Váša, F;
Hobday, H;
Stanyard, RA;
Daws, RE;
Giampietro, V;
O'Daly, O;
Lythgoe, DJ;
... Cole, JH; + view all
(2021)
Rapid processing and quantitative evaluation of structural brain scans for adaptive multimodal imaging.
Human Brain Mapping
10.1002/hbm.25755.
(In press).
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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.
| Type: | Article |
|---|---|
| Title: | Rapid processing and quantitative evaluation of structural brain scans for adaptive multimodal imaging |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1002/hbm.25755 |
| Publisher version: | https://doi.org/10.1002/hbm.25755 |
| Language: | English |
| Additional information: | Copyright © 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | EPImix, MRI, fingerprinting, identifiability, morphometric similarity, reliability, structural covariance |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10141239 |
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