology in Early-Stage Parkinson Disease Using Diffusion MRI: A Systematic Review.Frontiers in neurology · 2020Pooled it
- Effect of physical exercise on white matter microstructure in chemotherapy-treated breast cancer patients: a randomized controlled trial (PAM study).Brain imaging and behavior · 2025Trial
- Effects of simvastatin on white matter integrity in healthy middle-aged adults.Annals of clinical and translational neurology · 2021Trial
- Analysis of recovery-related white matter microstructures in visual spatial neglect based on diffusion tensor imaging.Brain imaging and behavior · 2026Article
- Evaluating Transferability of ComBat Harmonization of Diffusion Tensor Magnetic Resonance Imaging Data.Annals of biomedical engineering · 2026Article
- Cortical microstructural changes in minimal hepatic encephalopathy: a gray matter-based spatial statistics study.Quantitative imaging in medicine and surgery · 2025Article
- White matter trajectories in Down syndrome and Alzheimer's disease: Insights from diffusion tensor-based morphometry.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- White matter microstructure alterations in early psychosis and schizophrenia.Translational psychiatry · 2025Article
- FetDTIAlign: A deep learning framework for affine and deformable registration of fetal brain dMRI.NeuroImage · 2025Article
- Neural adaptations in short-term learning of sign language revealed by fMRI and DTI.Scientific reports · 2025Article
- Alterations of the cerebral microstructure in patients with noise-induced hearing loss: A diffusion tensor imaging study.Brain and behavior · 2024Article
- Glymphatic System Activity and Brain Morphology in Patients With Psychogenic Non-epileptic Seizures.Cureus · 2024Article
- A Comparison of White Matter Brain Differences in Monolingual and Highly Proficient Multilingual Speakers.Neurobiology of language (Cambridge, Mass.) · 2024Article
- Multiparametric mapping of white matter reorganizations in patients with frontal glioma-related epilepsy.CNS neuroscience & therapeutics · 2023Article
- Impacts of spaceflight experience on human brain structure.Scientific reports · 2023Article
- Structural connectome quantifies tumour invasion and predicts survival in glioblastoma patients.Brain : a journal of neurology · 2023Article
- A preliminary study of white matter correlates of a laboratory measure of attention and motor stability in attention-deficit/hyperactivity disorder.Journal of psychiatric research · 2023Article
- Reduced neurite density index in the prefrontal cortex of adults with autism assessed using neurite orientation dispersion and density imaging.Frontiers in neurology · 2023Article
- Fixel based analysis of white matter alterations in early stage cerebral small vessel disease.Scientific reports · 2022Article
58 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
14 authors at 2 institutions in 1 country.
Funding
Abstract
Tract-Based Spatial Statistics (TBSS) is a popular software pipeline to coregister sets of diffusion tensor Fractional Anisotropy (FA) images for performing voxel-wise comparisons. It is primarily defined by its skeleton projection step intended to reduce effects of local misregistration. A white matter "skeleton" is computed by morphological thinning of the inter-subject mean FA, and then all voxels are projected to the nearest location on this skeleton. Here we investigate several enhancements to the TBSS pipeline based on recent advances in registration for other modalities, principally based on groupwise registration with the ANTS-SyN algorithm. We validate these enhancements using simulation experiments with synthetically-modified images. When used with these enhancements, we discover that TBSS's skeleton projection step actually reduces algorithm accuracy, as the improved registration leaves fewer errors to warrant correction, and the effects of this projection's compromises become stronger than those of its benefits. In our experiments, our proposed pipeline without skeleton projection is more sensitive for detecting true changes and has greater specificity in resisting false positives from misregistration. We also present comparative results of the proposed and traditional methods, both with and without the skeleton projection step, on three real-life datasets: two comparing differing populations of Alzheimer's disease patients to matched controls, and one comparing progressive supranuclear palsy patients to matched controls. The proposed pipeline produces more plausible results according to each disease's pathophysiology.
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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.