Estimation of brain age delta from brain imaging.
It is of increasing interest to study "brain age" - the apparent age of a subject, as inferred from brain imaging data. The difference between brain age and actual age (the "delta") is typically computed, reflecting deviation from the population norm. This therefore may reflect a...
| Váldodahkkit: | , , , , |
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| Materiálatiipa: | Journal article |
| Giella: | English |
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Elsevier
2019
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| _version_ | 1826265521829445632 |
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| author | Smith, S Vidaurre, D Alfaro-Almagro, F Nichols, T Miller, K |
| author_facet | Smith, S Vidaurre, D Alfaro-Almagro, F Nichols, T Miller, K |
| author_sort | Smith, S |
| collection | OXFORD |
| description | It is of increasing interest to study "brain age" - the apparent age of a subject, as inferred from brain imaging data. The difference between brain age and actual age (the "delta") is typically computed, reflecting deviation from the population norm. This therefore may reflect accelerated aging (positive delta) or resilience (negative delta) and has been found to be a useful correlate with factors such as disease and cognitive decline. However, although there has been a range of methods proposed for estimating brain age, there has been little study of the optimal ways of computing the delta. In this technical note we describe problems with the most common current approach, and present potential improvements. We evaluate different estimation methods on simulated and real data. We also find the strongest correlations of corrected brain age delta with 5792 non-imaging variables (non-brain physical measures, life-factor measures, cognitive test scores, etc.), and also with 2641 multimodal brain imaging-derived phenotypes, with data from 19,000 participants in UK Biobank. |
| first_indexed | 2024-03-06T20:25:01Z |
| format | Journal article |
| id | oxford-uuid:2f1b1f9b-51e3-4137-b2ab-d2d6cf515d35 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T20:25:01Z |
| publishDate | 2019 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:2f1b1f9b-51e3-4137-b2ab-d2d6cf515d352022-03-26T12:53:14ZEstimation of brain age delta from brain imaging.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:2f1b1f9b-51e3-4137-b2ab-d2d6cf515d35EnglishSymplectic Elements at OxfordElsevier2019Smith, SVidaurre, DAlfaro-Almagro, FNichols, TMiller, KIt is of increasing interest to study "brain age" - the apparent age of a subject, as inferred from brain imaging data. The difference between brain age and actual age (the "delta") is typically computed, reflecting deviation from the population norm. This therefore may reflect accelerated aging (positive delta) or resilience (negative delta) and has been found to be a useful correlate with factors such as disease and cognitive decline. However, although there has been a range of methods proposed for estimating brain age, there has been little study of the optimal ways of computing the delta. In this technical note we describe problems with the most common current approach, and present potential improvements. We evaluate different estimation methods on simulated and real data. We also find the strongest correlations of corrected brain age delta with 5792 non-imaging variables (non-brain physical measures, life-factor measures, cognitive test scores, etc.), and also with 2641 multimodal brain imaging-derived phenotypes, with data from 19,000 participants in UK Biobank. |
| spellingShingle | Smith, S Vidaurre, D Alfaro-Almagro, F Nichols, T Miller, K Estimation of brain age delta from brain imaging. |
| title | Estimation of brain age delta from brain imaging. |
| title_full | Estimation of brain age delta from brain imaging. |
| title_fullStr | Estimation of brain age delta from brain imaging. |
| title_full_unstemmed | Estimation of brain age delta from brain imaging. |
| title_short | Estimation of brain age delta from brain imaging. |
| title_sort | estimation of brain age delta from brain imaging |
| work_keys_str_mv | AT smiths estimationofbrainagedeltafrombrainimaging AT vidaurred estimationofbrainagedeltafrombrainimaging AT alfaroalmagrof estimationofbrainagedeltafrombrainimaging AT nicholst estimationofbrainagedeltafrombrainimaging AT millerk estimationofbrainagedeltafrombrainimaging |