ArticleScientific reports2019
Reduction of bias in the evaluation of fractional anisotropy and mean diffusivity in magnetic resonance diffusion tensor imaging using region-of-interest methodology.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Precise disease heterogeneity and progression quantification in MSA and Parkinson's disease using machine learning.Scientific reports · 2026Article
- Application of magnetic resonance diffusion tensor imaging for the treatment of hemifacial spasm.American journal of translational research · 2026Article
- Presumed Pediatric Isolated Oculomotor Nerve Schwannoma - A Case Report.International medical case reports journal · 2025Article
- The effect of elimination of gibbs ringing, noise and systematic errors on the DTI metrics and tractography in a rat brain.Scientific reports · 2024Article
- Impact of Deep Learning Denoising Algorithm on Diffusion Tensor Imaging of the Growth Plate on Different Spatial Resolutions.Tomography (Ann Arbor, Mich.) · 2024Article
- Toward diffusion tensor imaging as a biomarker in neurodegenerative diseases: technical considerations to optimize recordings and data processing.Frontiers in human neuroscience · 2024Review
- Article
- Longitudinal monitoring of amyotrophic lateral sclerosis by diffusion tensor imaging: Power calculations for group studies.Frontiers in neuroscience · 2022Article
- Structural Connectivity in Down Syndrome and Alzheimer's Disease.Frontiers in neuroscience · 2022Review
- In-depth characterization of a mouse model of post-traumatic epilepsy for biomarker and drug discovery.Acta neuropathologica communications · 2021Article
- Non-local means based Rician noise filtering for diffusion tensor and kurtosis imaging in human brain and spinal cord.BMC medical imaging · 2021Article
- Advanced Diagnosis of Glioma by Using Emerging Magnetic Resonance Sequences.Frontiers in oncology · 2021Review
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Authors and funding
3 authors.
Funding
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Abstract
Accurate quantification of fractional anisotropy (FA) and mean diffusivity (MD) in MR diffusion tensor imaging (DTI) requires adequate signal-to-noise ratio (SNR) especially in low FA areas of the brain, which necessitates clinically impractical long image acquisition times. We explored a SNR enhancement strategy using region-of-interest (ROI)-based diffusion tensor for quantification. DTI scans from a healthy male were acquired 15 times and combined into sets with different number of signal averages (NSA = 1-4, 15) at one 1.5-T Philips and three 3-T (Philips, Siemens and GE) scanners. Equivalence test was performed to determine NSA thresholds for bias-free FA and MD quantifications by comparison with reference values derived from images with NSA = 15. We examined brain areas with low FA values including caudate nucleus, globus pallidus, putamen, superior temporal gyrus, and substructures within thalamus (lateral dorsal, ventral anterior and posterior nuclei), where bias-free FA is difficult to obtain using a conventional approach. Our results showed that bias-free FA can be obtained with NSA = 2 or 3 in some cases using ROI-based analysis. ROI-based analysis allows reliable FA and MD quantifications in various brain structures previously difficult to study with clinically feasible data acquisition schemes.
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