Goal-specific brain MRI harmonization
Goal-specific brain MRI harmonization
Abstract There is significant interest in pooling magnetic resonance image (MRI) data from multiple datasets to enable mega-analysis. Harmonization is typically performed to reduce heterogeneity when pooling MRI data across datasets. Most MRI harmonization algorithms do not explicitly consider downstream application performance during harmonization. However, the choice of downstream application might influence what might be considered as study-specific confounds. Therefore, ignoring downstream applications during harmonization might potentially limit downstream performance. Here we propose a goal-specific harmonization framework that utilizes downstream application performance to regularize the harmonization procedure. Our framework can be integrated with a wide variety of harmonization models based on deep neural networks, such as the recently proposed conditional variational autoencoder (cVAE) harmonization model. Three datasets from three different continents with a total of 2787 participants and 10085 anatomical T1 scans were used for evaluation. We found that cVAE removed more dataset differences than the widely used ComBat model, but at the expense of removing desirable biological information as measured by downstream prediction of mini mental state examination (MMSE) scores and clinical diagnoses. On the other hand, our goal-specific cVAE (gcVAE) was able to remove as much dataset differences as cVAE, while improving downstream cross-sectional prediction of MMSE scores and clinical diagnoses.
An Lijun、Chen Jianzhong、Yeo B.T. Thomas、He Tong、the Australian Imaging Biomarkers and Lifestyle Study of Aging、Zhang Chen、Chen Pansheng、Chen Christopher、Zhou Juan Helen、the Alzheimer?ˉs Disease Neuroimaging Initiative
Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore||Department of Electrical and Computer Engineering, National University of Singapore||N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of SingaporeCentre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore||Department of Electrical and Computer Engineering, National University of Singapore||N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of SingaporeCentre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore||Department of Electrical and Computer Engineering, National University of Singapore||N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore||NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore||Martinos Center for Biomedical Imaging, Massachusetts General HospitalCentre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore||Department of Electrical and Computer Engineering, National University of Singapore||N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of SingaporeCentre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore||Department of Electrical and Computer Engineering, National University of Singapore||N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of SingaporeCentre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore||Department of Electrical and Computer Engineering, National University of Singapore||N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of SingaporeDepartment of Pharmacology, Yong Loo Lin School of Medicine, National University of SingaporeCentre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore||Department of Electrical and Computer Engineering, National University of Singapore||NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore
医学研究方法基础医学生物科学研究方法、生物科学研究技术
An Lijun,Chen Jianzhong,Yeo B.T. Thomas,He Tong,the Australian Imaging Biomarkers and Lifestyle Study of Aging,Zhang Chen,Chen Pansheng,Chen Christopher,Zhou Juan Helen,the Alzheimer?ˉs Disease Neuroimaging Initiative.Goal-specific brain MRI harmonization[EB/OL].(2025-03-28)[2025-05-15].https://www.biorxiv.org/content/10.1101/2022.03.05.483077.点此复制
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