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DC Field | Value | Language |
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dc.contributor.author | Gordon, E | - |
dc.contributor.author | Bocchetta, M | - |
dc.contributor.author | Nicholas, J | - |
dc.contributor.author | Cash, DM | - |
dc.contributor.author | Rohrer, JD | - |
dc.date.accessioned | 2023-01-03T21:38:15Z | - |
dc.date.available | 2023-01-03T21:38:15Z | - |
dc.date.issued | 2021-10-05 | - |
dc.identifier | ORCID iD: Martina Bocchetta https://orcid.org/0000-0003-1814-5024 | - |
dc.identifier | 102842 | - |
dc.identifier.citation | Gordon E. et al. (2021) 'A comparison of automated atrophy measures across the frontotemporal dementia spectrum: Implications for trials', NeuroImage: Clinical, 32, 102842, pp. 1 - 13. doi: 10.1016/j.nicl.2021.102842. | en_US |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/25706 | - |
dc.description | Appendix A. Supplementary data: The following supplementary data to this article are available online at https://ars.els-cdn.com/content/image/1-s2.0-S2213158221002862-mmc1.docx (Word document (94KB)). | en_US |
dc.description.abstract | Copyright © 2021 The Author(s). Background: Frontotemporal dementia (FTD) is a common cause of young onset dementia, and whilst there are currently no treatments, there are several promising candidates in development and early phase trials. Comprehensive investigations of neuroimaging markers of disease progression across the full spectrum of FTD disorders are lacking and urgently needed to facilitate these trials. Objective: To investigate the comparative performance of multiple automated segmentation and registration pipelines used to quantify longitudinal whole-brain atrophy across the clinical, genetic and pathological subgroups of FTD, in order to inform upcoming trials about suitable neuroimaging-based endpoints. Methods: Seventeen fully automated techniques for extracting whole-brain atrophy measures were applied and directly compared in a cohort of 226 participants who had undergone longitudinal structural 3D T1-weighted imaging. Clinical diagnoses were behavioural variant FTD (n = 56) and primary progressive aphasia (PPA, n = 104), comprising semantic variant PPA (n = 38), non-fluent variant PPA (n = 42), logopenic variant PPA (n = 18), and PPA-not otherwise specified (n = 6). 49 of these patients had either a known pathogenic mutation or postmortem confirmation of their underlying pathology. 66 healthy controls were included for comparison. Sample size estimates to detect a 30% reduction in atrophy (80% power; 0.05 significance) were computed to explore the relative feasibility of these brain measures as surrogate markers of disease progression and their ability to detect putative disease-modifying treatment effects. Results: Multiple automated techniques showed great promise, detecting significantly increased rates of whole-brain atrophy (p<0.001) and requiring sample sizes of substantially less than 100 patients per treatment arm. Across the different FTD subgroups, direct measures of volume change consistently outperformed their indirect counterparts, irrespective of the initial segmentation quality. Significant differences in performance were found between both techniques and patient subgroups, highlighting the importance of informed biomarker choice based on the patient population of interest. Conclusion: This work expands current knowledge and builds on the limited longitudinal investigations currently available in FTD, as well as providing valuable information about the potential of fully automated neuroimaging biomarkers for sporadic and genetic FTD trials. | en_US |
dc.description.sponsorship | The Dementia Research Centre is supported by Alzheimer's Research UK, Brain Research Trust, and The Wolfson Foundation. This work was supported by the NIHR Queen Square Dementia Biomedical Research Unit, the NIHR UCL/H Biomedical Research Centre and the Leonard Wolfson Experimental Neurology Centre (LWENC) Clinical Research Facility as well as an Alzheimer's Society grant (AS-PG-16-007). EG is supported by an Alzheimer’s Society PhD grant (AS-PHD-2013-028). MB is supported by a Fellowship award from the Alzheimer’s Society, UK (AS-JF-19a-004-517). MB’s work is also supported by the UK Dementia Research Institute which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. JN is supported by a UK Medical Research Council grant (MR/M023664/1). DMC is supported by a grant from the Alzheimer's Society (AS‐PG‐15–025). JDR is supported by an MRC Clinician Scientist Fellowship (MR/M008525/1) and has received funding from the NIHR Rare Disease Translational Research Collaboration (BRC149/NS/MH). | en_US |
dc.format.extent | 1 - 13 | - |
dc.format.medium | Electronic | - |
dc.language | English | - |
dc.language.iso | en_US | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | Copyright © 2021 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/). | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | frontotemporal dementia | en_US |
dc.subject | magnetic resonance imaging | en_US |
dc.subject | automated segmentation | en_US |
dc.subject | longitudinal atrophy | en_US |
dc.subject | neuroimaging biomarkers | en_US |
dc.subject | volumetric imaging | en_US |
dc.subject | clinical trials | en_US |
dc.title | A comparison of automated atrophy measures across the frontotemporal dementia spectrum: Implications for trials | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.1016/j.nicl.2021.102842 | - |
dc.relation.isPartOf | NeuroImage: Clinical | - |
pubs.publication-status | Published | - |
pubs.volume | 32 | - |
dc.identifier.eissn | 2213-1582 | - |
dc.rights.holder | The Author(s) | - |
Appears in Collections: | Dept of Life Sciences Research Papers |
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FullText.pdf | Copyright © 2021 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/). | 6.78 MB | Adobe PDF | View/Open |
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