Correction of Physiological Artifacts in Multi-Echo fMRI Data-Evaluation of Possible RETROICOR Implementations

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14110%2F25%3A00141512" target="_blank" >RIV/00216224:14110/25:00141512 - isvavai.cz</a>
Result on the web
<a href="https://onlinelibrary.wiley.com/doi/10.1002/hbm.70264" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1002/hbm.70264</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/hbm.70264" target="_blank" >10.1002/hbm.70264</a>

Result language
angličtina
Original language name
Correction of Physiological Artifacts in Multi-Echo fMRI Data-Evaluation of Possible RETROICOR Implementations
Original language description
The study evaluates the efficacy of RETROICOR (Retrospective Image Correction) in mitigating physiological artifacts within multi-echo (ME) fMRI data. Two RETROICOR implementations were compared: applying corrections to individual echoes (RTC_ind) versus composite multi-echo data (RTC_comp). Data from 50 healthy participants were collected using diverse acquisition parameters, including multiband acceleration factors and varying flip angles, on a Siemens Prisma 3T scanner. Key metrics such as temporal signal-to-noise ratio (tSNR), signal fluctuation sensitivity (SFS), and variance of residuals demonstrated improved data quality in both RETROICOR models, particularly in moderately accelerated runs (multiband factors 4 and 6) with lower flip angles (45 degrees). Differences between RTC_ind and RTC_comp were minimal, suggesting both methods are viable for practical applications. While the highest acceleration (multiband factor 8) degraded data quality, RETROICOR's compatibility with faster acquisition sequences was confirmed. These findings underscore the importance of optimizing acquisition parameters and noise correction techniques for reliable fMRI investigations.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30210 - Clinical neurology

Project
<a href="/en/project/GA23-06957S" target="_blank" >GA23-06957S: New strategies in processing of multi-echo fMRI data</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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