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Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth
Brain predicted age difference, or BrainPAD, compares chronological age to an age estimate derived by applying machine learning (ML) to MRI brain data. BrainPAD studies in youth have been relatively limited, often using only a single MRI modality or a single ML algorithm. Here, we use multimodal MRI...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8410534/ https://www.ncbi.nlm.nih.gov/pubmed/34240783 http://dx.doi.org/10.1002/hbm.25565 |
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author | Luna, Alex Bernanke, Joel Kim, Kakyeong Aw, Natalie Dworkin, Jordan D. Cha, Jiook Posner, Jonathan |
author_facet | Luna, Alex Bernanke, Joel Kim, Kakyeong Aw, Natalie Dworkin, Jordan D. Cha, Jiook Posner, Jonathan |
author_sort | Luna, Alex |
collection | PubMed |
description | Brain predicted age difference, or BrainPAD, compares chronological age to an age estimate derived by applying machine learning (ML) to MRI brain data. BrainPAD studies in youth have been relatively limited, often using only a single MRI modality or a single ML algorithm. Here, we use multimodal MRI with a stacked ensemble ML approach that iteratively applies several ML algorithms (AutoML). Eligible participants in the Healthy Brain Network (N = 489) were split into training and test sets. Morphometry estimates, white matter connectomes, or both were entered into AutoML to develop BrainPAD models. The best model was then applied to a held‐out evaluation dataset, and associations with psychometrics were estimated. Models using morphometry and connectomes together had a mean absolute error of 1.18 years, outperforming models using a single MRI modality. Lower BrainPAD values were associated with more symptoms on the CBCL (p (corr) = .012) and lower functioning on the Children's Global Assessment Scale (p (corr) = .012). Higher BrainPAD values were associated with better performance on the Flanker task (p (corr) = .008). Brain age prediction was more accurate using ComBat‐harmonized brain data (MAE = 0.26). Associations with psychometric measures remained consistent after ComBat harmonization, though only the association with CGAS reached statistical significance in the reduced sample. Our findings suggest that BrainPAD scores derived from unharmonized multimodal MRI data using an ensemble ML approach may offer a clinically relevant indicator of psychiatric and cognitive functioning in youth. |
format | Online Article Text |
id | pubmed-8410534 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84105342021-09-03 Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth Luna, Alex Bernanke, Joel Kim, Kakyeong Aw, Natalie Dworkin, Jordan D. Cha, Jiook Posner, Jonathan Hum Brain Mapp Research Articles Brain predicted age difference, or BrainPAD, compares chronological age to an age estimate derived by applying machine learning (ML) to MRI brain data. BrainPAD studies in youth have been relatively limited, often using only a single MRI modality or a single ML algorithm. Here, we use multimodal MRI with a stacked ensemble ML approach that iteratively applies several ML algorithms (AutoML). Eligible participants in the Healthy Brain Network (N = 489) were split into training and test sets. Morphometry estimates, white matter connectomes, or both were entered into AutoML to develop BrainPAD models. The best model was then applied to a held‐out evaluation dataset, and associations with psychometrics were estimated. Models using morphometry and connectomes together had a mean absolute error of 1.18 years, outperforming models using a single MRI modality. Lower BrainPAD values were associated with more symptoms on the CBCL (p (corr) = .012) and lower functioning on the Children's Global Assessment Scale (p (corr) = .012). Higher BrainPAD values were associated with better performance on the Flanker task (p (corr) = .008). Brain age prediction was more accurate using ComBat‐harmonized brain data (MAE = 0.26). Associations with psychometric measures remained consistent after ComBat harmonization, though only the association with CGAS reached statistical significance in the reduced sample. Our findings suggest that BrainPAD scores derived from unharmonized multimodal MRI data using an ensemble ML approach may offer a clinically relevant indicator of psychiatric and cognitive functioning in youth. John Wiley & Sons, Inc. 2021-07-09 /pmc/articles/PMC8410534/ /pubmed/34240783 http://dx.doi.org/10.1002/hbm.25565 Text en © 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Articles Luna, Alex Bernanke, Joel Kim, Kakyeong Aw, Natalie Dworkin, Jordan D. Cha, Jiook Posner, Jonathan Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth |
title | Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth |
title_full | Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth |
title_fullStr | Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth |
title_full_unstemmed | Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth |
title_short | Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth |
title_sort | maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8410534/ https://www.ncbi.nlm.nih.gov/pubmed/34240783 http://dx.doi.org/10.1002/hbm.25565 |
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