ICA-based denoising strategies in breath-hold induced cerebrovascular reactivity mapping with multi echo BOLD fMRI

Stefano Moia*, Maite Termenon, Eneko Uruñuela, Gang Chen, Rachael C. Stickland, Molly G. Bright, César Caballero-Gaudes

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Performing a BOLD functional MRI (fMRI) acquisition during breath-hold (BH) tasks is a non-invasive, robust method to estimate cerebrovascular reactivity (CVR). However, movement and breathing-related artefacts caused by the BH can substantially hinder CVR estimates due to their high temporal collinearity with the effect of interest, and attention has to be paid when choosing which analysis model should be applied to the data. In this study, we evaluate the performance of multiple analysis strategies based on lagged general linear models applied on multi-echo BOLD fMRI data, acquired in ten subjects performing a BH task during ten sessions, to obtain subject-specific CVR and haemodynamic lag estimates. The evaluated approaches range from conventional regression models, i.e. including drifts and motion timecourses as nuisance regressors, applied on single-echo or optimally-combined data, to more complex models including regressors obtained from multi-echo independent component analysis with different grades of orthogonalization in order to preserve the effect of interest, i.e. the CVR. We compare these models in terms of their ability to make signal intensity changes independent from motion, as well as the reliability as measured by voxelwise intraclass correlation coefficients of both CVR and lag maps over time. Our results reveal that a conservative independent component analysis model applied on the optimally-combined multi-echo fMRI signal offers the largest reduction of motion-related effects in the signal, while yielding reliable CVR amplitude and lag estimates, although a conventional regression model applied on the optimally-combined data results in similar estimates. This work demonstrates the usefulness of multi-echo based fMRI acquisitions and independent component analysis denoising for precision mapping of CVR in single subjects based on BH paradigms, fostering its potential as a clinically-viable neuroimaging tool for individual patients. It also proves that the way in which data-driven regressors should be incorporated in the analysis model is not straight-forward due to their complex interaction with the BH-induced BOLD response.

Original languageEnglish (US)
Article number117914
JournalNeuroimage
Volume233
DOIs
StatePublished - Jun 2021

Funding

This research was supported by the European Union's Horizon 2020 research and innovation program ( Marie Sk\u0142odowska-Curie grant agreement No. 713673 ), a fellowship from La Caixa Foundation (ID 100010434 , fellowship code LCF/BQ/IN17/11620063 ), the Spanish Ministry of Economy and Competitiveness ( Ramon y Cajal Fellowship , RYC-2017- 21845 ), the Spanish State Research Agency (BCBL \u201CSevero Ochoa\u201D excellence accreditation, SEV- 2015-490 ), the Basque Government ( BERC 2018-2021 and PIBA_2019_104 ), the Spanish Ministry of Science, Innovation and Universities (MICINN; PID2019-105520GB-100 and FJCI-2017-31814 ), and the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under award number K12HD073945 . The authors would like to thank Vicente Ferrer for collaborating in data acquisition and two anonymous reviewers for helping improving the quality of the paper. This research was supported by the European Union's Horizon 2020 research and innovation program (Marie Sk?odowska-Curie grant agreement No. 713673), a fellowship from La Caixa Foundation (ID 100010434, fellowship code LCF/BQ/IN17/11620063), the Spanish Ministry of Economy and Competitiveness (Ramon y Cajal Fellowship, RYC-2017- 21845), the Spanish State Research Agency (BCBL ?Severo Ochoa? excellence accreditation, SEV- 2015-490), the Basque Government (BERC 2018-2021 and PIBA_2019_104), the Spanish Ministry of Science, Innovation and Universities (MICINN; PID2019-105520GB-100 and FJCI-2017-31814), and the Eunice Kennedy Shriver National Institute of Child Health and Human Development of the National Institutes of Health under award number K12HD073945.

Keywords

  • Breath-hold
  • Cerebrovascular reactivity
  • Denoising
  • Independent component analysis
  • Multi-echo fMRI
  • Precision functional mapping

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

Fingerprint

Dive into the research topics of 'ICA-based denoising strategies in breath-hold induced cerebrovascular reactivity mapping with multi echo BOLD fMRI'. Together they form a unique fingerprint.

Cite this