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Updated: Jun 21, 2025
Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
Published on: November 8, 2012
Signal drift in diffusion MRI of the brain: effects on intravoxel incoherent motion parameter estimates
Oscar Jalnefjord1,2, Louise Rosenqvist3, Amina Warsame3
1Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, MRI Center, Bruna Stråket 13, 413 45, Gothenburg, Sweden. oscar.jalnefjord@gu.se.
Objectives:
Signal drift has been put forward as one of the fundamental confounding factors in diffusion MRI (dMRI) of the brain. This study characterizes signal drift in dMRI of the brain, evaluates correction methods, and exemplifies its impact on parameter estimation for three intravoxel incoherent motion (IVIM) protocols.
Materials And Methods:
dMRI of the brain was acquired in ten healthy subjects using protocols designed to enable retrospective characterization and correction of signal drift. All scans were acquired twice for repeatability analysis. Three temporal polynomial correction methods were evaluated: (1) global, (2) voxelwise, and (3) spatiotemporal. Effects of acquisition order were simulated using estimated drift fields.
Results:
Signal drift was around 2% per 5 min in the brain as a whole, but reached above 5% per 5 min in the frontal regions. Only correction methods taking spatially varying signal drift into account could achieve effective corrections. Altered acquisition order introduced both systematic changes and differences in repeatability in the presence of signal drift.
Discussion:
Signal drift in dMRI of the brain was found to be spatially varying, calling for correction methods taking this into account. Without proper corrections, choice of protocol can affect dMRI parameter estimates and their repeatability.
Insights
Signal drift in brain diffusion MRI (dMRI) is spatially variable, impacting parameter estimates. Spatially aware correction methods are crucial for accurate dMRI analysis and repeatable results.
Area of Science:
- Neuroimaging
- Diffusion MRI (dMRI)
- Quantitative MRI
Background:
- Signal drift is a known confounding factor in diffusion MRI (dMRI) of the brain.
- Understanding and correcting signal drift is essential for accurate dMRI parameter estimation.
Purpose of the Study:
- To characterize signal drift in brain dMRI.
- To evaluate different signal drift correction methods.
- To assess the impact of signal drift on intravoxel incoherent motion (IVIM) parameter estimation.
Main Methods:
- Acquired dMRI data from ten healthy subjects twice for repeatability.
- Evaluated three temporal polynomial correction methods: global, voxelwise, and spatiotemporal.
- Simulated effects of acquisition order using estimated drift fields.
Main Results:
- Brain-wide signal drift averaged 2% per 5 minutes, exceeding 5% per 5 minutes in frontal regions.
- Only spatially varying correction methods effectively corrected signal drift.
- Altered acquisition order introduced systematic changes and affected repeatability in the presence of drift.
Conclusions:
- Spatially varying signal drift necessitates correction methods that account for spatial heterogeneity.
- Inadequate drift correction can significantly alter dMRI parameter estimates and their repeatability, depending on the chosen protocol.
