ArticleMagnetic resonance imaging2019
Characterization and correlation of signal drift in diffusion weighted MRI.
Article in Magnetic resonance imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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Who cites it
11 citing papers in PubMed.
- Human In Vivo Validation of Frequency-Dependent QTI.Magnetic resonance in medicine · 2026Article
- Diffusion MRI reveals amyloid plaque-associated cellular signatures through spatial transcriptomic integration.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Assessing Measurement Repeatability of a Novel Anisotropic Phantom for Advanced Diffusion MRI Models.Magnetic resonance in medicine · 2026Article
- Did you know? State-of-the-art preprocessing diffusion MRI data can improve tractography.Brain structure & function · 2026Review
- Sex differences in maturational timing of amygdala and prefrontal cortex volumes and white matter tract microstructure.Developmental cognitive neuroscience · 2025Article
- Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 1: In vivo small-animal imaging.Magnetic resonance in medicine · 2025Review
- Signal drift in diffusion MRI of the brain: effects on intravoxel incoherent motion parameter estimates.Magma (New York, N.Y.) · 2024Article
- Efficient PCA denoising of spatially correlated redundant MRI data.Imaging neuroscience (Cambridge, Mass.) · 2023Article
- What's new and what's next in diffusion MRI preprocessing.NeuroImage · 2022Review
- Review
- Consideration of Cerebrospinal Fluid Intensity Variation in Diffusion Weighted MRI.Proceedings of SPIE--the International Society for Optical Engineering · 2019Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Diffusion weighted MRI (DWMRI) and the myriad of analysis approaches (from tensors to spherical harmonics and brain tractography to body multi-compartment models) depend on accurate quantification of the apparent diffusion coefficient (ADC). Signal drift during imaging (e.g., due to b0 drift associated with heating) can cause systematic non-linearities that manifest as ADC changes if not corrected. Herein, we present a case study on two phantoms on one scanner. Different scan protocols exhibit different degrees of drift during similar scans and may be sensitive to the order of scans within an exam. Vos et al. recently reviewed the effects of signal drift in DWMRI acquisitions and proposed a temporal model for correction. We propose a novel spatial-temporal model to correct for higher order aspects of the signal drift and derive a statistically robust variant. We evaluate the Vos model and propose a method using two phantoms that mimic the ADC of the relevant brain tissue (0.36-2.2 × 10-3 mm
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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.