Abstract #2356

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

Kathryn Lamar-Bruno¹, Fuyixue Wang², Zijing Dong², Ryan Barnes³, Conan Chen⁴, Dan Handwerker⁵, and Thomas Liu⁶

¹Bioengineering, University of California, San Diego, La Jolla, CA, United States, ²Harvard University, Cambridge, MA, United States, ³University of California, San Diego, La Jolla, CA, United States, ⁴Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, United States, ⁵National Institute of Health, Bethesda, MD, United States, ⁶Radiology, University of California, San Diego, La Jolla, CA, United States

Synopsis

Keywords: fMRI Analysis, Analysis/Processing, Tedana, EPTI, fMRI, Multi-Echo

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.

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