Cargando…
Histopathologic brain age estimation via multiple instance learning
Understanding age acceleration, the discordance between biological and chronological age, in the brain can reveal mechanistic insights into normal physiology as well as elucidate pathological determinants of age-related functional decline and identify early disease changes in the context of Alzheime...
Autores principales: | , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10627911/ https://www.ncbi.nlm.nih.gov/pubmed/37815677 http://dx.doi.org/10.1007/s00401-023-02636-3 |
_version_ | 1785131632714317824 |
---|---|
author | Marx, Gabriel A. Kauffman, Justin McKenzie, Andrew T. Koenigsberg, Daniel G. McMillan, Cory T. Morgello, Susan Karlovich, Esma Insausti, Ricardo Richardson, Timothy E. Walker, Jamie M. White, Charles L. Babrowicz, Bergan M. Shen, Li McKee, Ann C. Stein, Thor D. Farrell, Kurt Crary, John F. |
author_facet | Marx, Gabriel A. Kauffman, Justin McKenzie, Andrew T. Koenigsberg, Daniel G. McMillan, Cory T. Morgello, Susan Karlovich, Esma Insausti, Ricardo Richardson, Timothy E. Walker, Jamie M. White, Charles L. Babrowicz, Bergan M. Shen, Li McKee, Ann C. Stein, Thor D. Farrell, Kurt Crary, John F. |
author_sort | Marx, Gabriel A. |
collection | PubMed |
description | Understanding age acceleration, the discordance between biological and chronological age, in the brain can reveal mechanistic insights into normal physiology as well as elucidate pathological determinants of age-related functional decline and identify early disease changes in the context of Alzheimer’s and other disorders. Histopathological whole slide images provide a wealth of pathologic data on the cellular level that can be leveraged to build deep learning models to assess age acceleration. Here, we used a collection of digitized human post-mortem hippocampal sections to develop a histological brain age estimation model. Our model predicted brain age within a mean absolute error of 5.45 ± 0.22 years, with attention weights corresponding to neuroanatomical regions vulnerable to age-related changes. We found that histopathologic brain age acceleration had significant associations with clinical and pathologic outcomes that were not found with epigenetic based measures. Our results indicate that histopathologic brain age is a powerful, independent metric for understanding factors that contribute to brain aging. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00401-023-02636-3. |
format | Online Article Text |
id | pubmed-10627911 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-106279112023-11-08 Histopathologic brain age estimation via multiple instance learning Marx, Gabriel A. Kauffman, Justin McKenzie, Andrew T. Koenigsberg, Daniel G. McMillan, Cory T. Morgello, Susan Karlovich, Esma Insausti, Ricardo Richardson, Timothy E. Walker, Jamie M. White, Charles L. Babrowicz, Bergan M. Shen, Li McKee, Ann C. Stein, Thor D. Farrell, Kurt Crary, John F. Acta Neuropathol Original Paper Understanding age acceleration, the discordance between biological and chronological age, in the brain can reveal mechanistic insights into normal physiology as well as elucidate pathological determinants of age-related functional decline and identify early disease changes in the context of Alzheimer’s and other disorders. Histopathological whole slide images provide a wealth of pathologic data on the cellular level that can be leveraged to build deep learning models to assess age acceleration. Here, we used a collection of digitized human post-mortem hippocampal sections to develop a histological brain age estimation model. Our model predicted brain age within a mean absolute error of 5.45 ± 0.22 years, with attention weights corresponding to neuroanatomical regions vulnerable to age-related changes. We found that histopathologic brain age acceleration had significant associations with clinical and pathologic outcomes that were not found with epigenetic based measures. Our results indicate that histopathologic brain age is a powerful, independent metric for understanding factors that contribute to brain aging. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00401-023-02636-3. Springer Berlin Heidelberg 2023-10-10 2023 /pmc/articles/PMC10627911/ /pubmed/37815677 http://dx.doi.org/10.1007/s00401-023-02636-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Paper Marx, Gabriel A. Kauffman, Justin McKenzie, Andrew T. Koenigsberg, Daniel G. McMillan, Cory T. Morgello, Susan Karlovich, Esma Insausti, Ricardo Richardson, Timothy E. Walker, Jamie M. White, Charles L. Babrowicz, Bergan M. Shen, Li McKee, Ann C. Stein, Thor D. Farrell, Kurt Crary, John F. Histopathologic brain age estimation via multiple instance learning |
title | Histopathologic brain age estimation via multiple instance learning |
title_full | Histopathologic brain age estimation via multiple instance learning |
title_fullStr | Histopathologic brain age estimation via multiple instance learning |
title_full_unstemmed | Histopathologic brain age estimation via multiple instance learning |
title_short | Histopathologic brain age estimation via multiple instance learning |
title_sort | histopathologic brain age estimation via multiple instance learning |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10627911/ https://www.ncbi.nlm.nih.gov/pubmed/37815677 http://dx.doi.org/10.1007/s00401-023-02636-3 |
work_keys_str_mv | AT marxgabriela histopathologicbrainageestimationviamultipleinstancelearning AT kauffmanjustin histopathologicbrainageestimationviamultipleinstancelearning AT mckenzieandrewt histopathologicbrainageestimationviamultipleinstancelearning AT koenigsbergdanielg histopathologicbrainageestimationviamultipleinstancelearning AT mcmillancoryt histopathologicbrainageestimationviamultipleinstancelearning AT morgellosusan histopathologicbrainageestimationviamultipleinstancelearning AT karlovichesma histopathologicbrainageestimationviamultipleinstancelearning AT insaustiricardo histopathologicbrainageestimationviamultipleinstancelearning AT richardsontimothye histopathologicbrainageestimationviamultipleinstancelearning AT walkerjamiem histopathologicbrainageestimationviamultipleinstancelearning AT whitecharlesl histopathologicbrainageestimationviamultipleinstancelearning AT babrowiczberganm histopathologicbrainageestimationviamultipleinstancelearning AT shenli histopathologicbrainageestimationviamultipleinstancelearning AT mckeeannc histopathologicbrainageestimationviamultipleinstancelearning AT steinthord histopathologicbrainageestimationviamultipleinstancelearning AT histopathologicbrainageestimationviamultipleinstancelearning AT farrellkurt histopathologicbrainageestimationviamultipleinstancelearning AT craryjohnf histopathologicbrainageestimationviamultipleinstancelearning |