Bayesian Optimization for Neuroimaging Pre-processing in Brain Age Classification and Prediction.

Frontiers in Aging Neuroscience
Jenessa LancasterJames H Cole

Abstract

Neuroimaging-based age prediction using machine learning is proposed as a biomarker of brain aging, relating to cognitive performance, health outcomes and progression of neurodegenerative disease. However, even leading age-prediction algorithms contain measurement error, motivating efforts to improve experimental pipelines. T1-weighted MRI is commonly used for age prediction, and the pre-processing of these scans involves normalization to a common template and resampling to a common voxel size, followed by spatial smoothing. Resampling parameters are often selected arbitrarily. Here, we sought to improve brain-age prediction accuracy by optimizing resampling parameters using Bayesian optimization. Using data on N = 2003 healthy individuals (aged 16-90 years) we trained support vector machines to (i) distinguish between young (<22 years) and old (>50 years) brains (classification) and (ii) predict chronological age (regression). We also evaluated generalisability of the age-regression model to an independent dataset (CamCAN, N = 648, aged 18-88 years). Bayesian optimization was used to identify optimal voxel size and smoothing kernel size for each task. This procedure adaptively samples the parameter space to evaluate accuracy a...Continue Reading

References

May 24, 2005·NeuroImage·Derek K JonesRobert J Howard
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Jan 15, 2010·NeuroImage·Katja FrankeUNKNOWN Alzheimer's Disease Neuroimaging Initiative
Dec 6, 2011·PloS One·Jonathan S AdelsteinMichael P Milham
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Jun 4, 2013·Medical Image Analysis·Ender KonukogluAntonio Criminisi
Aug 30, 2013·Frontiers in Neuroinformatics·Adrian AndronacheUNKNOWN Coma Research Centre (CRC) – Besta Institute
Oct 16, 2013·Schizophrenia Bulletin·Nikolaos KoutsoulerisEva Meisenzahl
Nov 8, 2014·Brain Imaging and Behavior·Andrei IrimiaJohn D Van Horn
Jan 28, 2015·Annals of Neurology·James H ColeUNKNOWN Alzheimer's Disease Neuroimaging Initiative
Jul 15, 2016·PloS One·Luise Christine LöweUNKNOWN Alzheimer’s Disease Neuroimaging Initiative
Nov 29, 2016·NeuroImage·Franziskus LiemDaniel S Margulies
Feb 27, 2017·Trends in Cognitive Sciences·Romy LorenzRobert Leech
Mar 5, 2017·Neurology·James H ColeUNKNOWN COBRA collaboration
Apr 15, 2017·Epilepsy Research·Heath R PardoeUNKNOWN Human Epilepsy Project Investigators
Apr 26, 2017·Molecular Psychiatry·J H ColeI J Deary

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Citations

Jul 13, 2019·Journal of Medical Systems·Hedieh Sajedi, Nastaran Pardakhti
Mar 14, 2019·Frontiers in Human Neuroscience·Jian Zhai, Ke Li
Nov 5, 2019·Wellcome Open Research·James H ColeRobert Leech
Dec 4, 2019·Frontiers in Neuroscience·Raymond SalvadorEdith Pomarol-Clotet
Dec 22, 2020·Frontiers in Psychiatry·Pedro F Da CostaWalter H L Pinaya
Nov 17, 2020·Frontiers in Neurology·Jin HongMing Yang
Nov 18, 2020·International Journal of Psychophysiology : Official Journal of the International Organization of Psychophysiology·Panteleimon ChriskosPanagiotis D Bamidis
Apr 20, 2020·Neurobiology of Aging·Xinyang FengUNKNOWN Frontotemporal Lobar Degeneration Neuroimaging Initiative
Jul 1, 2021·Human Brain Mapping·Ellyn R ButlerRussell T Shinohara
Jun 4, 2020·Aging and Disease·Iman BeheshtiHiroshi Matsuda
Aug 3, 2021·ACM Transactions on Intelligent Systems and Technology·Jessamyn Dahmen, Diane J Cook

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Software Mentioned

MATLAB
SPM12
CamCAN
DARTEL
MATLAB Bayesian Optimization Algorithm 2

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