What question did this study set out to answer?

The aim is to demonstrate how state-of-the-art preprocessing techniques enhance the accuracy and reproducibility of diffusion MRI tractography.

April 1, 2026Open Access

Did you know? State-of-the-art preprocessing diffusion MRI data can improve tractography

Key Points

The aim is to demonstrate how state-of-the-art preprocessing techniques enhance the accuracy and reproducibility of diffusion MRI tractography.
Synthesize evidence on preprocessing methods improving diffusion MRI data
Highlight best-practice techniques like denoising and motion correction
Outline publicly available processing pipelines for standardized analysis
Discuss acquisition and data-handling strategies to optimize outcomes
State-of-the-art preprocessing improves anatomical fidelity in tractography
Enhanced test-retest reproducibility compared to minimally processed data
Best practices lead to more reliable outcomes in brain studies

Abstract

Diffusion MRI fiber tractography is sensitive to noise and artifacts in diffusion-weighted images, and these challenges can propagate into fiber-orientation estimation and the tractography process. In this “Did You Know” communication, we synthesize evidence that state-of-the-art preprocessing improves tractography anatomical fidelity and test-retest reproducibility compared to minimally processed data. We summarize best-practice preprocessing – including denoising, motion and eddy current correction, EPI distortion correction, and Gibbs ringing removal – along with additional and emerging steps, and highlight integrated, publicly available pipelines that implement these methods in standardized, containerized workflows. We also outline practical acquisition and data-handling considerations that maximize the benefits of modern processing, providing a foundation for reliable tractography-based studies of the brain.

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