Reproducibility and Reliability of Free‐Water‐Corrected Diffusion Tensor Imaging of the Brain: Revisited

Diffusion tensor imaging (DTI) corrected for the free-water (FW) enables the separation of a hindered Gaussian-like profile from an isotropic component, which represents diffusion found in cerebrospinal and interstitial fluids within the extracellular space of grey and white matter. The assessment of the reproducibility and reliability properties of FW-corrected DTI is a crucial factor in demonstrating the potential clinical utility of this refinement, particularly considering the examinations across multiple medical centres. This paper explores the variability, reliability, and separability properties of free-water volume fraction (FWVF) and FW-corrected DTI-based measures in healthy human brain white matter using publicly available test-retest databases acquired in (1) intra-scanner, (2) intra-scanner longitudinal and (3) inter-scanner settings under varying acquisition schemes. Three different estimation techniques to retrieve the FW-corrected DTI parameters tailored to single- or multiple-shell diffusion-sensitising magnetic resonance (MR) acquisitions are investigated: (i) a direct optimization of bi-tensor signal representation in the variational framework, (ii) the region contraction-based approach and (iii) the spherical means technique combined with a correction of diffusion-weighted MR signal prior to DTI estimation. We found the previous suggestion that the FW correction to DTI in a single-shell diffusion-weighted MR acquisition improves the repeatability of DTI-based measures may be data- and methodology-dependent, and does not generalise to multiple-shell scenarios. The study also confirms that the single-shell variational FW-correction method fails to retrieve meaningful information from the mean diffusivity (MD) parameter. In contrast, the combined FW-correction scheme reduces the biological variability of MD, regardless of whether DTI is estimated from single- or multiple-shell data, given that the FWVF used for the correction in both cases is derived from multiple-shell acquisitions. Our experiments have shown that the most reliable and repeatable/reproducible measures, while preserving a moderate separability property, are fractional anisotropy and axial diffusivity estimated in a multiple-shell variant under a combined FW-correction scheme. On the contrary, our results show evidence that the least reliable measures are the mean diffusivity estimated using any FW-correction procedure, as well as the FWVF parameter itself. These results can be used to establish the direction for selecting the most attractive FW-correction DTI scheme for clinical applications in terms of the variability-reliability-separability criterion.

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Publication Details

Journal
Human Brain Mapping
Published
2026-02-15
DOI
https://doi.org/10.1002/hbm.70431
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Reproducibility and Reliability of Free‐Water‐Corrected Diffusion Tensor Imaging of the Brain: Revisited

Guillem París, Tomasz Pieciak, Santiago Aja‐Fernández, Antonio Tristán‐Vega
Human Brain Mapping
Advanced Neuroimaging Techniques and Applications
article

Reproducibility and Reliability of Free‐Water‐Corrected Diffusion Tensor Imaging of the Brain: Revisited

Guillem París, Tomasz Pieciak, Santiago Aja‐Fernández, Antonio Tristán‐Vega
article en

Abstract

Diffusion tensor imaging (DTI) corrected for the free-water (FW) enables the separation of a hindered Gaussian-like profile from an isotropic component, which represents diffusion found in cerebrospinal and interstitial fluids within the extracellular space of grey and white matter. The assessment of the reproducibility and reliability properties of FW-corrected DTI is a crucial factor in demonstrating the potential clinical utility of this refinement, particularly considering the examinations across multiple medical centres. This paper explores the variability, reliability, and separability properties of free-water volume fraction (FWVF) and FW-corrected DTI-based measures in healthy human brain white matter using publicly available test-retest databases acquired in (1) intra-scanner, (2) intra-scanner longitudinal and (3) inter-scanner settings under varying acquisition schemes. Three different estimation techniques to retrieve the FW-corrected DTI parameters tailored to single- or multiple-shell diffusion-sensitising magnetic resonance (MR) acquisitions are investigated: (i) a direct optimization of bi-tensor signal representation in the variational framework, (ii) the region contraction-based approach and (iii) the spherical means technique combined with a correction of diffusion-weighted MR signal prior to DTI estimation. We found the previous suggestion that the FW correction to DTI in a single-shell diffusion-weighted MR acquisition improves the repeatability of DTI-based measures may be data- and methodology-dependent, and does not generalise to multiple-shell scenarios. The study also confirms that the single-shell variational FW-correction method fails to retrieve meaningful information from the mean diffusivity (MD) parameter. In contrast, the combined FW-correction scheme reduces the biological variability of MD, regardless of whether DTI is estimated from single- or multiple-shell data, given that the FWVF used for the correction in both cases is derived from multiple-shell acquisitions. Our experiments have shown that the most reliable and repeatable/reproducible measures, while preserving a moderate separability property, are fractional anisotropy and axial diffusivity estimated in a multiple-shell variant under a combined FW-correction scheme. On the contrary, our results show evidence that the least reliable measures are the mean diffusivity estimated using any FW-correction procedure, as well as the FWVF parameter itself. These results can be used to establish the direction for selecting the most attractive FW-correction DTI scheme for clinical applications in terms of the variability-reliability-separability criterion.

Human Brain MappingVol. 47(3)
Universidad de Valladolid (ES)
Ministerio de Ciencia e Innovación, Junta de Castilla y León, Narodowa Agencja Wymiany Akademickiej, European Social Fund
Clean water and sanitation
Openalex Percentile: Top 52%
Advanced Neuroimaging Techniques and Applications
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