ArticleJournal of visualized experiments : JoVE2013
Diffusion tensor magnetic resonance imaging in the analysis of neurodegenerative diseases.
Article in Journal of visualized experiments : JoVE, 2013. 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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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
36 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- Corticoefferent pathology distribution in amyotrophic lateral sclerosis: in vivo evidence from a meta-analysis of diffusion tensor imaging data.Scientific reports · 2018Pooled it
- Longitudinal Cerebral Structural, Microstructural, and Functional Alterations After Brain Tumor Surgery for Early Detection of Recurrent Tumors.Biomedicines · 2025Article
- Radiologic evaluation of the uncinate fasciculus using diffusion tensor imaging and tractography: review of technical considerations and clinical implications.Polish journal of radiology · 2025Review
- Exploring Radial Asymmetry in MR Diffusion Tensor Imaging and Its Impact on the Interpretation of Glymphatic Mechanisms.Journal of magnetic resonance imaging : JMRI · 2024Article
- Bridging the Gap between Basic Research and Clinical Practice: The Growing Role of Translational Neurorehabilitation.Medicines (Basel, Switzerland) · 2023Article
- Multiparametric magnetic resonance imaging and positron emission tomography findings in neurodegenerative diseases: Current status and future directions.The neuroradiology journal · 2021Review
- Age-Related Alterations in DTI Metrics in the Human Brain-Consequences for Age Correction.Frontiers in aging neuroscience · 2021Article
- A prospective harmonized multicenter DTI study of cerebral white matter degeneration in ALS.Neurology · 2020Article
- Enhanced Bidirectional Connectivity of the Subthalamo-pallidal Pathway in 6-OHDA-mouse Model of Parkinson's Disease Revealed by Probabilistic Tractography of Diffusion-weighted MRI at 9.4T.Experimental neurobiology · 2020Article
- Severe white matter damage in SHANK3 deficiency: a human and translational study.Annals of clinical and translational neurology · 2020Article
- Measuring network disruption in neurodegenerative diseases: New approaches using signal analysis.Journal of neurology, neurosurgery, and psychiatry · 2019Review
- The same cortico-efferent tract involvement in progressive bulbar palsy and in 'classical' ALS: A tract of interest-based MRI study.NeuroImage. Clinical · 2019Article
- Structural brain signature of cognitive decline in Parkinson's disease: DTI-based evidence from the LANDSCAPE study.Therapeutic advances in neurological disorders · 2019Article
- Diffusion MRI Indices and Their Relation to Cognitive Impairment in Brain Aging: The Updated Multi-protocol Approach in ADNI3.Frontiers in neuroinformatics · 2019Article
- Article
- Imaging the pathoanatomy of amyotrophic lateral sclerosis in vivo: targeting a propagation-based biological marker.Journal of neurology, neurosurgery, and psychiatry · 2018Article
- Identical patterns of cortico-efferent tract involvement in primary lateral sclerosis and amyotrophic lateral sclerosis: A tract of interest-based MRI study.NeuroImage. Clinical · 2018Article
- Fast progressive lower motor neuron disease is an ALS variant: A two-centre tract of interest-based MRI data analysis.NeuroImage. Clinical · 2018Article
- Longitudinal Diffusion Tensor Imaging Resembles Patterns of Pathology Progression in Behavioral Variant Frontotemporal Dementia (bvFTD).Frontiers in aging neuroscience · 2018Article
- Structural and Functional Brain Mapping Correlates of Impaired Eye Movement Control in Parkinsonian Syndromes: A Systems-Based Concept.Frontiers in neurology · 2018Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
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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.