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Integrating multiple brain imaging modalities does not boost prediction of subclinical atherosclerosis in midlife adults
BACKGROUND: Human neuroimaging evidence suggests that cardiovascular disease (CVD) risk may relate to functional and structural features of the brain. The present study tested whether combining functional and structural (multimodal) brain measures, derived from magnetic resonance imaging (MRI), woul...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9421527/ https://www.ncbi.nlm.nih.gov/pubmed/36002967 http://dx.doi.org/10.1016/j.nicl.2022.103134 |
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author | Sentis, Amy Isabella Rasero, Javier Gianaros, Peter J. Verstynen, Timothy D. |
author_facet | Sentis, Amy Isabella Rasero, Javier Gianaros, Peter J. Verstynen, Timothy D. |
author_sort | Sentis, Amy Isabella |
collection | PubMed |
description | BACKGROUND: Human neuroimaging evidence suggests that cardiovascular disease (CVD) risk may relate to functional and structural features of the brain. The present study tested whether combining functional and structural (multimodal) brain measures, derived from magnetic resonance imaging (MRI), would yield a multivariate brain biomarker that reliably predicts a subclinical marker of CVD risk, carotid-artery intima-media thickness (CA-IMT). METHODS: Neuroimaging, cardiovascular, and demographic data were assessed in 324 midlife and otherwise healthy adults who were free of (a) clinical CVD and (b) use of medications for chronic illnesses (aged 30–51 years, 49% female). We implemented a prediction stacking algorithm that combined multimodal brain imaging measures and Framingham Risk Scores (FRS) to predict CA-IMT. We included imaging measures that could be easily obtained in clinical settings: resting state functional connectivity and structural morphology measures from T1-weighted images. RESULTS: Our models reliably predicted CA-IMT using FRS, as well as for several individual MRI measures; however, none of the individual MRI measures outperformed FRS. Moreover, stacking functional and structural brain measures with FRS did not boost prediction accuracy above that of FRS alone. CONCLUSIONS: Combining multimodal functional and structural brain measures through a stacking algorithm does not appear to yield a reliable brain biomarker of subclinical CVD, as reflected by CA-IMT. |
format | Online Article Text |
id | pubmed-9421527 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-94215272022-08-30 Integrating multiple brain imaging modalities does not boost prediction of subclinical atherosclerosis in midlife adults Sentis, Amy Isabella Rasero, Javier Gianaros, Peter J. Verstynen, Timothy D. Neuroimage Clin Regular Article BACKGROUND: Human neuroimaging evidence suggests that cardiovascular disease (CVD) risk may relate to functional and structural features of the brain. The present study tested whether combining functional and structural (multimodal) brain measures, derived from magnetic resonance imaging (MRI), would yield a multivariate brain biomarker that reliably predicts a subclinical marker of CVD risk, carotid-artery intima-media thickness (CA-IMT). METHODS: Neuroimaging, cardiovascular, and demographic data were assessed in 324 midlife and otherwise healthy adults who were free of (a) clinical CVD and (b) use of medications for chronic illnesses (aged 30–51 years, 49% female). We implemented a prediction stacking algorithm that combined multimodal brain imaging measures and Framingham Risk Scores (FRS) to predict CA-IMT. We included imaging measures that could be easily obtained in clinical settings: resting state functional connectivity and structural morphology measures from T1-weighted images. RESULTS: Our models reliably predicted CA-IMT using FRS, as well as for several individual MRI measures; however, none of the individual MRI measures outperformed FRS. Moreover, stacking functional and structural brain measures with FRS did not boost prediction accuracy above that of FRS alone. CONCLUSIONS: Combining multimodal functional and structural brain measures through a stacking algorithm does not appear to yield a reliable brain biomarker of subclinical CVD, as reflected by CA-IMT. Elsevier 2022-07-29 /pmc/articles/PMC9421527/ /pubmed/36002967 http://dx.doi.org/10.1016/j.nicl.2022.103134 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Regular Article Sentis, Amy Isabella Rasero, Javier Gianaros, Peter J. Verstynen, Timothy D. Integrating multiple brain imaging modalities does not boost prediction of subclinical atherosclerosis in midlife adults |
title | Integrating multiple brain imaging modalities does not boost prediction of subclinical atherosclerosis in midlife adults |
title_full | Integrating multiple brain imaging modalities does not boost prediction of subclinical atherosclerosis in midlife adults |
title_fullStr | Integrating multiple brain imaging modalities does not boost prediction of subclinical atherosclerosis in midlife adults |
title_full_unstemmed | Integrating multiple brain imaging modalities does not boost prediction of subclinical atherosclerosis in midlife adults |
title_short | Integrating multiple brain imaging modalities does not boost prediction of subclinical atherosclerosis in midlife adults |
title_sort | integrating multiple brain imaging modalities does not boost prediction of subclinical atherosclerosis in midlife adults |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9421527/ https://www.ncbi.nlm.nih.gov/pubmed/36002967 http://dx.doi.org/10.1016/j.nicl.2022.103134 |
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