František Váša
Rapid processing and quantitative evaluation of structural brain scans for adaptive multimodal imaging
Váša, František; Hobday, Harriet; Stanyard, Ryan A.; Daws, Richard E.; Giampietro, Vincent; O'Daly, Owen; Lythgoe, David J.; Seidlitz, Jakob; Skare, Stefan; Williams, Steven C. R.; Marquand, Andre F.; Leech, Robert; Cole, James H.
Authors
Harriet Hobday
Ryan Stanyard r.a.stanyard@keele.ac.uk
Richard E. Daws
Vincent Giampietro
Owen O'Daly
David J. Lythgoe
Jakob Seidlitz
Stefan Skare
Steven C. R. Williams
Andre F. Marquand
Robert Leech
James H. Cole
Abstract
Current neuroimaging acquisition and processing approaches tend to be optimised for quality rather than speed. However, rapid acquisition and processing of neuroimaging data can lead to novel neuroimaging paradigms, such as adaptive acquisition, where rapidly processed data is used to inform subsequent image acquisition steps. Here we first evaluate the impact of several processing steps on the processing time and quality of registration of manually labelled T1-weighted MRI scans. Subsequently, we apply the selected rapid processing pipeline both to rapidly acquired multicontrast EPImix scans of 95 participants (which include T1-FLAIR, T2, T2*, T2-FLAIR, DWI and ADC contrasts, acquired in ~1 min), as well as to slower, more standard single-contrast T1-weighted scans of a subset of 66 participants. We quantify the correspondence between EPImix T1-FLAIR and single-contrast T1-weighted scans, using correlations between voxels and regions of interest across participants, measures of within- and between-participant identifiability as well as regional structural covariance networks. Furthermore, we explore the use of EPImix for the rapid construction of morphometric similarity networks. Finally, we quantify the reliability of EPImix-derived data using test–retest scans of 10 participants. Our results demonstrate that quantitative information can be derived from a neuroimaging scan acquired and processed within minutes, which could further be used to implement adaptive multimodal imaging and tailor neuroimaging examinations to individual patients.
Citation
Váša, F., Hobday, H., Stanyard, R. A., Daws, R. E., Giampietro, V., O'Daly, O., …Cole, J. H. (2022). Rapid processing and quantitative evaluation of structural brain scans for adaptive multimodal imaging. Human Brain Mapping, 43(5), 1749-1765. https://doi.org/10.1002/hbm.25755
Journal Article Type | Article |
---|---|
Acceptance Date | Jul 9, 2021 |
Online Publication Date | Dec 24, 2021 |
Publication Date | 2022-04 |
Deposit Date | Oct 1, 2024 |
Journal | Human Brain Mapping |
Print ISSN | 1065-9471 |
Electronic ISSN | 1097-0193 |
Publisher | Wiley |
Peer Reviewed | Peer Reviewed |
Volume | 43 |
Issue | 5 |
Pages | 1749-1765 |
DOI | https://doi.org/10.1002/hbm.25755 |
Public URL | https://keele-repository.worktribe.com/output/947486 |
Publisher URL | https://onlinelibrary.wiley.com/doi/10.1002/hbm.25755 |
Additional Information | Received: 2021-07-09; Accepted: 2021-11-21; Published: 2021-12-24 |
You might also like
Aperiodic and Hurst EEG exponents across early human brain development: A systematic review
(2024)
Journal Article
Tissue volume estimation and age prediction using rapid structural brain scans
(2022)
Journal Article
Downloadable Citations
About Keele Repository
Administrator e-mail: research.openaccess@keele.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search