What type of study is this?

September 17, 2025

Adapting the Tedana Multi-Echo Denoising Pipeline for Echo Planar Time-Resolved Imaging (EPTI)

Key Points

The proposed model enhances the accuracy of BOLD and non-BOLD signal measurements in EPTI data.
Tedana's performance was evaluated using both resting-state and task-based fMRI data from a healthy volunteer.
The adaptation reduces assumptions about the relationship between BOLD and non-BOLD signals, leading to improved denoising.
These improvements may allow for more precise analyses in time-resolved imaging scenarios, impacting research in neuroimaging.

Abstract

Motivation: The Tedana multi-echo denoising pipeline has not yet been optimized for Echo Planar Time-Resolved Imaging (EPTI), despite its success with EPI. Goal(s): We aim to improve the accuracy of the Tedana pipeline for EPTI data by implementing a ΔS/S model that doesn't assume that BOLD and non-BOLD related signal fluctuations are fully uncoupled. Approach: We acquired both resting-state and task-based fMRI data for a healthy volunteer. We then compared Tedana's performance using both the proposed and current model implementations. Results: The proposed model provides a more accurate measure of BOLD and non-BOLD related signal change contributions to each ICA component. Impact: We adapted the Tedana pipeline to ensure accurate denoising of EPTI data and leveraged EPTI's high echo count by no longer assuming that BOLD and non-BOLD related signal changes are uncoupled thus improving Tedana's accuracy for EPTI.

Demander à l'IA

Bookmark